diff --git "a/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/PCB\345\255\227\347\254\246\350\257\206\345\210\253.md" "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/PCB\345\255\227\347\254\246\350\257\206\345\210\253.md" new file mode 100644 index 0000000000000000000000000000000000000000..a5052e2897ab9f09a6ed7b747f9fa1198af2a8ab --- /dev/null +++ "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/PCB\345\255\227\347\254\246\350\257\206\345\210\253.md" @@ -0,0 +1,648 @@ +# 基于PP-OCRv3的PCB字符识别 + +- [1. 项目介绍](#1-项目介绍) +- [2. 安装说明](#2-安装说明) +- [3. 数据准备](#3-数据准备) +- [4. 文本检测](#4-文本检测) + - [4.1 预训练模型直接评估](#41-预训练模型直接评估) + - [4.2 预训练模型+验证集padding直接评估](#42-预训练模型验证集padding直接评估) + - [4.3 预训练模型+fine-tune](#43-预训练模型fine-tune) +- [5. 文本识别](#5-文本识别) + - [5.1 预训练模型直接评估](#51-预训练模型直接评估) + - [5.2 三种fine-tune方案](#52-三种fine-tune方案) +- [6. 模型导出](#6-模型导出) +- [7. 端对端评测](#7-端对端评测) +- [8. Jetson部署](#8-Jetson部署) +- [9. 总结](#9-总结) +- [更多资源](#更多资源) + +# 1. 项目介绍 + +印刷电路板(PCB)是电子产品中的核心器件,对于板件质量的测试与监控是生产中必不可少的环节。在一些场景中,通过PCB中信号灯颜色和文字组合可以定位PCB局部模块质量问题,PCB文字识别中存在如下难点: + +- 裁剪出的PCB图片宽高比例较小 +- 文字区域整体面积也较小 +- 包含垂直、水平多种方向文本 + +针对本场景,PaddleOCR基于全新的PP-OCRv3通过合成数据、微调以及其他场景适配方法完成小字符文本识别任务,满足企业上线要求。PCB检测、识别效果如 **图1** 所示: + +
+
图1 PCB检测识别效果
+ +注:欢迎在AIStudio领取免费算力体验线上实训,项目链接: [基于PP-OCRv3实现PCB字符识别](https://aistudio.baidu.com/aistudio/projectdetail/4008973) + +# 2. 安装说明 + + +下载PaddleOCR源码,安装依赖环境。 + + +```python +# 如仍需安装or安装更新,可以执行以下步骤 +git clone https://github.com/PaddlePaddle/PaddleOCR.git +# git clone https://gitee.com/PaddlePaddle/PaddleOCR +``` + + +```python +# 安装依赖包 +pip install -r /home/aistudio/PaddleOCR/requirements.txt +``` + +# 3. 数据准备 + +我们通过图片合成工具生成 **图2** 所示的PCB图片,整图只有高25、宽150左右、文字区域高9、宽45左右,包含垂直和水平2种方向的文本: + +
+
图2 数据集示例
+ +暂时不开源生成的PCB数据集,但是通过更换背景,通过如下代码生成数据即可: + +``` +cd gen_data +python3 gen.py --num_img=10 +``` + +生成图片参数解释: + +``` +num_img:生成图片数量 +font_min_size、font_max_size:字体最大、最小尺寸 +bg_path:文字区域背景存放路径 +det_bg_path:整图背景存放路径 +fonts_path:字体路径 +corpus_path:语料路径 +output_dir:生成图片存储路径 +``` + +这里生成 **100张** 相同尺寸和文本的图片,如 **图3** 所示,方便大家跑通实验。通过如下代码解压数据集: + +
+
图3 案例提供数据集示例
+ + +```python +tar xf ./data/data148165/dataset.tar -C ./ +``` + +在生成数据集的时需要生成检测和识别训练需求的格式: + + +- **文本检测** + +标注文件格式如下,中间用'\t'分隔: + +``` +" 图像文件名 json.dumps编码的图像标注信息" +ch4_test_images/img_61.jpg [{"transcription": "MASA", "points": [[310, 104], [416, 141], [418, 216], [312, 179]]}, {...}] +``` + +json.dumps编码前的图像标注信息是包含多个字典的list,字典中的 `points` 表示文本框的四个点的坐标(x, y),从左上角的点开始顺时针排列。 `transcription` 表示当前文本框的文字,***当其内容为“###”时,表示该文本框无效,在训练时会跳过。*** + +- **文本识别** + +标注文件的格式如下, txt文件中默认请将图片路径和图片标签用'\t'分割,如用其他方式分割将造成训练报错。 + +``` +" 图像文件名 图像标注信息 " + +train_data/rec/train/word_001.jpg 简单可依赖 +train_data/rec/train/word_002.jpg 用科技让复杂的世界更简单 +... +``` + + +# 4. 文本检测 + +选用飞桨OCR开发套件[PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)中的PP-OCRv3模型进行文本检测和识别。针对检测模型和识别模型,进行了共计9个方面的升级: + +- PP-OCRv3检测模型对PP-OCRv2中的CML协同互学习文本检测蒸馏策略进行了升级,分别针对教师模型和学生模型进行进一步效果优化。其中,在对教师模型优化时,提出了大感受野的PAN结构LK-PAN和引入了DML蒸馏策略;在对学生模型优化时,提出了残差注意力机制的FPN结构RSE-FPN。 + +- PP-OCRv3的识别模块是基于文本识别算法SVTR优化。SVTR不再采用RNN结构,通过引入Transformers结构更加有效地挖掘文本行图像的上下文信息,从而提升文本识别能力。PP-OCRv3通过轻量级文本识别网络SVTR_LCNet、Attention损失指导CTC损失训练策略、挖掘文字上下文信息的数据增广策略TextConAug、TextRotNet自监督预训练模型、UDML联合互学习策略、UIM无标注数据挖掘方案,6个方面进行模型加速和效果提升。 + +更多细节请参考PP-OCRv3[技术报告](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.5/doc/doc_ch/PP-OCRv3_introduction.md)。 + + +我们使用 **3种方案** 进行检测模型的训练、评估: +- **PP-OCRv3英文超轻量检测预训练模型直接评估** +- PP-OCRv3英文超轻量检测预训练模型 + **验证集padding**直接评估 +- PP-OCRv3英文超轻量检测预训练模型 + **fine-tune** + +## **4.1 预训练模型直接评估** + +我们首先通过PaddleOCR提供的预训练模型在验证集上进行评估,如果评估指标能满足效果,可以直接使用预训练模型,不再需要训练。 + +使用预训练模型直接评估步骤如下: + +**1)下载预训练模型** + + +PaddleOCR已经提供了PP-OCR系列模型,部分模型展示如下表所示: + +| 模型简介 | 模型名称 | 推荐场景 | 检测模型 | 方向分类器 | 识别模型 | +| ------------------------------------- | ----------------------- | --------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | +| 中英文超轻量PP-OCRv3模型(16.2M) | ch_PP-OCRv3_xx | 移动端&服务器端 | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) | +| 英文超轻量PP-OCRv3模型(13.4M) | en_PP-OCRv3_xx | 移动端&服务器端 | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) | +| 中英文超轻量PP-OCRv2模型(13.0M) | ch_PP-OCRv2_xx | 移动端&服务器端 | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_train.tar) | +| 中英文超轻量PP-OCR mobile模型(9.4M) | ch_ppocr_mobile_v2.0_xx | 移动端&服务器端 | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_pre.tar) | +| 中英文通用PP-OCR server模型(143.4M) | ch_ppocr_server_v2.0_xx | 服务器端 | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_pre.tar) | + +更多模型下载(包括多语言),可以参[考PP-OCR系列模型下载](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.5/doc/doc_ch/models_list.md) + +这里我们使用PP-OCRv3英文超轻量检测模型,下载并解压预训练模型: + + + + +```python +# 如果更换其他模型,更新下载链接和解压指令就可以 +cd /home/aistudio/PaddleOCR +mkdir pretrain_models +cd pretrain_models +# 下载英文预训练模型 +wget https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar +tar xf en_PP-OCRv3_det_distill_train.tar && rm -rf en_PP-OCRv3_det_distill_train.tar +%cd .. +``` + +**模型评估** + + +首先修改配置文件`configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml`中的以下字段: +``` +Eval.dataset.data_dir:指向验证集图片存放目录,'/home/aistudio/dataset' +Eval.dataset.label_file_list:指向验证集标注文件,'/home/aistudio/dataset/det_gt_val.txt' +Eval.dataset.transforms.DetResizeForTest: 尺寸 + limit_side_len: 48 + limit_type: 'min' +``` + +然后在验证集上进行评估,具体代码如下: + + + +```python +cd /home/aistudio/PaddleOCR +python tools/eval.py \ + -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml \ + -o Global.checkpoints="./pretrain_models/en_PP-OCRv3_det_distill_train/best_accuracy" +``` + +## **4.2 预训练模型+验证集padding直接评估** + +考虑到PCB图片比较小,宽度只有25左右、高度只有140-170左右,我们在原图的基础上进行padding,再进行检测评估,padding前后效果对比如 **图4** 所示: + +
+
图4 padding前后对比图
+ +将图片都padding到300*300大小,因为坐标信息发生了变化,我们同时要修改标注文件,在`/home/aistudio/dataset`目录里也提供了padding之后的图片,大家也可以尝试训练和评估: + +同上,我们需要修改配置文件`configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml`中的以下字段: +``` +Eval.dataset.data_dir:指向验证集图片存放目录,'/home/aistudio/dataset' +Eval.dataset.label_file_list:指向验证集标注文件,/home/aistudio/dataset/det_gt_padding_val.txt +Eval.dataset.transforms.DetResizeForTest: 尺寸 + limit_side_len: 1100 + limit_type: 'min' +``` + +然后执行评估代码 + + +```python +cd /home/aistudio/PaddleOCR +python tools/eval.py \ + -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml \ + -o Global.checkpoints="./pretrain_models/en_PP-OCRv3_det_distill_train/best_accuracy" +``` + +## **4.3 预训练模型+fine-tune** + + +基于预训练模型,在生成的1500图片上进行fine-tune训练和评估,其中train数据1200张,val数据300张,修改配置文件`configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml`中的以下字段: +``` +Global.epoch_num: 这里设置为1,方便快速跑通,实际中根据数据量调整该值 +Global.save_model_dir:模型保存路径 +Global.pretrained_model:指向预训练模型路径,'./pretrain_models/en_PP-OCRv3_det_distill_train/student.pdparams' +Optimizer.lr.learning_rate:调整学习率,本实验设置为0.0005 +Train.dataset.data_dir:指向训练集图片存放目录,'/home/aistudio/dataset' +Train.dataset.label_file_list:指向训练集标注文件,'/home/aistudio/dataset/det_gt_train.txt' +Train.dataset.transforms.EastRandomCropData.size:训练尺寸改为[480,64] +Eval.dataset.data_dir:指向验证集图片存放目录,'/home/aistudio/dataset/' +Eval.dataset.label_file_list:指向验证集标注文件,'/home/aistudio/dataset/det_gt_val.txt' +Eval.dataset.transforms.DetResizeForTest:评估尺寸,添加如下参数 + limit_side_len: 64 + limit_type:'min' +``` +执行下面命令启动训练: + + +```python +cd /home/aistudio/PaddleOCR/ +python tools/train.py \ + -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml +``` + +**模型评估** + + +使用训练好的模型进行评估,更新模型路径`Global.checkpoints`: + + +```python +cd /home/aistudio/PaddleOCR/ +python3 tools/eval.py \ + -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml \ + -o Global.checkpoints="./output/ch_PP-OCR_V3_det/latest" +``` + +使用训练好的模型进行评估,指标如下所示: + + +| 序号 | 方案 | hmean | 效果提升 | 实验分析 | +| -------- | -------- | -------- | -------- | -------- | +| 1 | PP-OCRv3英文超轻量检测预训练模型 | 64.64% | - | 提供的预训练模型具有泛化能力 | +| 2 | PP-OCRv3英文超轻量检测预训练模型 + 验证集padding | 72.13% |+7.5% | padding可以提升尺寸较小图片的检测效果| +| 3 | PP-OCRv3英文超轻量检测预训练模型 + fine-tune | 100% | +27.9% | fine-tune会提升垂类场景效果 | + + +``` +注:上述实验结果均是在1500张图片(1200张训练集,300张测试集)上训练、评估的得到,AIstudio只提供了100张数据,所以指标有所差异属于正常,只要策略有效、规律相同即可。 +``` + +# 5. 文本识别 + +我们分别使用如下4种方案进行训练、评估: + +- **方案1**:**PP-OCRv3中英文超轻量识别预训练模型直接评估** +- **方案2**:PP-OCRv3中英文超轻量检测预训练模型 + **fine-tune** +- **方案3**:PP-OCRv3中英文超轻量检测预训练模型 + fine-tune + **公开通用识别数据集** +- **方案4**:PP-OCRv3中英文超轻量检测预训练模型 + fine-tune + **增加PCB图像数量** + + +## **5.1 预训练模型直接评估** + +同检测模型,我们首先使用PaddleOCR提供的识别预训练模型在PCB验证集上进行评估。 + +使用预训练模型直接评估步骤如下: + +**1)下载预训练模型** + + +我们使用PP-OCRv3中英文超轻量文本识别模型,下载并解压预训练模型: + + +```python +# 如果更换其他模型,更新下载链接和解压指令就可以 +cd /home/aistudio/PaddleOCR/pretrain_models/ +wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar +tar xf ch_PP-OCRv3_rec_train.tar && rm -rf ch_PP-OCRv3_rec_train.tar +cd .. +``` + +**模型评估** + + +首先修改配置文件`configs/det/ch_PP-OCRv3/ch_PP-OCRv2_rec_distillation.yml`中的以下字段: + +``` +Metric.ignore_space: True:忽略空格 +Eval.dataset.data_dir:指向验证集图片存放目录,'/home/aistudio/dataset' +Eval.dataset.label_file_list:指向验证集标注文件,'/home/aistudio/dataset/rec_gt_val.txt' +``` + +我们使用下载的预训练模型进行评估: + + +```python +cd /home/aistudio/PaddleOCR +python3 tools/eval.py \ + -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml \ + -o Global.checkpoints=pretrain_models/ch_PP-OCRv3_rec_train/best_accuracy + +``` + +## **5.2 三种fine-tune方案** + +方案2、3、4训练和评估方式是相同的,因此在我们了解每个技术方案之后,再具体看修改哪些参数是相同,哪些是不同的。 + +**方案介绍:** + +1) **方案2**:预训练模型 + **fine-tune** + +- 在预训练模型的基础上进行fine-tune,使用1500张PCB进行训练和评估,其中训练集1200张,验证集300张。 + + +2) **方案3**:预训练模型 + fine-tune + **公开通用识别数据集** + +- 当识别数据比较少的情况,可以考虑添加公开通用识别数据集。在方案2的基础上,添加公开通用识别数据集,如lsvt、rctw等。 + +3)**方案4**:预训练模型 + fine-tune + **增加PCB图像数量** + +- 如果能够获取足够多真实场景,我们可以通过增加数据量提升模型效果。在方案2的基础上,增加PCB的数量到2W张左右。 + + +**参数修改:** + +接着我们看需要修改的参数,以上方案均需要修改配置文件`configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml`的参数,**修改一次即可**: + +``` +Global.pretrained_model:指向预训练模型路径,'pretrain_models/ch_PP-OCRv3_rec_train/best_accuracy' +Optimizer.lr.values:学习率,本实验设置为0.0005 +Train.loader.batch_size_per_card: batch size,默认128,因为数据量小于128,因此我们设置为8,数据量大可以按默认的训练 +Eval.loader.batch_size_per_card: batch size,默认128,设置为4 +Metric.ignore_space: 忽略空格,本实验设置为True +``` + +**更换不同的方案**每次需要修改的参数: +``` +Global.epoch_num: 这里设置为1,方便快速跑通,实际中根据数据量调整该值 +Global.save_model_dir:指向模型保存路径 +Train.dataset.data_dir:指向训练集图片存放目录 +Train.dataset.label_file_list:指向训练集标注文件 +Eval.dataset.data_dir:指向验证集图片存放目录 +Eval.dataset.label_file_list:指向验证集标注文件 +``` + +同时**方案3**修改以下参数 +``` +Eval.dataset.label_file_list:添加公开通用识别数据标注文件 +Eval.dataset.ratio_list:数据和公开通用识别数据每次采样比例,按实际修改即可 +``` +如 **图5** 所示: +
+
图5 添加公开通用识别数据配置文件示例
+ + +我们提取Student模型的参数,在PCB数据集上进行fine-tune,可以参考如下代码: + + +```python +import paddle +# 加载预训练模型 +all_params = paddle.load("./pretrain_models/ch_PP-OCRv3_rec_train/best_accuracy.pdparams") +# 查看权重参数的keys +print(all_params.keys()) +# 学生模型的权重提取 +s_params = {key[len("student_model."):]: all_params[key] for key in all_params if "student_model." in key} +# 查看学生模型权重参数的keys +print(s_params.keys()) +# 保存 +paddle.save(s_params, "./pretrain_models/ch_PP-OCRv3_rec_train/student.pdparams") +``` + +修改参数后,**每个方案**都执行如下命令启动训练: + + + +```python +cd /home/aistudio/PaddleOCR/ +python3 tools/train.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml +``` + + +使用训练好的模型进行评估,更新模型路径`Global.checkpoints`: + + +```python +cd /home/aistudio/PaddleOCR/ +python3 tools/eval.py \ + -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml \ + -o Global.checkpoints=./output/rec_ppocr_v3/latest +``` + +所有方案评估指标如下: + +| 序号 | 方案 | acc | 效果提升 | 实验分析 | +| -------- | -------- | -------- | -------- | -------- | +| 1 | PP-OCRv3中英文超轻量识别预训练模型直接评估 | 46.67% | - | 提供的预训练模型具有泛化能力 | +| 2 | PP-OCRv3中英文超轻量识别预训练模型 + fine-tune | 42.02% |-4.6% | 在数据量不足的情况,反而比预训练模型效果低(也可以通过调整超参数再试试)| +| 3 | PP-OCRv3中英文超轻量识别预训练模型 + fine-tune + 公开通用识别数据集 | 77% | +30% | 在数据量不足的情况下,可以考虑补充公开数据训练 | +| 4 | PP-OCRv3中英文超轻量识别预训练模型 + fine-tune + 增加PCB图像数量 | 99.99% | +23% | 如果能获取更多数据量的情况,可以通过增加数据量提升效果 | + +``` +注:上述实验结果均是在1500张图片(1200张训练集,300张测试集)、2W张图片、添加公开通用识别数据集上训练、评估的得到,AIstudio只提供了100张数据,所以指标有所差异属于正常,只要策略有效、规律相同即可。 +``` + +# 6. 模型导出 + +inference 模型(paddle.jit.save保存的模型) 一般是模型训练,把模型结构和模型参数保存在文件中的固化模型,多用于预测部署场景。 训练过程中保存的模型是checkpoints模型,保存的只有模型的参数,多用于恢复训练等。 与checkpoints模型相比,inference 模型会额外保存模型的结构信息,在预测部署、加速推理上性能优越,灵活方便,适合于实际系统集成。 + + +```python +# 导出检测模型 +python3 tools/export_model.py \ + -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml \ + -o Global.pretrained_model="./output/ch_PP-OCR_V3_det/latest" \ + Global.save_inference_dir="./inference_model/ch_PP-OCR_V3_det/" +``` + +因为上述模型只训练了1个epoch,因此我们使用训练最优的模型进行预测,存储在`/home/aistudio/best_models/`目录下,解压即可 + + +```python +cd /home/aistudio/best_models/ +wget https://paddleocr.bj.bcebos.com/fanliku/PCB/det_ppocr_v3_en_infer_PCB.tar +tar xf /home/aistudio/best_models/det_ppocr_v3_en_infer_PCB.tar -C /home/aistudio/PaddleOCR/pretrain_models/ +``` + + +```python +# 检测模型inference模型预测 +cd /home/aistudio/PaddleOCR/ +python3 tools/infer/predict_det.py \ + --image_dir="/home/aistudio/dataset/imgs/0000.jpg" \ + --det_algorithm="DB" \ + --det_model_dir="./pretrain_models/det_ppocr_v3_en_infer_PCB/" \ + --det_limit_side_len=48 \ + --det_limit_type='min' \ + --det_db_unclip_ratio=2.5 \ + --use_gpu=True +``` + +结果存储在`inference_results`目录下,检测如下图所示: +
+
图6 检测结果
+ + +同理,导出识别模型并进行推理。 + +```python +# 导出识别模型 +python3 tools/export_model.py \ + -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml \ + -o Global.pretrained_model="./output/rec_ppocr_v3/latest" \ + Global.save_inference_dir="./inference_model/rec_ppocr_v3/" + +``` + +同检测模型,识别模型也只训练了1个epoch,因此我们使用训练最优的模型进行预测,存储在`/home/aistudio/best_models/`目录下,解压即可 + + +```python +cd /home/aistudio/best_models/ +wget https://paddleocr.bj.bcebos.com/fanliku/PCB/rec_ppocr_v3_ch_infer_PCB.tar +tar xf /home/aistudio/best_models/rec_ppocr_v3_ch_infer_PCB.tar -C /home/aistudio/PaddleOCR/pretrain_models/ +``` + + +```python +# 识别模型inference模型预测 +cd /home/aistudio/PaddleOCR/ +python3 tools/infer/predict_rec.py \ + --image_dir="../test_imgs/0000_rec.jpg" \ + --rec_model_dir="./pretrain_models/rec_ppocr_v3_ch_infer_PCB" \ + --rec_image_shape="3, 48, 320" \ + --use_space_char=False \ + --use_gpu=True +``` + +```python +# 检测+识别模型inference模型预测 +cd /home/aistudio/PaddleOCR/ +python3 tools/infer/predict_system.py \ + --image_dir="../test_imgs/0000.jpg" \ + --det_model_dir="./pretrain_models/det_ppocr_v3_en_infer_PCB" \ + --det_limit_side_len=48 \ + --det_limit_type='min' \ + --det_db_unclip_ratio=2.5 \ + --rec_model_dir="./pretrain_models/rec_ppocr_v3_ch_infer_PCB" \ + --rec_image_shape="3, 48, 320" \ + --draw_img_save_dir=./det_rec_infer/ \ + --use_space_char=False \ + --use_angle_cls=False \ + --use_gpu=True + +``` + +端到端预测结果存储在`det_res_infer`文件夹内,结果如下图所示: +
+
图7 检测+识别结果
+ +# 7. 端对端评测 + +接下来介绍文本检测+文本识别的端对端指标评估方式。主要分为三步: + +1)首先运行`tools/infer/predict_system.py`,将`image_dir`改为需要评估的数据文件家,得到保存的结果: + + +```python +# 检测+识别模型inference模型预测 +python3 tools/infer/predict_system.py \ + --image_dir="../dataset/imgs/" \ + --det_model_dir="./pretrain_models/det_ppocr_v3_en_infer_PCB" \ + --det_limit_side_len=48 \ + --det_limit_type='min' \ + --det_db_unclip_ratio=2.5 \ + --rec_model_dir="./pretrain_models/rec_ppocr_v3_ch_infer_PCB" \ + --rec_image_shape="3, 48, 320" \ + --draw_img_save_dir=./det_rec_infer/ \ + --use_space_char=False \ + --use_angle_cls=False \ + --use_gpu=True +``` + +得到保存结果,文本检测识别可视化图保存在`det_rec_infer/`目录下,预测结果保存在`det_rec_infer/system_results.txt`中,格式如下:`0018.jpg [{"transcription": "E295", "points": [[88, 33], [137, 33], [137, 40], [88, 40]]}]` + +2)然后将步骤一保存的数据转换为端对端评测需要的数据格式: 修改 `tools/end2end/convert_ppocr_label.py`中的代码,convert_label函数中设置输入标签路径,Mode,保存标签路径等,对预测数据的GTlabel和预测结果的label格式进行转换。 +``` +ppocr_label_gt = "/home/aistudio/dataset/det_gt_val.txt" +convert_label(ppocr_label_gt, "gt", "./save_gt_label/") + +ppocr_label_gt = "/home/aistudio/PaddleOCR/PCB_result/det_rec_infer/system_results.txt" +convert_label(ppocr_label_gt, "pred", "./save_PPOCRV2_infer/") +``` + +运行`convert_ppocr_label.py`: + + +```python + python3 tools/end2end/convert_ppocr_label.py +``` + +得到如下结果: +``` +├── ./save_gt_label/ +├── ./save_PPOCRV2_infer/ +``` + +3) 最后,执行端对端评测,运行`tools/end2end/eval_end2end.py`计算端对端指标,运行方式如下: + + +```python +pip install editdistance +python3 tools/end2end/eval_end2end.py ./save_gt_label/ ./save_PPOCRV2_infer/ +``` + +使用`预训练模型+fine-tune'检测模型`、`预训练模型 + 2W张PCB图片funetune`识别模型,在300张PCB图片上评估得到如下结果,fmeasure为主要关注的指标: +
+
图8 端到端评估指标
+ +``` +注: 使用上述命令不能跑出该结果,因为数据集不相同,可以更换为自己训练好的模型,按上述流程运行 +``` + +# 8. Jetson部署 + +我们只需要以下步骤就可以完成Jetson nano部署模型,简单易操作: + +**1、在Jetson nano开发版上环境准备:** + +* 安装PaddlePaddle + +* 下载PaddleOCR并安装依赖 + +**2、执行预测** + +* 将推理模型下载到jetson + +* 执行检测、识别、串联预测即可 + +详细[参考流程](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.5/deploy/Jetson/readme_ch.md)。 + +# 9. 总结 + +检测实验分别使用PP-OCRv3预训练模型在PCB数据集上进行了直接评估、验证集padding、 fine-tune 3种方案,识别实验分别使用PP-OCRv3预训练模型在PCB数据集上进行了直接评估、 fine-tune、添加公开通用识别数据集、增加PCB图片数量4种方案,指标对比如下: + +* 检测 + + +| 序号 | 方案 | hmean | 效果提升 | 实验分析 | +| ---- | -------------------------------------------------------- | ------ | -------- | ------------------------------------- | +| 1 | PP-OCRv3英文超轻量检测预训练模型直接评估 | 64.64% | - | 提供的预训练模型具有泛化能力 | +| 2 | PP-OCRv3英文超轻量检测预训练模型 + 验证集padding直接评估 | 72.13% | +7.5% | padding可以提升尺寸较小图片的检测效果 | +| 3 | PP-OCRv3英文超轻量检测预训练模型 + fine-tune | 100% | +27.9% | fine-tune会提升垂类场景效果 | + +* 识别 + +| 序号 | 方案 | acc | 效果提升 | 实验分析 | +| ---- | ------------------------------------------------------------ | ------ | -------- | ------------------------------------------------------------ | +| 1 | PP-OCRv3中英文超轻量识别预训练模型直接评估 | 46.67% | - | 提供的预训练模型具有泛化能力 | +| 2 | PP-OCRv3中英文超轻量识别预训练模型 + fine-tune | 42.02% | -4.6% | 在数据量不足的情况,反而比预训练模型效果低(也可以通过调整超参数再试试) | +| 3 | PP-OCRv3中英文超轻量识别预训练模型 + fine-tune + 公开通用识别数据集 | 77% | +30% | 在数据量不足的情况下,可以考虑补充公开数据训练 | +| 4 | PP-OCRv3中英文超轻量识别预训练模型 + fine-tune + 增加PCB图像数量 | 99.99% | +23% | 如果能获取更多数据量的情况,可以通过增加数据量提升效果 | + +* 端到端 + +| det | rec | fmeasure | +| --------------------------------------------- | ------------------------------------------------------------ | -------- | +| PP-OCRv3英文超轻量检测预训练模型 + fine-tune | PP-OCRv3中英文超轻量识别预训练模型 + fine-tune + 增加PCB图像数量 | 93.3% | + +*结论* + +PP-OCRv3的检测模型在未经过fine-tune的情况下,在PCB数据集上也有64.64%的精度,说明具有泛化能力。验证集padding之后,精度提升7.5%,在图片尺寸较小的情况,我们可以通过padding的方式提升检测效果。经过 fine-tune 后能够极大的提升检测效果,精度达到100%。 + +PP-OCRv3的识别模型方案1和方案2对比可以发现,当数据量不足的情况,预训练模型精度可能比fine-tune效果还要高,所以我们可以先尝试预训练模型直接评估。如果在数据量不足的情况下想进一步提升模型效果,可以通过添加公开通用识别数据集,识别效果提升30%,非常有效。最后如果我们能够采集足够多的真实场景数据集,可以通过增加数据量提升模型效果,精度达到99.99%。 + +# 更多资源 + +- 更多深度学习知识、产业案例、面试宝典等,请参考:[awesome-DeepLearning](https://github.com/paddlepaddle/awesome-DeepLearning) + +- 更多PaddleOCR使用教程,请参考:[PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR/tree/dygraph) + + +- 飞桨框架相关资料,请参考:[飞桨深度学习平台](https://www.paddlepaddle.org.cn/?fr=paddleEdu_aistudio) + +# 参考 + +* 数据生成代码库:https://github.com/zcswdt/Color_OCR_image_generator diff --git "a/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/background/bg.jpg" "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/background/bg.jpg" new file mode 100644 index 0000000000000000000000000000000000000000..3cb6eab819c3b7d4f68590d2cdc9d36351590197 Binary files /dev/null and "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/background/bg.jpg" differ diff --git "a/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/corpus/text.txt" "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/corpus/text.txt" new file mode 100644 index 0000000000000000000000000000000000000000..8b8cb793ef6755bf00ed8c154e24638b07a519c2 --- /dev/null +++ "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/corpus/text.txt" @@ -0,0 +1,30 @@ +5ZQ +I4UL +PWL +SNOG +ZL02 +1C30 +O3H +YHRS +N03S +1U5Y +JTK +EN4F +YKJ +DWNH +R42W +X0V +4OF5 +08AM +Y93S +GWE2 +0KR +9U2A +DBQ +Y6J +ROZ +K06 +KIEY +NZQJ +UN1B +6X4 \ No newline at end of file diff --git "a/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/det_background/1.png" "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/det_background/1.png" new file mode 100644 index 0000000000000000000000000000000000000000..8a49eaa6862113044e05d17e32941a0a20911426 Binary files /dev/null and "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/det_background/1.png" differ diff --git "a/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/det_background/2.png" "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/det_background/2.png" new file mode 100644 index 0000000000000000000000000000000000000000..c3fcc0c92826b97b5f6abd970f1a0580eede0f5d Binary files /dev/null and "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/det_background/2.png" differ diff --git "a/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/gen.py" "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/gen.py" new file mode 100644 index 0000000000000000000000000000000000000000..4c768067f998b6b4bbe0b2f5982f46a3f01fc872 --- /dev/null +++ "b/applications/PCB\345\255\227\347\254\246\350\257\206\345\210\253/gen_data/gen.py" @@ -0,0 +1,261 @@ +# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +This code is refer from: +https://github.com/zcswdt/Color_OCR_image_generator +""" +import os +import random +from PIL import Image, ImageDraw, ImageFont +import json +import argparse + + +def get_char_lines(txt_root_path): + """ + desc:get corpus line + """ + txt_files = os.listdir(txt_root_path) + char_lines = [] + for txt in txt_files: + f = open(os.path.join(txt_root_path, txt), mode='r', encoding='utf-8') + lines = f.readlines() + f.close() + for line in lines: + char_lines.append(line.strip()) + return char_lines + + +def get_horizontal_text_picture(image_file, chars, fonts_list, cf): + """ + desc:gen horizontal text picture + """ + img = Image.open(image_file) + if img.mode != 'RGB': + img = img.convert('RGB') + img_w, img_h = img.size + + # random choice font + font_path = random.choice(fonts_list) + # random choice font size + font_size = random.randint(cf.font_min_size, cf.font_max_size) + font = ImageFont.truetype(font_path, font_size) + + ch_w = [] + ch_h = [] + for ch in chars: + wt, ht = font.getsize(ch) + ch_w.append(wt) + ch_h.append(ht) + f_w = sum(ch_w) + f_h = max(ch_h) + + # add space + char_space_width = max(ch_w) + f_w += (char_space_width * (len(chars) - 1)) + + x1 = random.randint(0, img_w - f_w) + y1 = random.randint(0, img_h - f_h) + x2 = x1 + f_w + y2 = y1 + f_h + + crop_y1 = y1 + crop_x1 = x1 + crop_y2 = y2 + crop_x2 = x2 + + best_color = (0, 0, 0) + draw = ImageDraw.Draw(img) + for i, ch in enumerate(chars): + draw.text((x1, y1), ch, best_color, font=font) + x1 += (ch_w[i] + char_space_width) + crop_img = img.crop((crop_x1, crop_y1, crop_x2, crop_y2)) + return crop_img, chars + + +def get_vertical_text_picture(image_file, chars, fonts_list, cf): + """ + desc:gen vertical text picture + """ + img = Image.open(image_file) + if img.mode != 'RGB': + img = img.convert('RGB') + img_w, img_h = img.size + # random choice font + font_path = random.choice(fonts_list) + # random choice font size + font_size = random.randint(cf.font_min_size, cf.font_max_size) + font = ImageFont.truetype(font_path, font_size) + + ch_w = [] + ch_h = [] + for ch in chars: + wt, ht = font.getsize(ch) + ch_w.append(wt) + ch_h.append(ht) + f_w = max(ch_w) + f_h = sum(ch_h) + + x1 = random.randint(0, img_w - f_w) + y1 = random.randint(0, img_h - f_h) + x2 = x1 + f_w + y2 = y1 + f_h + + crop_y1 = y1 + crop_x1 = x1 + crop_y2 = y2 + crop_x2 = x2 + + best_color = (0, 0, 0) + draw = ImageDraw.Draw(img) + i = 0 + for ch in chars: + draw.text((x1, y1), ch, best_color, font=font) + y1 = y1 + ch_h[i] + i = i + 1 + crop_img = img.crop((crop_x1, crop_y1, crop_x2, crop_y2)) + crop_img = crop_img.transpose(Image.ROTATE_90) + return crop_img, chars + + +def get_fonts(fonts_path): + """ + desc: get all fonts + """ + font_files = os.listdir(fonts_path) + fonts_list=[] + for font_file in font_files: + font_path=os.path.join(fonts_path, font_file) + fonts_list.append(font_path) + return fonts_list + +if __name__ == '__main__': + parser = argparse.ArgumentParser() + parser.add_argument('--num_img', type=int, default=30, help="Number of images to generate") + parser.add_argument('--font_min_size', type=int, default=11) + parser.add_argument('--font_max_size', type=int, default=12, + help="Help adjust the size of the generated text and the size of the picture") + parser.add_argument('--bg_path', type=str, default='./background', + help='The generated text pictures will be pasted onto the pictures of this folder') + parser.add_argument('--det_bg_path', type=str, default='./det_background', + help='The generated text pictures will use the pictures of this folder as the background') + parser.add_argument('--fonts_path', type=str, default='../../StyleText/fonts', + help='The font used to generate the picture') + parser.add_argument('--corpus_path', type=str, default='./corpus', + help='The corpus used to generate the text picture') + parser.add_argument('--output_dir', type=str, default='./output/', help='Images save dir') + + + cf = parser.parse_args() + # save path + if not os.path.exists(cf.output_dir): + os.mkdir(cf.output_dir) + + # get corpus + txt_root_path = cf.corpus_path + char_lines = get_char_lines(txt_root_path=txt_root_path) + + # get all fonts + fonts_path = cf.fonts_path + fonts_list = get_fonts(fonts_path) + + # rec bg + img_root_path = cf.bg_path + imnames=os.listdir(img_root_path) + + # det bg + det_bg_path = cf.det_bg_path + bg_pics = os.listdir(det_bg_path) + + # OCR det files + det_val_file = open(cf.output_dir + 'det_gt_val.txt', 'w', encoding='utf-8') + det_train_file = open(cf.output_dir + 'det_gt_train.txt', 'w', encoding='utf-8') + # det imgs + det_save_dir = 'imgs/' + if not os.path.exists(cf.output_dir + det_save_dir): + os.mkdir(cf.output_dir + det_save_dir) + det_val_save_dir = 'imgs_val/' + if not os.path.exists(cf.output_dir + det_val_save_dir): + os.mkdir(cf.output_dir + det_val_save_dir) + + # OCR rec files + rec_val_file = open(cf.output_dir + 'rec_gt_val.txt', 'w', encoding='utf-8') + rec_train_file = open(cf.output_dir + 'rec_gt_train.txt', 'w', encoding='utf-8') + # rec imgs + rec_save_dir = 'rec_imgs/' + if not os.path.exists(cf.output_dir + rec_save_dir): + os.mkdir(cf.output_dir + rec_save_dir) + rec_val_save_dir = 'rec_imgs_val/' + if not os.path.exists(cf.output_dir + rec_val_save_dir): + os.mkdir(cf.output_dir + rec_val_save_dir) + + + val_ratio = cf.num_img * 0.2 # val dataset ratio + + print('start generating...') + for i in range(0, cf.num_img): + imname = random.choice(imnames) + img_path = os.path.join(img_root_path, imname) + + rnd = random.random() + # gen horizontal text picture + if rnd < 0.5: + gen_img, chars = get_horizontal_text_picture(img_path, char_lines[i], fonts_list, cf) + ori_w, ori_h = gen_img.size + gen_img = gen_img.crop((0, 3, ori_w, ori_h)) + # gen vertical text picture + else: + gen_img, chars = get_vertical_text_picture(img_path, char_lines[i], fonts_list, cf) + ori_w, ori_h = gen_img.size + gen_img = gen_img.crop((3, 0, ori_w, ori_h)) + + ori_w, ori_h = gen_img.size + + # rec imgs + save_img_name = str(i).zfill(4) + '.jpg' + if i < val_ratio: + save_dir = os.path.join(rec_val_save_dir, save_img_name) + line = save_dir + '\t' + char_lines[i] + '\n' + rec_val_file.write(line) + else: + save_dir = os.path.join(rec_save_dir, save_img_name) + line = save_dir + '\t' + char_lines[i] + '\n' + rec_train_file.write(line) + gen_img.save(cf.output_dir + save_dir, quality = 95, subsampling=0) + + # det img + # random choice bg + bg_pic = random.sample(bg_pics, 1)[0] + det_img = Image.open(os.path.join(det_bg_path, bg_pic)) + # the PCB position is fixed, modify it according to your own scenario + if bg_pic == '1.png': + x1 = 38 + y1 = 3 + else: + x1 = 34 + y1 = 1 + + det_img.paste(gen_img, (x1, y1)) + # text pos + chars_pos = [[x1, y1], [x1 + ori_w, y1], [x1 + ori_w, y1 + ori_h], [x1, y1 + ori_h]] + label = [{"transcription":char_lines[i], "points":chars_pos}] + if i < val_ratio: + save_dir = os.path.join(det_val_save_dir, save_img_name) + det_val_file.write(save_dir + '\t' + json.dumps( + label, ensure_ascii=False) + '\n') + else: + save_dir = os.path.join(det_save_dir, save_img_name) + det_train_file.write(save_dir + '\t' + json.dumps( + label, ensure_ascii=False) + '\n') + det_img.save(cf.output_dir + save_dir, quality = 95, subsampling=0) diff --git "a/applications/\350\275\246\347\211\214\350\257\206\345\210\253.md" "b/applications/\350\275\246\347\211\214\350\257\206\345\210\253.md" deleted file mode 100644 index 7510f3c5a86b84ba2a384521102ca8c338aaec36..0000000000000000000000000000000000000000 --- "a/applications/\350\275\246\347\211\214\350\257\206\345\210\253.md" +++ /dev/null @@ -1,646 +0,0 @@ -# 一种基于PaddleOCR的轻量级车牌识别模型 - -- [1. 项目介绍](#1-项目介绍) -- [2. 环境搭建](#2-环境搭建) -- [3. 数据集准备](#3-数据集准备) - - [3.1 数据集标注规则](#31-数据集标注规则) - - [3.2 制作符合PP-OCR训练格式的标注文件](#32-制作符合pp-ocr训练格式的标注文件) -- [4. 实验](#4-实验) - - [4.1 检测](#41-检测) - - [4.1.1 预训练模型直接预测](#411-预训练模型直接预测) - - [4.1.2 CCPD车牌数据集fine-tune](#412-ccpd车牌数据集fine-tune) - - [4.1.3 CCPD车牌数据集fine-tune+量化训练](#413-ccpd车牌数据集fine-tune量化训练) - - [4.1.4 模型导出](#414-模型导出) - - [4.2 识别](#42-识别) - - [4.2.1 预训练模型直接预测](#421-预训练模型直接预测) - - [4.2.2 预训练模型直接预测+改动后处理](#422-预训练模型直接预测改动后处理) - - [4.2.3 CCPD车牌数据集fine-tune](#423-ccpd车牌数据集fine-tune) - - [4.2.4 CCPD车牌数据集fine-tune+量化训练](#424-ccpd车牌数据集fine-tune量化训练) - - [4.2.5 模型导出](#425-模型导出) - - [4.3 串联推理](#43-串联推理) - - [4.4 实验总结](#44-实验总结) - -## 1. 项目介绍 - -车牌识别(Vehicle License Plate Recognition,VLPR) 是计算机视频图像识别技术在车辆牌照识别中的一种应用。车牌识别技术要求能够将运动中的汽车牌照从复杂背景中提取并识别出来,在高速公路车辆管理,停车场管理和中得到广泛应用。 - -结合我国国情,目前车牌识别技术的难点有: - -1. 车牌样式多。我国车牌颜色大致有四种:黄底黑字、蓝底白字、白底黑字、黑底白字;车牌格式包括民用车牌、武警车牌、军车车牌、外交车牌、特种车牌、消防车牌等等。 -2. 车牌位置不固定。由于不同汽车品牌公司出产的汽车型号和外形各有不同,每辆车的车牌悬挂位置也不一样; -3. 图像质量差: 运动模糊,由于强光,反射或阴影造成的光照和对比度较差, 车牌(部分)遮挡; -4. 在车辆管理等场景场景对于模型速度有着一定限制。 - -针对以上问题, 本例选用 [PP-OCRv3](../doc/doc_ch/PP-OCRv3_introduction.md) 这一开源超轻量OCR系统进行车牌识别系统的开发。基于PP-OCRv3模型,在CCPD数据集达到99%的检测和94%的识别精度,模型大小12.8M(2.5M+10.3M)。基于量化对模型体积进行进一步压缩到5.8M(1M+4.8M), 同时推理速度提升x%。 - -aistudio项目链接: [基于PaddleOCR的轻量级车牌识别范例](https://aistudio.baidu.com/aistudio/projectdetail/3919091?contributionType=1) - -## 2. 环境搭建 - -本任务基于Aistudio完成, 具体环境如下: - -- 操作系统: Linux -- PaddlePaddle: 2.3 -- paddleslim: 2.2.2 -- PaddleOCR: Release/2.5 - -下载 PaddleOCR代码 - -```bash -git clone -b dygraph https://github.com/PaddlePaddle/PaddleOCR -``` - -安装依赖库 - -```bash -pip install -r PaddleOCR/requirements.txt -``` - -## 3. 数据集准备 - -所使用的数据集为 CCPD2020 新能源车牌数据集,该数据集为 - -该数据集分布如下: - -|数据集类型|数量| -|---|---| -|训练集| 5769| -|验证集| 1001| -|测试集| 5006| - -数据集图片示例如下: -![](https://ai-studio-static-online.cdn.bcebos.com/3bce057a8e0c40a0acbd26b2e29e4e2590a31bc412764be7b9e49799c69cb91c) - -数据集可以从这里下载 https://aistudio.baidu.com/aistudio/datasetdetail/101595 - -下载好数据集后对数据集进行解压 - -```bash -unzip -d /home/aistudio/data /home/aistudio/data/data101595/CCPD2020.zip -``` - -### 3.1 数据集标注规则 - -CPPD数据集的图片文件名具有特殊规则,详细可查看:https://github.com/detectRecog/CCPD - -具体规则如下: - -例如: 025-95_113-154&383_386&473-386&473_177&454_154&383_363&402-0_0_22_27_27_33_16-37-15.jpg - -由分隔符'-'分为几个部分: - -- 025:车牌区域与整个图片区域的面积比。 - -- 95_113: 车牌水平倾斜度和垂直倾斜度, 水平95°, 竖直113° - -- 154&383_386&473: 车牌边界框坐标:左上(154, 383), 右下(386, 473) - -- 386&473_177&454_154&383_363&402: 车牌四个角点坐标, 坐标顺序为[右下,左下,左上,右上] - -- 0_0_22_27_27_33_16: 车牌号码,CCPD中的每个图像只有一个LP。每个LP编号由一个汉字、一个字母和五个字母或数字组成。有效的中国车牌由七个字符组成:省(1个字符)、字母(1个字符)、字母+数字(5个字符)。“0_0_22_27_27_33_16”是每个字符的索引。这三个数组的定义如下。每个数组的最后一个字符是字母O,而不是数字0。我们使用O作为“无字符”的标志,因为中国车牌字符中没有O。 - -```python -provinces = ["皖", "沪", "津", "渝", "冀", "晋", "蒙", "辽", "吉", "黑", "苏", "浙", "京", "闽", "赣", "鲁", "豫", "鄂", "湘", "粤", "桂", "琼", "川", "贵", "云", "藏", "陕", "甘", "青", "宁", "新", "警", "学", "O"] -alphabets = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', - 'X', 'Y', 'Z', 'O'] -ads = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', - 'Y', 'Z', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'O'] - -``` - -### 3.2 制作符合PP-OCR训练格式的标注文件 - -在开始训练之前,可使用如下代码制作符合PP-OCR训练格式的标注文件。 - - -```python -import cv2 -import os -import json -from tqdm import tqdm -import numpy as np - -provinces = ["皖", "沪", "津", "渝", "冀", "晋", "蒙", "辽", "吉", "黑", "苏", "浙", "京", "闽", "赣", "鲁", "豫", "鄂", "湘", "粤", "桂", "琼", "川", "贵", "云", "藏", "陕", "甘", "青", "宁", "新", "警", "学", "O"] -alphabets = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', 'O'] -ads = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'O'] - -def make_label(img_dir, save_gt_folder, phase): - crop_img_save_dir = os.path.join(save_gt_folder, phase, 'crop_imgs') - os.makedirs(crop_img_save_dir, exist_ok=True) - - f_det = open(os.path.join(save_gt_folder, phase, 'det.txt'), 'w', encoding='utf-8') - f_rec = open(os.path.join(save_gt_folder, phase, 'rec.txt'), 'w', encoding='utf-8') - - i = 0 - for filename in tqdm(os.listdir(os.path.join(img_dir, phase))): - str_list = filename.split('-') - if len(str_list) < 5: - continue - coord_list = str_list[3].split('_') - txt_list = str_list[4].split('_') - boxes = [] - for coord in coord_list: - boxes.append([int(x) for x in coord.split("&")]) - boxes = [boxes[2], boxes[3], boxes[0], boxes[1]] - lp_number = provinces[int(txt_list[0])] + alphabets[int(txt_list[1])] + ''.join([ads[int(x)] for x in txt_list[2:]]) - - # det - det_info = [{'points':boxes, 'transcription':lp_number}] - f_det.write('{}\t{}\n'.format(os.path.join(phase, filename), json.dumps(det_info, ensure_ascii=False))) - - # rec - boxes = np.float32(boxes) - img = cv2.imread(os.path.join(img_dir, phase, filename)) - # crop_img = img[int(boxes[:,1].min()):int(boxes[:,1].max()),int(boxes[:,0].min()):int(boxes[:,0].max())] - crop_img = get_rotate_crop_image(img, boxes) - crop_img_save_filename = '{}_{}.jpg'.format(i,'_'.join(txt_list)) - crop_img_save_path = os.path.join(crop_img_save_dir, crop_img_save_filename) - cv2.imwrite(crop_img_save_path, crop_img) - f_rec.write('{}/crop_imgs/{}\t{}\n'.format(phase, crop_img_save_filename, lp_number)) - i+=1 - f_det.close() - f_rec.close() - -def get_rotate_crop_image(img, points): - ''' - img_height, img_width = img.shape[0:2] - left = int(np.min(points[:, 0])) - right = int(np.max(points[:, 0])) - top = int(np.min(points[:, 1])) - bottom = int(np.max(points[:, 1])) - img_crop = img[top:bottom, left:right, :].copy() - points[:, 0] = points[:, 0] - left - points[:, 1] = points[:, 1] - top - ''' - assert len(points) == 4, "shape of points must be 4*2" - img_crop_width = int( - max( - np.linalg.norm(points[0] - points[1]), - np.linalg.norm(points[2] - points[3]))) - img_crop_height = int( - max( - np.linalg.norm(points[0] - points[3]), - np.linalg.norm(points[1] - points[2]))) - pts_std = np.float32([[0, 0], [img_crop_width, 0], - [img_crop_width, img_crop_height], - [0, img_crop_height]]) - M = cv2.getPerspectiveTransform(points, pts_std) - dst_img = cv2.warpPerspective( - img, - M, (img_crop_width, img_crop_height), - borderMode=cv2.BORDER_REPLICATE, - flags=cv2.INTER_CUBIC) - dst_img_height, dst_img_width = dst_img.shape[0:2] - if dst_img_height * 1.0 / dst_img_width >= 1.5: - dst_img = np.rot90(dst_img) - return dst_img - -img_dir = '/home/aistudio/data/CCPD2020/ccpd_green' -save_gt_folder = '/home/aistudio/data/CCPD2020/PPOCR' -# phase = 'train' # change to val and test to make val dataset and test dataset -for phase in ['train','val','test']: - make_label(img_dir, save_gt_folder, phase) -``` - -通过上述命令可以完成了`训练集`,`验证集`和`测试集`的制作,制作完成的数据集信息如下: - -| 类型 | 数据集 | 图片地址 | 标签地址 | 图片数量 | -| --- | --- | --- | --- | --- | -| 检测 | 训练集 | /home/aistudio/data/CCPD2020/ccpd_green/train | /home/aistudio/data/CCPD2020/PPOCR/train/det.txt | 5769 | -| 检测 | 验证集 | /home/aistudio/data/CCPD2020/ccpd_green/val | /home/aistudio/data/CCPD2020/PPOCR/val/det.txt | 1001 | -| 检测 | 测试集 | /home/aistudio/data/CCPD2020/ccpd_green/test | /home/aistudio/data/CCPD2020/PPOCR/test/det.txt | 5006 | -| 识别 | 训练集 | /home/aistudio/data/CCPD2020/PPOCR/train/crop_imgs | /home/aistudio/data/CCPD2020/PPOCR/train/rec.txt | 5769 | -| 识别 | 验证集 | /home/aistudio/data/CCPD2020/PPOCR/val/crop_imgs | /home/aistudio/data/CCPD2020/PPOCR/val/rec.txt | 1001 | -| 识别 | 测试集 | /home/aistudio/data/CCPD2020/PPOCR/test/crop_imgs | /home/aistudio/data/CCPD2020/PPOCR/test/rec.txt | 5006 | - -在普遍的深度学习流程中,都是在训练集训练,在验证集选择最优模型后在测试集上进行测试。在本例中,我们省略中间步骤,直接在训练集训练,在测试集选择最优模型,因此我们只使用训练集和测试集。 - -## 4. 实验 - -由于数据集比较少,为了模型更好和更快的收敛,这里选用 PaddleOCR 中的 PP-OCRv3 模型进行文本检测和识别,并且使用 PP-OCRv3 模型参数作为预训练模型。PP-OCRv3在PP-OCRv2的基础上,中文场景端到端Hmean指标相比于PP-OCRv2提升5%, 英文数字模型端到端效果提升11%。详细优化细节请参考[PP-OCRv3](../doc/doc_ch/PP-OCRv3_introduction.md)技术报告。 - -由于车牌场景均为端侧设备部署,因此对速度和模型大小有比较高的要求,因此还需要采用量化训练的方式进行模型大小的压缩和模型推理速度的加速。模型量化可以在基本不损失模型的精度的情况下,将FP32精度的模型参数转换为Int8精度,减小模型参数大小并加速计算,使用量化后的模型在移动端等部署时更具备速度优势。 - -因此,本实验中对于车牌检测和识别有如下3种方案: - -1. PP-OCRv3中英文超轻量预训练模型直接预测 -2. CCPD车牌数据集在PP-OCRv3模型上fine-tune -3. CCPD车牌数据集在PP-OCRv3模型上fine-tune后量化 - -### 4.1 检测 -#### 4.1.1 预训练模型直接预测 - -从下表中下载PP-OCRv3文本检测预训练模型 - -|模型名称|模型简介|配置文件|推理模型大小|下载地址| -| --- | --- | --- | --- | --- | -|ch_PP-OCRv3_det| 【最新】原始超轻量模型,支持中英文、多语种文本检测 |[ch_PP-OCRv3_det_cml.yml](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml)| 3.8M |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar)| - -使用如下命令下载预训练模型 - -```bash -mkdir models -cd models -wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar -tar -xf ch_PP-OCRv3_det_distill_train.tar -cd /home/aistudio/PaddleOCR -``` - -预训练模型下载完成后,我们使用[ch_PP-OCRv3_det_student.yml](../configs/chepai/ch_PP-OCRv3_det_student.yml) 配置文件进行后续实验,在开始评估之前需要对配置文件中部分字段进行设置,具体如下: - -1. 模型存储和训练相关: - 1. Global.pretrained_model: 指向PP-OCRv3文本检测预训练模型地址 -2. 数据集相关 - 1. Eval.dataset.data_dir:指向测试集图片存放目录 - 2. Eval.dataset.label_file_list:指向测试集标注文件 - -上述字段均为必须修改的字段,可以通过修改配置文件的方式改动,也可在不需要修改配置文件的情况下,改变训练的参数。这里使用不改变配置文件的方式 。使用如下命令进行PP-OCRv3文本检测预训练模型的评估 - - -```bash -python tools/eval.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \ - Global.pretrained_model=models/ch_PP-OCRv3_det_distill_train/student.pdparams \ - Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \ - Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt] -``` -上述指令中,通过-c 选择训练使用配置文件,通过-o参数在不需要修改配置文件的情况下,改变训练的参数。 - -使用预训练模型进行评估,指标如下所示: - -| 方案 |hmeans| -|---------------------------|---| -| PP-OCRv3中英文超轻量检测预训练模型直接预测 |76.12%| - -#### 4.1.2 CCPD车牌数据集fine-tune - -**训练** - -为了进行fine-tune训练,我们需要在配置文件中设置需要使用的预训练模型地址,学习率和数据集等参数。 具体如下: - -1. 模型存储和训练相关: - 1. Global.pretrained_model: 指向PP-OCRv3文本检测预训练模型地址 - 2. Global.eval_batch_step: 模型多少step评估一次,这里设为从第0个step开始没隔772个step评估一次,772为一个epoch总的step数。 -2. 优化器相关: - 1. Optimizer.lr.name: 学习率衰减器设为常量 Const - 2. Optimizer.lr.learning_rate: 做finetune实验,学习率需要设置的比较小,此处学习率设为配置文件中的0.05倍 - 3. Optimizer.lr.warmup_epoch: warmup_epoch设为0 -3. 数据集相关: - 1. Train.dataset.data_dir:指向训练集图片存放目录 - 2. Train.dataset.label_file_list:指向训练集标注文件 - 3. Eval.dataset.data_dir:指向测试集图片存放目录 - 4. Eval.dataset.label_file_list:指向测试集标注文件 - -使用如下代码即可启动在CCPD车牌数据集上的fine-tune。 - -```bash -python tools/train.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \ - Global.pretrained_model=models/ch_PP-OCRv3_det_distill_train/student.pdparams \ - Global.save_model_dir=output/CCPD/det \ - Global.eval_batch_step="[0, 772]" \ - Optimizer.lr.name=Const \ - Optimizer.lr.learning_rate=0.0005 \ - Optimizer.lr.warmup_epoch=0 \ - Train.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \ - Train.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/train/det.txt] \ - Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \ - Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt] -``` - -在上述命令中,通过`-o`的方式修改了配置文件中的参数。 - -训练好的模型地址为: [det_ppocr_v3_finetune.tar](https://paddleocr.bj.bcebos.com/fanliku/license_plate_recognition/det_ppocr_v3_finetune.tar) - -**评估** - -训练完成后使用如下命令进行评估 - - -```bash -python tools/eval.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \ - Global.pretrained_model=output/CCPD/det/best_accuracy.pdparams \ - Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \ - Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt] -``` - -使用预训练模型和CCPD车牌数据集fine-tune,指标分别如下: - -|方案|hmeans| -|---|---| -|PP-OCRv3中英文超轻量检测预训练模型直接预测|76.12%| -|PP-OCRv3中英文超轻量检测预训练模型 fine-tune|99%| - -可以看到进行fine-tune能显著提升车牌检测的效果。 - -#### 4.1.3 CCPD车牌数据集fine-tune+量化训练 - -此处采用 PaddleOCR 中提供好的[量化教程](../deploy/slim/quantization/README.md)对模型进行量化训练。 - -量化训练可通过如下命令启动: - -```bash -python3.7 deploy/slim/quantization/quant.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \ - Global.pretrained_model=output/CCPD/det/best_accuracy.pdparams \ - Global.save_model_dir=output/CCPD/det_quant \ - Global.eval_batch_step="[0, 772]" \ - Optimizer.lr.name=Const \ - Optimizer.lr.learning_rate=0.0005 \ - Optimizer.lr.warmup_epoch=0 \ - Train.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \ - Train.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/train/det.txt] \ - Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \ - Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt] -``` - -训练好的模型地址为: [det_ppocr_v3_quant.tar](https://paddleocr.bj.bcebos.com/fanliku/license_plate_recognition/det_ppocr_v3_quant.tar) - -量化后指标对比如下 - -|方案|hmeans| 模型大小 |预测速度(lite)| -|---|---|------|---| -|PP-OCRv3中英文超轻量检测预训练模型 fine-tune|99%| 2.5M | 223ms/image | -|PP-OCRv3中英文超轻量检测预训练模型 fine-tune+量化|98.91%| 1M | 189ms/image | - -可以看到量化后能显著降低模型体积并且精度几乎无损。 - -预测速度是在android骁龙855上预测275张图像的平均耗时。模型在移动端的部署步骤参考[文档](../deploy/lite/readme_ch.md) - -#### 4.1.4 模型导出 - -使用如下命令可以将训练好的模型进行导出 - -* 非量化模型 -```bash -python tools/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \ - Global.pretrained_model=output/CCPD/det/best_accuracy.pdparams \ - Global.save_inference_dir=output/det/infer -``` -* 量化模型 -```bash -python deploy/slim/quantization/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \ - Global.pretrained_model=output/CCPD/det_quant/best_accuracy.pdparams \ - Global.save_inference_dir=output/det/infer -``` - -### 4.2 识别 -#### 4.2.1 预训练模型直接预测 - -从下表中下载PP-OCRv3文本识别预训练模型 - -|模型名称|模型简介|配置文件|推理模型大小|下载地址| -| --- | --- | --- | --- | --- | -|ch_PP-OCRv3_rec|【最新】原始超轻量模型,支持中英文、数字识别|[ch_PP-OCRv3_rec_distillation.yml](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml)| 12.4M |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) | - -使用如下命令下载预训练模型 - -```bash -mkdir models -cd models -wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar -tar -xf ch_PP-OCRv3_rec_train.tar -cd /home/aistudio/PaddleOCR -``` - -PaddleOCR提供的PP-OCRv3识别模型采用蒸馏训练策略,因此提供的预训练模型中会包含`Teacher`和`Student`模型的参数,详细信息可参考[knowledge_distillation.md](../doc/doc_ch/knowledge_distillation.md)。 因此,模型下载完成后需要使用如下代码提取`Student`模型的参数: - -```python -import paddle -# 加载预训练模型 -all_params = paddle.load("models/ch_PP-OCRv3_rec_train/best_accuracy.pdparams") -# 查看权重参数的keys -print(all_params.keys()) -# 学生模型的权重提取 -s_params = {key[len("Student."):]: all_params[key] for key in all_params if "Student." in key} -# 查看学生模型权重参数的keys -print(s_params.keys()) -# 保存 -paddle.save(s_params, "models/ch_PP-OCRv3_rec_train/student.pdparams") -``` - -预训练模型下载完成后,我们使用[ch_PP-OCRv3_rec.yml](../configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml) 配置文件进行后续实验,在开始评估之前需要对配置文件中部分字段进行设置,具体如下: - -1. 模型存储和训练相关: - 1. Global.pretrained_model: 指向PP-OCRv3文本识别预训练模型地址 -2. 数据集相关 - 1. Eval.dataset.data_dir:指向测试集图片存放目录 - 2. Eval.dataset.label_file_list:指向测试集标注文件 - -使用如下命令进行PP-OCRv3文本识别预训练模型的评估 - -```bash -python tools/eval.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \ - Global.pretrained_model=models/ch_PP-OCRv3_rec_train/student.pdparams \ - Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \ - Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt] -``` - -评估部分日志如下: -```bash -[2022/05/12 19:52:02] ppocr INFO: load pretrain successful from models/ch_PP-OCRv3_rec_train/best_accuracy -eval model:: 100%|██████████████████████████████| 40/40 [00:15<00:00, 2.57it/s] -[2022/05/12 19:52:17] ppocr INFO: metric eval *************** -[2022/05/12 19:52:17] ppocr INFO: acc:0.0 -[2022/05/12 19:52:17] ppocr INFO: norm_edit_dis:0.8656084923002452 -[2022/05/12 19:52:17] ppocr INFO: Teacher_acc:0.000399520574511545 -[2022/05/12 19:52:17] ppocr INFO: Teacher_norm_edit_dis:0.8657902943394548 -[2022/05/12 19:52:17] ppocr INFO: fps:1443.1801978719905 - -``` -使用预训练模型进行评估,指标如下所示: - -|方案|acc| -|---|---| -|PP-OCRv3中英文超轻量识别预训练模型直接预测|0%| - -从评估日志中可以看到,直接使用PP-OCRv3预训练模型进行评估,acc非常低,但是norm_edit_dis很高。因此,我们猜测是模型大部分文字识别是对的,只有少部分文字识别错误。使用如下命令进行infer查看模型的推理结果进行验证: - - -```bash -python tools/infer_rec.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \ - Global.pretrained_model=models/ch_PP-OCRv3_rec_train/student.pdparams \ - Global.infer_img=/home/aistudio/data/CCPD2020/PPOCR/test/crop_imgs/0_0_0_3_32_30_31_30_30.jpg -``` - -输出部分日志如下: -```bash -[2022/05/01 08:51:57] ppocr INFO: train with paddle 2.2.2 and device CUDAPlace(0) -W0501 08:51:57.127391 11326 device_context.cc:447] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 11.0, Runtime API Version: 10.1 -W0501 08:51:57.132315 11326 device_context.cc:465] device: 0, cuDNN Version: 7.6. -[2022/05/01 08:52:00] ppocr INFO: load pretrain successful from models/ch_PP-OCRv3_rec_train/student -[2022/05/01 08:52:00] ppocr INFO: infer_img: /home/aistudio/data/CCPD2020/PPOCR/test/crop_imgs/0_0_3_32_30_31_30_30.jpg -[2022/05/01 08:52:00] ppocr INFO: result: {"Student": {"label": "皖A·D86766", "score": 0.9552637934684753}, "Teacher": {"label": "皖A·D86766", "score": 0.9917094707489014}} -[2022/05/01 08:52:00] ppocr INFO: success! -``` - -从infer结果可以看到,车牌中的文字大部分都识别正确,只是多识别出了一个`·`。针对这种情况,有如下两种方案: -1. 直接通过后处理去掉多识别的`·`。 -2. 进行finetune。 - -#### 4.2.2 预训练模型直接预测+改动后处理 - -直接通过后处理去掉多识别的`·`,在后处理的改动比较简单,只需在 [ppocr/postprocess/rec_postprocess.py](../ppocr/postprocess/rec_postprocess.py) 文件的76行添加如下代码: -```python -text = text.replace('·','') -``` - -改动前后指标对比: - -|方案|acc| -|---|---| -|PP-OCRv3中英文超轻量识别预训练模型直接预测|0.2%| -|PP-OCRv3中英文超轻量识别预训练模型直接预测+后处理去掉多识别的`·`|90.97%| - -可以看到,去掉多余的`·`能大幅提高精度。 - -#### 4.2.3 CCPD车牌数据集fine-tune - -**训练** - -为了进行fine-tune训练,我们需要在配置文件中设置需要使用的预训练模型地址,学习率和数据集等参数。 具体如下: - -1. 模型存储和训练相关: - 1. Global.pretrained_model: 指向PP-OCRv3文本识别预训练模型地址 - 2. Global.eval_batch_step: 模型多少step评估一次,这里设为从第0个step开始没隔45个step评估一次,45为一个epoch总的step数。 -2. 优化器相关 - 1. Optimizer.lr.name: 学习率衰减器设为常量 Const - 2. Optimizer.lr.learning_rate: 做finetune实验,学习率需要设置的比较小,此处学习率设为配置文件中的0.05倍 - 3. Optimizer.lr.warmup_epoch: warmup_epoch设为0 -3. 数据集相关 - 1. Train.dataset.data_dir:指向训练集图片存放目录 - 2. Train.dataset.label_file_list:指向训练集标注文件 - 3. Eval.dataset.data_dir:指向测试集图片存放目录 - 4. Eval.dataset.label_file_list:指向测试集标注文件 - -使用如下命令启动finetune - -```bash -python tools/train.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \ - Global.pretrained_model=models/ch_PP-OCRv3_rec_train/student.pdparams \ - Global.save_model_dir=output/CCPD/rec/ \ - Global.eval_batch_step="[0, 90]" \ - Optimizer.lr.name=Const \ - Optimizer.lr.learning_rate=0.0005 \ - Optimizer.lr.warmup_epoch=0 \ - Train.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \ - Train.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/train/rec.txt] \ - Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \ - Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt] -``` -训练好的模型地址为: [rec_ppocr_v3_finetune.tar](https://paddleocr.bj.bcebos.com/fanliku/license_plate_recognition/rec_ppocr_v3_finetune.tar) - -**评估** - -训练完成后使用如下命令进行评估 - -```bash -python tools/eval.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \ - Global.pretrained_model=output/CCPD/rec/best_accuracy.pdparams \ - Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \ - Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt] -``` - -使用预训练模型和CCPD车牌数据集fine-tune,指标分别如下: - -|方案| acc | -|---|--------| -|PP-OCRv3中英文超轻量识别预训练模型直接预测| 0% | -|PP-OCRv3中英文超轻量识别预训练模型直接预测+后处理去掉多识别的`·`| 90.97% | -|PP-OCRv3中英文超轻量识别预训练模型 fine-tune| 94.54% | - -可以看到进行fine-tune能显著提升车牌识别的效果。 - -#### 4.2.4 CCPD车牌数据集fine-tune+量化训练 - -此处采用 PaddleOCR 中提供好的[量化教程](../deploy/slim/quantization/README.md)对模型进行量化训练。 - -量化训练可通过如下命令启动: - -```bash -python3.7 deploy/slim/quantization/quant.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \ - Global.pretrained_model=output/CCPD/rec/best_accuracy.pdparams \ - Global.save_model_dir=output/CCPD/rec_quant/ \ - Global.eval_batch_step="[0, 90]" \ - Optimizer.lr.name=Const \ - Optimizer.lr.learning_rate=0.0005 \ - Optimizer.lr.warmup_epoch=0 \ - Train.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \ - Train.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/train/rec.txt] \ - Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \ - Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt] -``` -训练好的模型地址为: [rec_ppocr_v3_quant.tar](https://paddleocr.bj.bcebos.com/fanliku/license_plate_recognition/rec_ppocr_v3_quant.tar) - -量化后指标对比如下 - -|方案| acc | 模型大小 |预测速度(lite)| -|---|--------|-------|---| -|PP-OCRv3中英文超轻量识别预训练模型 fine-tune| 94.54% | 10.3M | 4.2ms/image | -|PP-OCRv3中英文超轻量识别预训练模型 fine-tune + 量化| 93.4% | 4.8M | 1.8ms/image; | - -可以看到量化后能显著降低模型体积,但是由于识别数据过少,量化带来了1%的精度下降。 - -预测速度是在android骁龙855上预测5006张识别文字图像的平均耗时。模型在移动端的部署步骤参考[文档](../deploy/lite/readme_ch.md) - -#### 4.2.5 模型导出 - -使用如下命令可以将训练好的模型进行导出。 - -* 非量化模型 -```bash -python tools/export_model.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \ - Global.pretrained_model=output/CCPD/rec/best_accuracy.pdparams \ - Global.save_inference_dir=output/CCPD/rec/infer -``` -* 量化模型 -```bash -python deploy/slim/quantization/export_model.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \ - Global.pretrained_model=output/CCPD/rec_quant/best_accuracy.pdparams \ - Global.save_inference_dir=output/CCPD/rec_quant/infer -``` - -### 4.3 串联推理 - -检测模型和识别模型分别fine-tune并导出为inference模型之后,可以使用如下命令进行端到端推理并对结果进行可视化。 - - -```bash -python tools/infer/predict_system.py \ - --det_model_dir=output/CCPD/det/infer/ \ - --rec_model_dir=output/CCPD/rec/infer/ \ - --image_dir="/home/aistudio/data/CCPD2020/ccpd_green/test/04131106321839081-92_258-159&509_530&611-527&611_172&599_159&509_530&525-0_0_3_32_30_31_30_30-109-106.jpg" \ - --rec_image_shape=3,48,320 -``` -推理结果如下 - -![](https://ai-studio-static-online.cdn.bcebos.com/76b6a0939c2c4cf49039b6563c4b28e241e11285d7464e799e81c58c0f7707a7) - - -### 4.4 实验总结 - -我们分别使用PP-OCRv3中英文超轻量预训练模型在车牌数据集上进行了直接评估和finetune 和finetune+量化3种方案的实验,指标对比如下: - -- 检测 - -|方案|hmeans| 模型大小 |预测速度(lite)| -|---|---|------|---| -|PP-OCRv3中英文超轻量检测预训练模型直接预测|76.12%|2.5M| 223ms/image | -|PP-OCRv3中英文超轻量检测预训练模型 fine-tune|99%| 2.5M | 223ms/image | -|PP-OCRv3中英文超轻量检测预训练模型 fine-tune+量化|98.91%| 1M | 189ms/image | - -预测速度是在android骁龙855上预测275张图像的平均耗时。 - -- 识别 - -|方案| acc | 模型大小 |预测速度(lite)| -|---|--------|-------|---| -|PP-OCRv3中英文超轻量识别预训练模型直接预测| 0% |10.3M| 4.2ms/image | -|PP-OCRv3中英文超轻量识别预训练模型直接预测+后处理去掉多识别的`·`| 90.97% |10.3M| 4.2ms/image | -|PP-OCRv3中英文超轻量识别预训练模型 fine-tune| 94.54% | 10.3M | 4.2ms/image | -|PP-OCRv3中英文超轻量识别预训练模型 fine-tune + 量化| 94.4% | 4.8M | 1.8ms/image | - -预测速度是在android骁龙855上预测5006张识别文字图像的平均耗时。 - -- 结论 - -PP-OCRv3的检测模型在未经过fine-tune的情况下,在车牌数据集上也有一定的精度,经过finetune后能够极大的提升检测效果,精度达到99%。在使用量化训练后检测模型的精度几乎无损,并且模型大小压缩60%。 - -PP-OCRv3的识别模型在未经过fine-tune的情况下,在车牌数据集上精度为0,但是经过分析可以知道,模型大部分字符都预测正确,但是会多预测一个特殊字符,去掉这个特殊字符后,精度达到90%。PP-OCRv3识别模型在经过finetune后识别精度进一步提升,达到94.4%。在使用量化训练后识别模型大小压缩53%,但是由于数据量多少,带来了1%的精度损失。 diff --git "a/applications/\350\275\273\351\207\217\347\272\247\350\275\246\347\211\214\350\257\206\345\210\253.md" "b/applications/\350\275\273\351\207\217\347\272\247\350\275\246\347\211\214\350\257\206\345\210\253.md" new file mode 100644 index 0000000000000000000000000000000000000000..b6c3847d14c4c9b6f89333d1f4b806bd1f68499f --- /dev/null +++ "b/applications/\350\275\273\351\207\217\347\272\247\350\275\246\347\211\214\350\257\206\345\210\253.md" @@ -0,0 +1,2831 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + PaddleOCR/轻量级车牌识别.md at dygraph · PaddlePaddle/PaddleOCR · GitHub + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+

一种基于PaddleOCR的轻量级车牌识别模型

+ +

1. 项目介绍

+

车牌识别(Vehicle License Plate Recognition,VLPR) 是计算机视频图像识别技术在车辆牌照识别中的一种应用。车牌识别技术要求能够将运动中的汽车牌照从复杂背景中提取并识别出来,在高速公路车辆管理,停车场管理和城市交通中得到广泛应用。

+

本项目难点如下:

+
    +
  1. 车牌在图像中的尺度差异大、在车辆上的悬挂位置不固定
  2. +
  3. 车牌图像质量层次不齐: 角度倾斜、图片模糊、光照不足、过曝等问题严重
  4. +
  5. 边缘和端测场景应用对模型大小有限制,推理速度有要求
  6. +
+

针对以上问题, 本例选用 PP-OCRv3 这一开源超轻量OCR系统进行车牌识别系统的开发。基于PP-OCRv3模型,在CCPD数据集达到99%的检测和94%的识别精度,模型大小12.8M(2.5M+10.3M)。基于量化对模型体积进行进一步压缩到5.8M(1M+4.8M), 同时推理速度提升25%。

+

aistudio项目链接: 基于PaddleOCR的轻量级车牌识别范例

+

2. 环境搭建

+

本任务基于Aistudio完成, 具体环境如下:

+
    +
  • 操作系统: Linux
  • +
  • PaddlePaddle: 2.3
  • +
  • paddleslim: 2.2.2
  • +
  • PaddleOCR: Release/2.5
  • +
+

下载 PaddleOCR代码

+
git clone -b dygraph https://github.com/PaddlePaddle/PaddleOCR
+

安装依赖库

+
pip install -r PaddleOCR/requirements.txt
+

3. 数据集准备

+

所使用的数据集为 CCPD2020 新能源车牌数据集,该数据集为

+

该数据集分布如下:

+ + + + + + + + + + + + + + + + + + + + + +
数据集类型数量
训练集5769
验证集1001
测试集5006
+

数据集图片示例如下: +

+

数据集可以从这里下载 https://aistudio.baidu.com/aistudio/datasetdetail/101595

+

下载好数据集后对数据集进行解压

+
unzip -d /home/aistudio/data /home/aistudio/data/data101595/CCPD2020.zip
+

3.1 数据集标注规则

+

CPPD数据集的图片文件名具有特殊规则,详细可查看:https://github.com/detectRecog/CCPD

+

具体规则如下:

+

例如: 025-95_113-154&383_386&473-386&473_177&454_154&383_363&402-0_0_22_27_27_33_16-37-15.jpg

+

每个名称可以分为七个字段,以-符号作为分割。这些字段解释如下。

+
    +
  • +

    025:车牌面积与整个图片区域的面积比。025 (25%)

    +
  • +
  • +

    95_113:水平倾斜程度和垂直倾斜度。水平 95度 垂直 113度

    +
  • +
  • +

    154&383_386&473:左上和右下顶点的坐标。左上(154,383) 右下(386,473)

    +
  • +
  • +

    386&473_177&454_154&383_363&402:整个图像中车牌的四个顶点的精确(x,y)坐标。这些坐标从右下角顶点开始。(386,473) (177,454) (154,383) (363,402)

    +
  • +
  • +

    0_0_22_27_27_33_16:CCPD中的每个图像只有一个车牌。每个车牌号码由一个汉字,一个字母和五个字母或数字组成。有效的中文车牌由七个字符组成:省(1个字符),字母(1个字符),字母+数字(5个字符)。“ 0_0_22_27_27_33_16”是每个字符的索引。这三个数组定义如下。每个数组的最后一个字符是字母O,而不是数字0。我们将O用作“无字符”的符号,因为中文车牌字符中没有O。因此以上车牌拼起来即为 皖AY339S

    +
  • +
  • +

    37:牌照区域的亮度。 37 (37%)

    +
  • +
  • +

    15:车牌区域的模糊度。15 (15%)

    +
  • +
+
provinces = ["皖", "沪", "津", "渝", "冀", "晋", "蒙", "辽", "吉", "黑", "苏", "浙", "京", "闽", "赣", "鲁", "豫", "鄂", "湘", "粤", "桂", "琼", "川", "贵", "云", "藏", "陕", "甘", "青", "宁", "新", "警", "学", "O"]
+alphabets = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W','X', 'Y', 'Z', 'O']
+ads = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X','Y', 'Z', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'O']
+

3.2 制作符合PP-OCR训练格式的标注文件

+

在开始训练之前,可使用如下代码制作符合PP-OCR训练格式的标注文件。

+
import cv2
+import os
+import json
+from tqdm import tqdm
+import numpy as np
+
+provinces = ["皖", "沪", "津", "渝", "冀", "晋", "蒙", "辽", "吉", "黑", "苏", "浙", "京", "闽", "赣", "鲁", "豫", "鄂", "湘", "粤", "桂", "琼", "川", "贵", "云", "藏", "陕", "甘", "青", "宁", "新", "警", "学", "O"]
+alphabets = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', 'O']
+ads = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'O']
+
+def make_label(img_dir, save_gt_folder, phase):
+    crop_img_save_dir = os.path.join(save_gt_folder, phase, 'crop_imgs')
+    os.makedirs(crop_img_save_dir, exist_ok=True)
+
+    f_det = open(os.path.join(save_gt_folder, phase, 'det.txt'), 'w', encoding='utf-8')
+    f_rec = open(os.path.join(save_gt_folder, phase, 'rec.txt'), 'w', encoding='utf-8')
+
+    i = 0
+    for filename in tqdm(os.listdir(os.path.join(img_dir, phase))):
+        str_list = filename.split('-')
+        if len(str_list) < 5:
+            continue
+        coord_list = str_list[3].split('_')
+        txt_list = str_list[4].split('_')
+        boxes = []
+        for coord in coord_list:
+            boxes.append([int(x) for x in coord.split("&")])
+        boxes = [boxes[2], boxes[3], boxes[0], boxes[1]]
+        lp_number = provinces[int(txt_list[0])] + alphabets[int(txt_list[1])] + ''.join([ads[int(x)] for x in txt_list[2:]])
+
+        # det
+        det_info = [{'points':boxes, 'transcription':lp_number}]
+        f_det.write('{}\t{}\n'.format(os.path.join(phase, filename), json.dumps(det_info, ensure_ascii=False)))
+
+        # rec
+        boxes = np.float32(boxes)
+        img = cv2.imread(os.path.join(img_dir, phase, filename))
+        # crop_img = img[int(boxes[:,1].min()):int(boxes[:,1].max()),int(boxes[:,0].min()):int(boxes[:,0].max())]
+        crop_img = get_rotate_crop_image(img, boxes)
+        crop_img_save_filename = '{}_{}.jpg'.format(i,'_'.join(txt_list))
+        crop_img_save_path = os.path.join(crop_img_save_dir, crop_img_save_filename)
+        cv2.imwrite(crop_img_save_path, crop_img)
+        f_rec.write('{}/crop_imgs/{}\t{}\n'.format(phase, crop_img_save_filename, lp_number))
+        i+=1
+    f_det.close()
+    f_rec.close()
+
+def get_rotate_crop_image(img, points):
+    '''
+    img_height, img_width = img.shape[0:2]
+    left = int(np.min(points[:, 0]))
+    right = int(np.max(points[:, 0]))
+    top = int(np.min(points[:, 1]))
+    bottom = int(np.max(points[:, 1]))
+    img_crop = img[top:bottom, left:right, :].copy()
+    points[:, 0] = points[:, 0] - left
+    points[:, 1] = points[:, 1] - top
+    '''
+    assert len(points) == 4, "shape of points must be 4*2"
+    img_crop_width = int(
+        max(
+            np.linalg.norm(points[0] - points[1]),
+            np.linalg.norm(points[2] - points[3])))
+    img_crop_height = int(
+        max(
+            np.linalg.norm(points[0] - points[3]),
+            np.linalg.norm(points[1] - points[2])))
+    pts_std = np.float32([[0, 0], [img_crop_width, 0],
+                          [img_crop_width, img_crop_height],
+                          [0, img_crop_height]])
+    M = cv2.getPerspectiveTransform(points, pts_std)
+    dst_img = cv2.warpPerspective(
+        img,
+        M, (img_crop_width, img_crop_height),
+        borderMode=cv2.BORDER_REPLICATE,
+        flags=cv2.INTER_CUBIC)
+    dst_img_height, dst_img_width = dst_img.shape[0:2]
+    if dst_img_height * 1.0 / dst_img_width >= 1.5:
+        dst_img = np.rot90(dst_img)
+    return dst_img
+
+img_dir = '/home/aistudio/data/CCPD2020/ccpd_green'
+save_gt_folder = '/home/aistudio/data/CCPD2020/PPOCR'
+# phase = 'train' # change to val and test to make val dataset and test dataset
+for phase in ['train','val','test']:
+    make_label(img_dir, save_gt_folder, phase)
+

通过上述命令可以完成了训练集验证集测试集的制作,制作完成的数据集信息如下:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
类型数据集图片地址标签地址图片数量
检测训练集/home/aistudio/data/CCPD2020/ccpd_green/train/home/aistudio/data/CCPD2020/PPOCR/train/det.txt5769
检测验证集/home/aistudio/data/CCPD2020/ccpd_green/val/home/aistudio/data/CCPD2020/PPOCR/val/det.txt1001
检测测试集/home/aistudio/data/CCPD2020/ccpd_green/test/home/aistudio/data/CCPD2020/PPOCR/test/det.txt5006
识别训练集/home/aistudio/data/CCPD2020/PPOCR/train/crop_imgs/home/aistudio/data/CCPD2020/PPOCR/train/rec.txt5769
识别验证集/home/aistudio/data/CCPD2020/PPOCR/val/crop_imgs/home/aistudio/data/CCPD2020/PPOCR/val/rec.txt1001
识别测试集/home/aistudio/data/CCPD2020/PPOCR/test/crop_imgs/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt5006
+

在普遍的深度学习流程中,都是在训练集训练,在验证集选择最优模型后在测试集上进行测试。在本例中,我们省略中间步骤,直接在训练集训练,在测试集选择最优模型,因此我们只使用训练集和测试集。

+

4. 实验

+

由于数据集比较少,为了模型更好和更快的收敛,这里选用 PaddleOCR 中的 PP-OCRv3 模型进行文本检测和识别,并且使用 PP-OCRv3 模型参数作为预训练模型。PP-OCRv3在PP-OCRv2的基础上,中文场景端到端Hmean指标相比于PP-OCRv2提升5%, 英文数字模型端到端效果提升11%。详细优化细节请参考PP-OCRv3技术报告。

+

由于车牌场景均为端侧设备部署,因此对速度和模型大小有比较高的要求,因此还需要采用量化训练的方式进行模型大小的压缩和模型推理速度的加速。模型量化可以在基本不损失模型的精度的情况下,将FP32精度的模型参数转换为Int8精度,减小模型参数大小并加速计算,使用量化后的模型在移动端等部署时更具备速度优势。

+

因此,本实验中对于车牌检测和识别有如下3种方案:

+
    +
  1. PP-OCRv3中英文超轻量预训练模型直接预测
  2. +
  3. CCPD车牌数据集在PP-OCRv3模型上fine-tune
  4. +
  5. CCPD车牌数据集在PP-OCRv3模型上fine-tune后量化
  6. +
+

4.1 检测

+

4.1.1 预训练模型直接预测

+

从下表中下载PP-OCRv3文本检测预训练模型

+ + + + + + + + + + + + + + + + + + + +
模型名称模型简介配置文件推理模型大小下载地址
ch_PP-OCRv3_det【最新】原始超轻量模型,支持中英文、多语种文本检测ch_PP-OCRv3_det_cml.yml3.8M推理模型 / 训练模型
+

使用如下命令下载预训练模型

+
mkdir models
+cd models
+wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar
+tar -xf ch_PP-OCRv3_det_distill_train.tar
+cd /home/aistudio/PaddleOCR
+

预训练模型下载完成后,我们使用ch_PP-OCRv3_det_student.yml 配置文件进行后续实验,在开始评估之前需要对配置文件中部分字段进行设置,具体如下:

+
    +
  1. 模型存储和训练相关: +
      +
    1. Global.pretrained_model: 指向PP-OCRv3文本检测预训练模型地址
    2. +
    +
  2. +
  3. 数据集相关 +
      +
    1. Eval.dataset.data_dir:指向测试集图片存放目录
    2. +
    3. Eval.dataset.label_file_list:指向测试集标注文件
    4. +
    +
  4. +
+

上述字段均为必须修改的字段,可以通过修改配置文件的方式改动,也可在不需要修改配置文件的情况下,改变训练的参数。这里使用不改变配置文件的方式 。使用如下命令进行PP-OCRv3文本检测预训练模型的评估

+
python tools/eval.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=models/ch_PP-OCRv3_det_distill_train/student.pdparams \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt]
+

上述指令中,通过-c 选择训练使用配置文件,通过-o参数在不需要修改配置文件的情况下,改变训练的参数。

+

使用预训练模型进行评估,指标如下所示:

+ + + + + + + + + + + + + +
方案hmeans
PP-OCRv3中英文超轻量检测预训练模型直接预测76.12%
+

4.1.2 CCPD车牌数据集fine-tune

+

训练

+

为了进行fine-tune训练,我们需要在配置文件中设置需要使用的预训练模型地址,学习率和数据集等参数。 具体如下:

+
    +
  1. 模型存储和训练相关: +
      +
    1. Global.pretrained_model: 指向PP-OCRv3文本检测预训练模型地址
    2. +
    3. Global.eval_batch_step: 模型多少step评估一次,这里设为从第0个step开始没隔772个step评估一次,772为一个epoch总的step数。
    4. +
    +
  2. +
  3. 优化器相关: +
      +
    1. Optimizer.lr.name: 学习率衰减器设为常量 Const
    2. +
    3. Optimizer.lr.learning_rate: 做 fine-tune 实验,学习率需要设置的比较小,此处学习率设为配置文件中的0.05倍
    4. +
    5. Optimizer.lr.warmup_epoch: warmup_epoch设为0
    6. +
    +
  4. +
  5. 数据集相关: +
      +
    1. Train.dataset.data_dir:指向训练集图片存放目录
    2. +
    3. Train.dataset.label_file_list:指向训练集标注文件
    4. +
    5. Eval.dataset.data_dir:指向测试集图片存放目录
    6. +
    7. Eval.dataset.label_file_list:指向测试集标注文件
    8. +
    +
  6. +
+

使用如下代码即可启动在CCPD车牌数据集上的fine-tune。

+
python tools/train.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=models/ch_PP-OCRv3_det_distill_train/student.pdparams \
+    Global.save_model_dir=output/CCPD/det \
+    Global.eval_batch_step="[0, 772]" \
+    Optimizer.lr.name=Const \
+    Optimizer.lr.learning_rate=0.0005 \
+    Optimizer.lr.warmup_epoch=0 \
+    Train.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \
+    Train.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/train/det.txt] \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt]
+

在上述命令中,通过-o的方式修改了配置文件中的参数。

+

训练好的模型地址为: det_ppocr_v3_finetune.tar

+

评估

+

训练完成后使用如下命令进行评估

+
python tools/eval.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=output/CCPD/det/best_accuracy.pdparams \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt]
+

使用预训练模型和CCPD车牌数据集fine-tune,指标分别如下:

+ + + + + + + + + + + + + + + + + +
方案hmeans
PP-OCRv3中英文超轻量检测预训练模型直接预测76.12%
PP-OCRv3中英文超轻量检测预训练模型 fine-tune99%
+

可以看到进行fine-tune能显著提升车牌检测的效果。

+

4.1.3 CCPD车牌数据集fine-tune+量化训练

+

此处采用 PaddleOCR 中提供好的量化教程对模型进行量化训练。

+

量化训练可通过如下命令启动:

+
python3.7 deploy/slim/quantization/quant.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=output/CCPD/det/best_accuracy.pdparams \
+    Global.save_model_dir=output/CCPD/det_quant \
+    Global.eval_batch_step="[0, 772]" \
+    Optimizer.lr.name=Const \
+    Optimizer.lr.learning_rate=0.0005 \
+    Optimizer.lr.warmup_epoch=0 \
+    Train.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \
+    Train.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/train/det.txt] \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt]
+

训练好的模型地址为: det_ppocr_v3_quant.tar

+

量化后指标对比如下

+ + + + + + + + + + + + + + + + + + + + + + + +
方案hmeans模型大小预测速度(lite)
PP-OCRv3中英文超轻量检测预训练模型 fine-tune99%2.5M223ms
PP-OCRv3中英文超轻量检测预训练模型 fine-tune+量化98.91%1M189ms
+

可以看到通过量化训练在精度几乎无损的情况下,降低模型体积60%并且推理速度提升15%。

+

速度测试基于PaddleOCR lite教程完成。

+

4.1.4 模型导出

+

使用如下命令可以将训练好的模型进行导出

+
    +
  • 非量化模型
  • +
+
python tools/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=output/CCPD/det/best_accuracy.pdparams \
+    Global.save_inference_dir=output/det/infer
+
    +
  • 量化模型
  • +
+
python deploy/slim/quantization/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=output/CCPD/det_quant/best_accuracy.pdparams \
+    Global.save_inference_dir=output/det/infer
+

4.2 识别

+

4.2.1 预训练模型直接预测

+

从下表中下载PP-OCRv3文本识别预训练模型

+ + + + + + + + + + + + + + + + + + + +
模型名称模型简介配置文件推理模型大小下载地址
ch_PP-OCRv3_rec【最新】原始超轻量模型,支持中英文、数字识别ch_PP-OCRv3_rec_distillation.yml12.4M推理模型 / 训练模型
+

使用如下命令下载预训练模型

+
mkdir models
+cd models
+wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar
+tar -xf ch_PP-OCRv3_rec_train.tar
+cd /home/aistudio/PaddleOCR
+

PaddleOCR提供的PP-OCRv3识别模型采用蒸馏训练策略,因此提供的预训练模型中会包含TeacherStudent模型的参数,详细信息可参考knowledge_distillation.md。 因此,模型下载完成后需要使用如下代码提取Student模型的参数:

+
import paddle
+# 加载预训练模型
+all_params = paddle.load("models/ch_PP-OCRv3_rec_train/best_accuracy.pdparams")
+# 查看权重参数的keys
+print(all_params.keys())
+# 学生模型的权重提取
+s_params = {key[len("Student."):]: all_params[key] for key in all_params if "Student." in key}
+# 查看学生模型权重参数的keys
+print(s_params.keys())
+# 保存
+paddle.save(s_params, "models/ch_PP-OCRv3_rec_train/student.pdparams")
+

预训练模型下载完成后,我们使用ch_PP-OCRv3_rec.yml 配置文件进行后续实验,在开始评估之前需要对配置文件中部分字段进行设置,具体如下:

+
    +
  1. 模型存储和训练相关: +
      +
    1. Global.pretrained_model: 指向PP-OCRv3文本识别预训练模型地址
    2. +
    +
  2. +
  3. 数据集相关 +
      +
    1. Eval.dataset.data_dir:指向测试集图片存放目录
    2. +
    3. Eval.dataset.label_file_list:指向测试集标注文件
    4. +
    +
  4. +
+

使用如下命令进行PP-OCRv3文本识别预训练模型的评估

+
python tools/eval.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=models/ch_PP-OCRv3_rec_train/student.pdparams \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt]
+

评估部分日志如下:

+
[2022/05/12 19:52:02] ppocr INFO: load pretrain successful from models/ch_PP-OCRv3_rec_train/best_accuracy
+eval model:: 100%|██████████████████████████████| 40/40 [00:15<00:00,  2.57it/s]
+[2022/05/12 19:52:17] ppocr INFO: metric eval ***************
+[2022/05/12 19:52:17] ppocr INFO: acc:0.0
+[2022/05/12 19:52:17] ppocr INFO: norm_edit_dis:0.8656084923002452
+[2022/05/12 19:52:17] ppocr INFO: Teacher_acc:0.000399520574511545
+[2022/05/12 19:52:17] ppocr INFO: Teacher_norm_edit_dis:0.8657902943394548
+[2022/05/12 19:52:17] ppocr INFO: fps:1443.1801978719905
+
+

使用预训练模型进行评估,指标如下所示:

+ + + + + + + + + + + + + +
方案acc
PP-OCRv3中英文超轻量识别预训练模型直接预测0%
+

从评估日志中可以看到,直接使用PP-OCRv3预训练模型进行评估,acc非常低,但是norm_edit_dis很高。因此,我们猜测是模型大部分文字识别是对的,只有少部分文字识别错误。使用如下命令进行infer查看模型的推理结果进行验证:

+
python tools/infer_rec.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=models/ch_PP-OCRv3_rec_train/student.pdparams \
+    Global.infer_img=/home/aistudio/data/CCPD2020/PPOCR/test/crop_imgs/0_0_0_3_32_30_31_30_30.jpg
+

输出部分日志如下:

+
[2022/05/01 08:51:57] ppocr INFO: train with paddle 2.2.2 and device CUDAPlace(0)
+W0501 08:51:57.127391 11326 device_context.cc:447] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 11.0, Runtime API Version: 10.1
+W0501 08:51:57.132315 11326 device_context.cc:465] device: 0, cuDNN Version: 7.6.
+[2022/05/01 08:52:00] ppocr INFO: load pretrain successful from models/ch_PP-OCRv3_rec_train/student
+[2022/05/01 08:52:00] ppocr INFO: infer_img: /home/aistudio/data/CCPD2020/PPOCR/test/crop_imgs/0_0_3_32_30_31_30_30.jpg
+[2022/05/01 08:52:00] ppocr INFO:      result: {"Student": {"label": "皖A·D86766", "score": 0.9552637934684753}, "Teacher": {"label": "皖A·D86766", "score": 0.9917094707489014}}
+[2022/05/01 08:52:00] ppocr INFO: success!
+

从infer结果可以看到,车牌中的文字大部分都识别正确,只是多识别出了一个·。针对这种情况,有如下两种方案:

+
    +
  1. 直接通过后处理去掉多识别的·
  2. +
  3. 进行 fine-tune。
  4. +
+

4.2.2 预训练模型直接预测+改动后处理

+

直接通过后处理去掉多识别的·,在后处理的改动比较简单,只需在 ppocr/postprocess/rec_postprocess.py 文件的76行添加如下代码:

+
text = text.replace('·','')
+

改动前后指标对比:

+ + + + + + + + + + + + + + + + + +
方案acc
PP-OCRv3中英文超轻量识别预训练模型直接预测0.2%
PP-OCRv3中英文超轻量识别预训练模型直接预测+后处理去掉多识别的·90.97%
+

可以看到,去掉多余的·能大幅提高精度。

+

4.2.3 CCPD车牌数据集fine-tune

+

训练

+

为了进行fine-tune训练,我们需要在配置文件中设置需要使用的预训练模型地址,学习率和数据集等参数。 具体如下:

+
    +
  1. 模型存储和训练相关: +
      +
    1. Global.pretrained_model: 指向PP-OCRv3文本识别预训练模型地址
    2. +
    3. Global.eval_batch_step: 模型多少step评估一次,这里设为从第0个step开始没隔45个step评估一次,45为一个epoch总的step数。
    4. +
    +
  2. +
  3. 优化器相关 +
      +
    1. Optimizer.lr.name: 学习率衰减器设为常量 Const
    2. +
    3. Optimizer.lr.learning_rate: 做 fine-tune 实验,学习率需要设置的比较小,此处学习率设为配置文件中的0.05倍
    4. +
    5. Optimizer.lr.warmup_epoch: warmup_epoch设为0
    6. +
    +
  4. +
  5. 数据集相关 +
      +
    1. Train.dataset.data_dir:指向训练集图片存放目录
    2. +
    3. Train.dataset.label_file_list:指向训练集标注文件
    4. +
    5. Eval.dataset.data_dir:指向测试集图片存放目录
    6. +
    7. Eval.dataset.label_file_list:指向测试集标注文件
    8. +
    +
  6. +
+

使用如下命令启动 fine-tune

+
python tools/train.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=models/ch_PP-OCRv3_rec_train/student.pdparams \
+    Global.save_model_dir=output/CCPD/rec/ \
+    Global.eval_batch_step="[0, 90]" \
+    Optimizer.lr.name=Const \
+    Optimizer.lr.learning_rate=0.0005 \
+    Optimizer.lr.warmup_epoch=0 \
+    Train.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \
+    Train.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/train/rec.txt] \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt]
+

训练好的模型地址为: rec_ppocr_v3_finetune.tar

+

评估

+

训练完成后使用如下命令进行评估

+
python tools/eval.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=output/CCPD/rec/best_accuracy.pdparams \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt]
+

使用预训练模型和CCPD车牌数据集fine-tune,指标分别如下:

+ + + + + + + + + + + + + + + + + + + + + +
方案acc
PP-OCRv3中英文超轻量识别预训练模型直接预测0%
PP-OCRv3中英文超轻量识别预训练模型直接预测+后处理去掉多识别的·90.97%
PP-OCRv3中英文超轻量识别预训练模型 fine-tune94.54%
+

可以看到进行fine-tune能显著提升车牌识别的效果。

+

4.2.4 CCPD车牌数据集fine-tune+量化训练

+

此处采用 PaddleOCR 中提供好的量化教程对模型进行量化训练。

+

量化训练可通过如下命令启动:

+
python3.7 deploy/slim/quantization/quant.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=output/CCPD/rec/best_accuracy.pdparams \
+    Global.save_model_dir=output/CCPD/rec_quant/ \
+    Global.eval_batch_step="[0, 90]" \
+    Optimizer.lr.name=Const \
+    Optimizer.lr.learning_rate=0.0005 \
+    Optimizer.lr.warmup_epoch=0 \
+    Train.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \
+    Train.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/train/rec.txt] \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt]
+

训练好的模型地址为: rec_ppocr_v3_quant.tar

+

量化后指标对比如下

+ + + + + + + + + + + + + + + + + + + + + + + +
方案acc模型大小预测速度(lite)
PP-OCRv3中英文超轻量识别预训练模型 fine-tune94.54%10.3M4.2ms
PP-OCRv3中英文超轻量识别预训练模型 fine-tune + 量化93.4%4.8M1.8ms
+

可以看到量化后能降低模型体积53%并且推理速度提升57%,但是由于识别数据过少,量化带来了1%的精度下降。

+

速度测试基于PaddleOCR lite教程完成。

+

4.2.5 模型导出

+

使用如下命令可以将训练好的模型进行导出。

+
    +
  • 非量化模型
  • +
+
python tools/export_model.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=output/CCPD/rec/best_accuracy.pdparams \
+    Global.save_inference_dir=output/CCPD/rec/infer
+
    +
  • 量化模型
  • +
+
python deploy/slim/quantization/export_model.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=output/CCPD/rec_quant/best_accuracy.pdparams \
+    Global.save_inference_dir=output/CCPD/rec_quant/infer
+

4.3 计算End2End指标

+

端到端指标可通过 PaddleOCR内置脚本 进行计算,具体步骤如下:

+
    +
  1. 导出模型
  2. +
+

通过如下命令进行模型的导出。注意,量化模型导出时,需要配置eval数据集

+
# 检测模型
+
+# 预训练模型
+python tools/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=models/ch_PP-OCRv3_det_distill_train/student.pdparams \
+    Global.save_inference_dir=output/ch_PP-OCRv3_det_distill_train/infer
+
+# 非量化模型
+python tools/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=output/CCPD/det/best_accuracy.pdparams \
+    Global.save_inference_dir=output/CCPD/det/infer
+
+# 量化模型
+python deploy/slim/quantization/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o \
+    Global.pretrained_model=output/CCPD/det_quant/best_accuracy.pdparams \
+    Global.save_inference_dir=output/CCPD/det_quant/infer \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/ccpd_green \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/det.txt] \
+    Eval.loader.num_workers=0
+
+# 识别模型
+
+# 预训练模型
+python tools/export_model.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=models/ch_PP-OCRv3_rec_train/student.pdparams \
+    Global.save_inference_dir=output/ch_PP-OCRv3_rec_train/infer
+
+# 非量化模型
+python tools/export_model.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=output/CCPD/rec/best_accuracy.pdparams \
+    Global.save_inference_dir=output/CCPD/rec/infer
+
+# 量化模型
+python deploy/slim/quantization/export_model.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o \
+    Global.pretrained_model=output/CCPD/rec_quant/best_accuracy.pdparams \
+    Global.save_inference_dir=output/CCPD/rec_quant/infer \
+    Eval.dataset.data_dir=/home/aistudio/data/CCPD2020/PPOCR \
+    Eval.dataset.label_file_list=[/home/aistudio/data/CCPD2020/PPOCR/test/rec.txt]
+
    +
  1. 用导出的模型对测试集进行预测
  2. +
+

此处,分别使用PP-OCRv3预训练模型,fintune模型和量化模型对测试集的所有图像进行预测,命令如下:

+
# PP-OCRv3中英文超轻量检测预训练模型,PP-OCRv3中英文超轻量识别预训练模型
+python3 tools/infer/predict_system.py --det_model_dir=models/ch_PP-OCRv3_det_distill_train/infer --rec_model_dir=models/ch_PP-OCRv3_rec_train/infer --det_limit_side_len=736 --det_limit_type=min --image_dir=/home/aistudio/data/CCPD2020/ccpd_green/test/ --draw_img_save_dir=infer/pretrain --use_dilation=true
+
+# PP-OCRv3中英文超轻量检测预训练模型+fine-tune,PP-OCRv3中英文超轻量识别预训练模型+fine-tune
+python3 tools/infer/predict_system.py --det_model_dir=output/CCPD/det/infer --rec_model_dir=output/CCPD/rec/infer --det_limit_side_len=736 --det_limit_type=min --image_dir=/home/aistudio/data/CCPD2020/ccpd_green/test/ --draw_img_save_dir=infer/fine-tune --use_dilation=true
+
+# PP-OCRv3中英文超轻量检测预训练模型 fine-tune +量化,PP-OCRv3中英文超轻量识别预训练模型 fine-tune +量化 结果转换和评估
+python3 tools/infer/predict_system.py --det_model_dir=output/CCPD/det_quant/infer --rec_model_dir=output/CCPD/rec_quant/infer --det_limit_side_len=736 --det_limit_type=min --image_dir=/home/aistudio/data/CCPD2020/ccpd_green/test/ --draw_img_save_dir=infer/quant --use_dilation=true
+
    +
  1. 转换label并计算指标
  2. +
+

将gt和上一步保存的预测结果转换为端对端评测需要的数据格式,并根据转换后的数据进行端到端指标计算

+
python3 tools/end2end/convert_ppocr_label.py --mode=gt --label_path=/home/aistudio/data/CCPD2020/PPOCR/test/det.txt --save_folder=end2end/gt
+
+# PP-OCRv3中英文超轻量检测预训练模型,PP-OCRv3中英文超轻量识别预训练模型 结果转换和评估
+python3 tools/end2end/convert_ppocr_label.py --mode=pred --label_path=infer/pretrain/system_results.txt --save_folder=end2end/pretrain
+python3 tools/end2end/eval_end2end.py end2end/gt end2end/pretrain
+
+# PP-OCRv3中英文超轻量检测预训练模型,PP-OCRv3中英文超轻量识别预训练模型+后处理去掉多识别的`·` 结果转换和评估
+# 需手动修改后处理函数
+python3 tools/end2end/convert_ppocr_label.py --mode=pred --label_path=infer/post/system_results.txt --save_folder=end2end/post
+python3 tools/end2end/eval_end2end.py end2end/gt end2end/post
+
+# PP-OCRv3中英文超轻量检测预训练模型 fine-tune,PP-OCRv3中英文超轻量识别预训练模型 fine-tune 结果转换和评估
+python3 tools/end2end/convert_ppocr_label.py --mode=pred --label_path=infer/fine-tune/system_results.txt --save_folder=end2end/fine-tune
+python3 tools/end2end/eval_end2end.py end2end/gt end2end/fine-tune
+
+# PP-OCRv3中英文超轻量检测预训练模型 fine-tune +量化,PP-OCRv3中英文超轻量识别预训练模型 fine-tune +量化 结果转换和评估
+python3 tools/end2end/convert_ppocr_label.py --mode=pred --label_path=infer/quant/system_results.txt --save_folder=end2end/quant
+python3 tools/end2end/eval_end2end.py end2end/gt end2end/quant
+

日志如下:

+
The convert label saved in end2end/gt
+The convert label saved in end2end/pretrain
+start testing...
+hit, dt_count, gt_count 2 5988 5006
+character_acc: 70.42%
+avg_edit_dist_field: 2.37
+avg_edit_dist_img: 2.37
+precision: 0.03%
+recall: 0.04%
+fmeasure: 0.04%
+The convert label saved in end2end/post
+start testing...
+hit, dt_count, gt_count 4224 5988 5006
+character_acc: 81.59%
+avg_edit_dist_field: 1.47
+avg_edit_dist_img: 1.47
+precision: 70.54%
+recall: 84.38%
+fmeasure: 76.84%
+The convert label saved in end2end/fine-tune
+start testing...
+hit, dt_count, gt_count 4286 4898 5006
+character_acc: 94.16%
+avg_edit_dist_field: 0.47
+avg_edit_dist_img: 0.47
+precision: 87.51%
+recall: 85.62%
+fmeasure: 86.55%
+The convert label saved in end2end/quant
+start testing...
+hit, dt_count, gt_count 4349 4951 5006
+character_acc: 94.13%
+avg_edit_dist_field: 0.47
+avg_edit_dist_img: 0.47
+precision: 87.84%
+recall: 86.88%
+fmeasure: 87.36%
+

各个方案端到端指标如下:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
模型指标
PP-OCRv3中英文超轻量检测预训练模型
PP-OCRv3中英文超轻量识别预训练模型
0.04%
PP-OCRv3中英文超轻量检测预训练模型
PP-OCRv3中英文超轻量识别预训练模型 + 后处理去掉多识别的·
78.27%
PP-OCRv3中英文超轻量检测预训练模型+fine-tune
PP-OCRv3中英文超轻量识别预训练模型+fine-tune
87.14%
PP-OCRv3中英文超轻量检测预训练模型+fine-tune+量化
PP-OCRv3中英文超轻量识别预训练模型+fine-tune+量化
88%
+

从结果中可以看到对预训练模型不做修改,只根据场景下的具体情况进行后处理的修改就能大幅提升端到端指标到78.27%,在CCPD数据集上进行 fine-tune 后指标进一步提升到87.14%, 在经过量化训练之后,由于检测模型的recall变高,指标进一步提升到88%。但是这个结果仍旧不符合检测模型+识别模型的真实性能(99%*94%=93%),因此我们需要对 base case 进行具体分析。

+

在之前的端到端预测结果中,可以看到很多不符合车牌标注的文字被识别出来, 因此可以进行简单的过滤来提升precision

+

为了快速评估,我们在 tools/end2end/convert_ppocr_label.py 脚本的 58 行加入如下代码,对非8个字符的结果进行过滤

+
if len(txt) != 8: # 车牌字符串长度为8
+    continue
+

此外,通过可视化box可以发现有很多框都是竖直翻转之后的框,并且没有完全框住车牌边界,因此需要进行框的竖直翻转以及轻微扩大,示意图如下:

+

+

修改前后个方案指标对比如下:

+

各个方案端到端指标如下:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
模型baseA:识别结果过滤B:use_dilationC:flip_boxbest
PP-OCRv3中英文超轻量检测预训练模型
PP-OCRv3中英文超轻量识别预训练模型
0.04%0.08%0.02%0.05%0.00%(A)
PP-OCRv3中英文超轻量检测预训练模型
PP-OCRv3中英文超轻量识别预训练模型 + 后处理去掉多识别的·
78.27%90.84%78.61%79.43%91.66%(A+B+C)
PP-OCRv3中英文超轻量检测预训练模型+fine-tune
PP-OCRv3中英文超轻量识别预训练模型+fine-tune
87.14%90.40%87.66%89.9892.5%(A+B+C)
PP-OCRv3中英文超轻量检测预训练模型+fine-tune+量化
PP-OCRv3中英文超轻量识别预训练模型+fine-tune+量化
88%90.54%88.5%89.46%92.02%(A+B+C)
+

从结果中可以看到对预训练模型不做修改,只根据场景下的具体情况进行后处理的修改就能大幅提升端到端指标到91.66%,在CCPD数据集上进行 fine-tune 后指标进一步提升到92.5%, 在经过量化训练之后,指标变为92.02%。

+

4.4 部署

+
    +
  • 基于 Paddle Inference 的python推理
  • +
+

检测模型和识别模型分别 fine-tune 并导出为inference模型之后,可以使用如下命令基于 Paddle Inference 进行端到端推理并对结果进行可视化。

+
python tools/infer/predict_system.py \
+    --det_model_dir=output/CCPD/det/infer/ \
+    --rec_model_dir=output/CCPD/rec/infer/ \
+    --image_dir="/home/aistudio/data/CCPD2020/ccpd_green/test/04131106321839081-92_258-159&509_530&611-527&611_172&599_159&509_530&525-0_0_3_32_30_31_30_30-109-106.jpg" \
+    --rec_image_shape=3,48,320
+

推理结果如下

+

+
    +
  • 端侧部署
  • +
+

端侧部署我们采用基于 PaddleLite 的 cpp 推理。Paddle Lite是飞桨轻量化推理引擎,为手机、IOT端提供高效推理能力,并广泛整合跨平台硬件,为端侧部署及应用落地问题提供轻量化的部署方案。具体可参考 PaddleOCR lite教程

+

4.5 实验总结

+

我们分别使用PP-OCRv3中英文超轻量预训练模型在车牌数据集上进行了直接评估和 fine-tune 和 fine-tune +量化3种方案的实验,并基于PaddleOCR lite教程进行了速度测试,指标对比如下:

+
    +
  • 检测
  • +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
方案hmeans模型大小预测速度(lite)
PP-OCRv3中英文超轻量检测预训练模型直接预测76.12%2.5M233ms
PP-OCRv3中英文超轻量检测预训练模型 fine-tune99%2.5M233ms
PP-OCRv3中英文超轻量检测预训练模型 fine-tune + 量化98.91%1M189ms
+
    +
  • 识别
  • +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
方案acc模型大小预测速度(lite)
PP-OCRv3中英文超轻量识别预训练模型直接预测0%10.3M4.2ms
PP-OCRv3中英文超轻量识别预训练模型直接预测+后处理去掉多识别的·90.97%10.3M4.2ms
PP-OCRv3中英文超轻量识别预训练模型 fine-tune94.54%10.3M4,2ms
PP-OCRv3中英文超轻量识别预训练模型 fine-tune + 量化93.4%4.8M1.8ms
+
    +
  • 端到端指标如下:
  • +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
方案fmeasure模型大小预测速度(lite)
PP-OCRv3中英文超轻量检测预训练模型
PP-OCRv3中英文超轻量识别预训练模型
0.08%12.8M298ms
PP-OCRv3中英文超轻量检测预训练模型
PP-OCRv3中英文超轻量识别预训练模型 + 后处理去掉多识别的·
91.66%12.8M298ms
PP-OCRv3中英文超轻量检测预训练模型+fine-tune
PP-OCRv3中英文超轻量识别预训练模型+fine-tune
92.5%12.8M298ms
PP-OCRv3中英文超轻量检测预训练模型+fine-tune+量化
PP-OCRv3中英文超轻量识别预训练模型+fine-tune+量化
92.02%5.8M224ms
+

结论

+

PP-OCRv3的检测模型在未经过fine-tune的情况下,在车牌数据集上也有一定的精度,经过 fine-tune 后能够极大的提升检测效果,精度达到99%。在使用量化训练后检测模型的精度几乎无损,并且模型大小压缩60%。

+

PP-OCRv3的识别模型在未经过fine-tune的情况下,在车牌数据集上精度为0,但是经过分析可以知道,模型大部分字符都预测正确,但是会多预测一个特殊字符,去掉这个特殊字符后,精度达到90%。PP-OCRv3识别模型在经过 fine-tune 后识别精度进一步提升,达到94.4%。在使用量化训练后识别模型大小压缩53%,但是由于数据量多少,带来了1%的精度损失。

+

从端到端结果中可以看到对预训练模型不做修改,只根据场景下的具体情况进行后处理的修改就能大幅提升端到端指标到91.66%,在CCPD数据集上进行 fine-tune 后指标进一步提升到92.5%, 在经过量化训练之后,指标轻微下降到92.02%但模型大小降低54%。

+
+
+ +
+ +
+ + + +
+ + +
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+
+ + + + +
+ +
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+ + +
+
+ +
+ + + + + + + + + + + + + + + + + + + + diff --git a/configs/cls/ch_PP-OCRv3/ch_PP-OCRv3_rotnet.yml b/configs/cls/ch_PP-OCRv3/ch_PP-OCRv3_rotnet.yml index 1ffeba07995860f964e22b8b9d2538320d80f651..f7e327d1e0378ed75b03b1f866414ef34e197c47 100644 --- a/configs/cls/ch_PP-OCRv3/ch_PP-OCRv3_rotnet.yml +++ b/configs/cls/ch_PP-OCRv3/ch_PP-OCRv3_rotnet.yml @@ -63,8 +63,7 @@ Train: - DecodeImage: img_mode: BGR channel_first: false - - RecAug: - use_tia: False + - BaseDataAugmentation: - RandAugment: - SSLRotateResize: image_shape: [3, 48, 320] diff --git a/configs/cls/cls_mv3.yml b/configs/cls/cls_mv3.yml index 5e643dc3839b2e2edf3c811db813dd6a90797366..0c46ff560277d9e318587432671de09f0d13cf35 100644 --- a/configs/cls/cls_mv3.yml +++ b/configs/cls/cls_mv3.yml @@ -60,8 +60,7 @@ Train: img_mode: BGR channel_first: False - ClsLabelEncode: # Class handling label - - RecAug: - use_tia: False + - BaseDataAugmentation: - RandAugment: - ClsResizeImg: image_shape: [3, 48, 192] diff --git a/deploy/cpp_infer/CMakeLists.txt b/deploy/cpp_infer/CMakeLists.txt index 6d3ecb6ac2e9e6993814f077ca772d0d94f5d008..7deacfadc585e8905870e7fd218c6b115dcd8256 100644 --- a/deploy/cpp_infer/CMakeLists.txt +++ b/deploy/cpp_infer/CMakeLists.txt @@ -92,6 +92,8 @@ include_directories("${PADDLE_LIB}/third_party/install/glog/include") include_directories("${PADDLE_LIB}/third_party/install/gflags/include") include_directories("${PADDLE_LIB}/third_party/install/xxhash/include") include_directories("${PADDLE_LIB}/third_party/install/zlib/include") +include_directories("${PADDLE_LIB}/third_party/install/onnxruntime/include") +include_directories("${PADDLE_LIB}/third_party/install/paddle2onnx/include") include_directories("${PADDLE_LIB}/third_party/boost") include_directories("${PADDLE_LIB}/third_party/eigen3") @@ -110,6 +112,8 @@ link_directories("${PADDLE_LIB}/third_party/install/protobuf/lib") link_directories("${PADDLE_LIB}/third_party/install/glog/lib") link_directories("${PADDLE_LIB}/third_party/install/gflags/lib") link_directories("${PADDLE_LIB}/third_party/install/xxhash/lib") +link_directories("${PADDLE_LIB}/third_party/install/onnxruntime/lib") +link_directories("${PADDLE_LIB}/third_party/install/paddle2onnx/lib") link_directories("${PADDLE_LIB}/paddle/lib") diff --git a/deploy/cpp_infer/readme.md b/deploy/cpp_infer/readme.md index ddd15d49558454a5ffb0731665b118c929e607f0..a87db7e6596bc2528bfb4a93c3170ebf0482ccad 100644 --- a/deploy/cpp_infer/readme.md +++ b/deploy/cpp_infer/readme.md @@ -208,7 +208,7 @@ Execute the built executable file: ./build/ppocr [--param1] [--param2] [...] ``` -**Note**:ppocr uses the `PP-OCRv3` model by default, and the input shape used by the recognition model is `3, 48, 320`, so if you use the recognition function, you need to add the parameter `--rec_img_h=48`, if you do not use the default `PP-OCRv3` model, you do not need to set this parameter. +**Note**:ppocr uses the `PP-OCRv3` model by default, and the input shape used by the recognition model is `3, 48, 320`, if you want to use the old version model, you should add the parameter `--rec_img_h=32`. Specifically, @@ -222,7 +222,6 @@ Specifically, --det=true \ --rec=true \ --cls=true \ - --rec_img_h=48\ ``` ##### 2. det+rec: @@ -234,7 +233,6 @@ Specifically, --det=true \ --rec=true \ --cls=false \ - --rec_img_h=48\ ``` ##### 3. det @@ -254,7 +252,6 @@ Specifically, --det=false \ --rec=true \ --cls=true \ - --rec_img_h=48\ ``` ##### 5. rec @@ -265,7 +262,6 @@ Specifically, --det=false \ --rec=true \ --cls=false \ - --rec_img_h=48\ ``` ##### 6. cls @@ -330,7 +326,7 @@ More parameters are as follows, |rec_model_dir|string|-|Address of recognition inference model| |rec_char_dict_path|string|../../ppocr/utils/ppocr_keys_v1.txt|dictionary file| |rec_batch_num|int|6|batch size of recognition| -|rec_img_h|int|32|image height of recognition| +|rec_img_h|int|48|image height of recognition| |rec_img_w|int|320|image width of recognition| * Multi-language inference is also supported in PaddleOCR, you can refer to [recognition tutorial](../../doc/doc_en/recognition_en.md) for more supported languages and models in PaddleOCR. Specifically, if you want to infer using multi-language models, you just need to modify values of `rec_char_dict_path` and `rec_model_dir`. diff --git a/deploy/cpp_infer/readme_ch.md b/deploy/cpp_infer/readme_ch.md index e5a4869eca1d35765013e63011c680e59b33ac00..8c334851c0d44acd393c6daa79edf25dc9e6fa24 100644 --- a/deploy/cpp_infer/readme_ch.md +++ b/deploy/cpp_infer/readme_ch.md @@ -213,7 +213,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir 本demo支持系统串联调用,也支持单个功能的调用,如,只使用检测或识别功能。 -**注意** ppocr默认使用`PP-OCRv3`模型,识别模型使用的输入shape为`3,48,320`, 因此如果使用识别功能,需要添加参数`--rec_img_h=48`,如果不使用默认的`PP-OCRv3`模型,则无需设置该参数。 +**注意** ppocr默认使用`PP-OCRv3`模型,识别模型使用的输入shape为`3,48,320`, 如需使用旧版本的PP-OCR模型,则需要设置参数`--rec_img_h=32`。 运行方式: @@ -232,7 +232,6 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir --det=true \ --rec=true \ --cls=true \ - --rec_img_h=48\ ``` ##### 2. 检测+识别: @@ -244,7 +243,6 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir --det=true \ --rec=true \ --cls=false \ - --rec_img_h=48\ ``` ##### 3. 检测: @@ -264,7 +262,6 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir --det=false \ --rec=true \ --cls=true \ - --rec_img_h=48\ ``` ##### 5. 识别: @@ -275,7 +272,6 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir --det=false \ --rec=true \ --cls=false \ - --rec_img_h=48\ ``` ##### 6. 分类: @@ -339,7 +335,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir |rec_model_dir|string|-|识别模型inference model地址| |rec_char_dict_path|string|../../ppocr/utils/ppocr_keys_v1.txt|字典文件| |rec_batch_num|int|6|识别模型batchsize| -|rec_img_h|int|32|识别模型输入图像高度| +|rec_img_h|int|48|识别模型输入图像高度| |rec_img_w|int|320|识别模型输入图像宽度| diff --git a/deploy/cpp_infer/src/args.cpp b/deploy/cpp_infer/src/args.cpp index fe58236734568035dfb26570df39f21154f4e9ef..93d0f5ea5fd07bdc3eb44537bc1c0d4e131736d3 100644 --- a/deploy/cpp_infer/src/args.cpp +++ b/deploy/cpp_infer/src/args.cpp @@ -47,7 +47,7 @@ DEFINE_string(rec_model_dir, "", "Path of rec inference model."); DEFINE_int32(rec_batch_num, 6, "rec_batch_num."); DEFINE_string(rec_char_dict_path, "../../ppocr/utils/ppocr_keys_v1.txt", "Path of dictionary."); -DEFINE_int32(rec_img_h, 32, "rec image height"); +DEFINE_int32(rec_img_h, 48, "rec image height"); DEFINE_int32(rec_img_w, 320, "rec image width"); // ocr forward related diff --git a/deploy/cpp_infer/src/ocr_rec.cpp b/deploy/cpp_infer/src/ocr_rec.cpp index 0a6fe693e20b59b96a10d9189b7894ec83670ba2..0f90ddfab4872f97829da081e64cb7437e72493a 100644 --- a/deploy/cpp_infer/src/ocr_rec.cpp +++ b/deploy/cpp_infer/src/ocr_rec.cpp @@ -83,7 +83,7 @@ void CRNNRecognizer::Run(std::vector img_list, int out_num = std::accumulate(predict_shape.begin(), predict_shape.end(), 1, std::multiplies()); predict_batch.resize(out_num); - + // predict_batch is the result of Last FC with softmax output_t->CopyToCpu(predict_batch.data()); auto inference_end = std::chrono::steady_clock::now(); inference_diff += inference_end - inference_start; @@ -98,9 +98,11 @@ void CRNNRecognizer::Run(std::vector img_list, float max_value = 0.0f; for (int n = 0; n < predict_shape[1]; n++) { + // get idx argmax_idx = int(Utility::argmax( &predict_batch[(m * predict_shape[1] + n) * predict_shape[2]], &predict_batch[(m * predict_shape[1] + n + 1) * predict_shape[2]])); + // get score max_value = float(*std::max_element( &predict_batch[(m * predict_shape[1] + n) * predict_shape[2]], &predict_batch[(m * predict_shape[1] + n + 1) * predict_shape[2]])); @@ -132,7 +134,9 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) { paddle_infer::Config config; config.SetModel(model_dir + "/inference.pdmodel", model_dir + "/inference.pdiparams"); - + std::cout << "In PP-OCRv3, default rec_img_h is 48," + << "if you use other model, you should set the param rec_img_h=32" + << std::endl; if (this->use_gpu_) { config.EnableUseGpu(this->gpu_mem_, this->gpu_id_); if (this->use_tensorrt_) { diff --git a/deploy/pdserving/README.md b/deploy/pdserving/README.md index 55e03c4c2654f336ed942ae03e61e88b61940006..83329a11cdb57fea003a800fe9ca73791da9f6da 100644 --- a/deploy/pdserving/README.md +++ b/deploy/pdserving/README.md @@ -136,7 +136,7 @@ The recognition model is the same. 2. Run the following command to start the service. ``` # Start the service and save the running log in log.txt - python3 web_service.py &>log.txt & + python3 web_service.py --config=config.yml &>log.txt & ``` After the service is successfully started, a log similar to the following will be printed in log.txt ![](./imgs/start_server.png) @@ -217,7 +217,7 @@ The C++ service deployment is the same as python in the environment setup and da 2. Run the following command to start the service. ``` # Start the service and save the running log in log.txt - python3 -m paddle_serving_server.serve --model ppocr_det_v3_serving ppocr_rec_v3_serving --op GeneralDetectionOp GeneralInferOp --port 9293 &>log.txt & + python3 -m paddle_serving_server.serve --model ppocr_det_v3_serving ppocr_rec_v3_serving --op GeneralDetectionOp GeneralInferOp --port 8181 &>log.txt & ``` After the service is successfully started, a log similar to the following will be printed in log.txt ![](./imgs/start_server.png) diff --git a/deploy/pdserving/README_CN.md b/deploy/pdserving/README_CN.md index 0891611db5f39d322473354f7d988b10afa78cbd..ab05b766e32bc8435d2c0568e848190bf6761173 100644 --- a/deploy/pdserving/README_CN.md +++ b/deploy/pdserving/README_CN.md @@ -135,7 +135,7 @@ python3 -m paddle_serving_client.convert --dirname ./ch_PP-OCRv3_rec_infer/ \ 2. 启动服务可运行如下命令: ``` # 启动服务,运行日志保存在log.txt - python3 web_service.py &>log.txt & + python3 web_service.py --config=config.yml &>log.txt & ``` 成功启动服务后,log.txt中会打印类似如下日志 ![](./imgs/start_server.png) @@ -230,7 +230,7 @@ cp -rf general_detection_op.cpp Serving/core/general-server/op ``` # 启动服务,运行日志保存在log.txt - python3 -m paddle_serving_server.serve --model ppocr_det_v3_serving ppocr_rec_v3_serving --op GeneralDetectionOp GeneralInferOp --port 9293 &>log.txt & + python3 -m paddle_serving_server.serve --model ppocr_det_v3_serving ppocr_rec_v3_serving --op GeneralDetectionOp GeneralInferOp --port 8181 &>log.txt & ``` 成功启动服务后,log.txt中会打印类似如下日志 ![](./imgs/start_server.png) diff --git a/deploy/pdserving/ocr_cpp_client.py b/deploy/pdserving/ocr_cpp_client.py index 7f9333dd858aad5440ff256d501cf1e5d2f5fb1f..3aaf03155953ce2129fd548deef15033e91e9a09 100755 --- a/deploy/pdserving/ocr_cpp_client.py +++ b/deploy/pdserving/ocr_cpp_client.py @@ -22,15 +22,16 @@ import cv2 from paddle_serving_app.reader import Sequential, URL2Image, ResizeByFactor from paddle_serving_app.reader import Div, Normalize, Transpose from ocr_reader import OCRReader +import codecs client = Client() # TODO:load_client need to load more than one client model. # this need to figure out some details. client.load_client_config(sys.argv[1:]) -client.connect(["127.0.0.1:9293"]) +client.connect(["127.0.0.1:8181"]) import paddle -test_img_dir = "../../doc/imgs/" +test_img_dir = "../../doc/imgs/1.jpg" ocr_reader = OCRReader(char_dict_path="../../ppocr/utils/ppocr_keys_v1.txt") @@ -40,14 +41,43 @@ def cv2_to_base64(image): 'utf8') #data.tostring()).decode('utf8') -for img_file in os.listdir(test_img_dir): - with open(os.path.join(test_img_dir, img_file), 'rb') as file: +def _check_image_file(path): + img_end = {'jpg', 'bmp', 'png', 'jpeg', 'rgb', 'tif', 'tiff', 'gif'} + return any([path.lower().endswith(e) for e in img_end]) + + +test_img_list = [] +if os.path.isfile(test_img_dir) and _check_image_file(test_img_dir): + test_img_list.append(test_img_dir) +elif os.path.isdir(test_img_dir): + for single_file in os.listdir(test_img_dir): + file_path = os.path.join(test_img_dir, single_file) + if os.path.isfile(file_path) and _check_image_file(file_path): + test_img_list.append(file_path) +if len(test_img_list) == 0: + raise Exception("not found any img file in {}".format(test_img_dir)) + +for img_file in test_img_list: + with open(img_file, 'rb') as file: image_data = file.read() image = cv2_to_base64(image_data) res_list = [] fetch_map = client.predict(feed={"x": image}, fetch=[], batch=True) - one_batch_res = ocr_reader.postprocess(fetch_map, with_score=True) - for res in one_batch_res: - res_list.append(res[0]) - res = {"res": str(res_list)} - print(res) + if fetch_map is None: + print('no results') + else: + if "text" in fetch_map: + for x in fetch_map["text"]: + x = codecs.encode(x) + words = base64.b64decode(x).decode('utf-8') + res_list.append(words) + else: + try: + one_batch_res = ocr_reader.postprocess( + fetch_map, with_score=True) + for res in one_batch_res: + res_list.append(res[0]) + except: + print('no results') + res = {"res": str(res_list)} + print(res) diff --git a/deploy/pdserving/ocr_reader.py b/deploy/pdserving/ocr_reader.py index 75f0f3d5c3aea488f82ec01a72e20310663d565b..d488cc0920391eded6c08945597b5c938b7c7a42 100644 --- a/deploy/pdserving/ocr_reader.py +++ b/deploy/pdserving/ocr_reader.py @@ -339,7 +339,7 @@ class CharacterOps(object): class OCRReader(object): def __init__(self, algorithm="CRNN", - image_shape=[3, 32, 320], + image_shape=[3, 48, 320], char_type="ch", batch_num=1, char_dict_path="./ppocr_keys_v1.txt"): @@ -356,7 +356,7 @@ class OCRReader(object): def resize_norm_img(self, img, max_wh_ratio): imgC, imgH, imgW = self.rec_image_shape if self.character_type == "ch": - imgW = int(32 * max_wh_ratio) + imgW = int(imgH * max_wh_ratio) h = img.shape[0] w = img.shape[1] ratio = w / float(h) @@ -377,7 +377,7 @@ class OCRReader(object): def preprocess(self, img_list): img_num = len(img_list) norm_img_batch = [] - max_wh_ratio = 0 + max_wh_ratio = 320/48. for ino in range(img_num): h, w = img_list[ino].shape[0:2] wh_ratio = w * 1.0 / h diff --git a/deploy/pdserving/pipeline_http_client.py b/deploy/pdserving/pipeline_http_client.py index a1226a9469cc96090603f57f5e44f9dad1d64b5f..0a86a6398701ef6715afdd9643cb9cb8ccbb58b2 100644 --- a/deploy/pdserving/pipeline_http_client.py +++ b/deploy/pdserving/pipeline_http_client.py @@ -36,11 +36,27 @@ def cv2_to_base64(image): return base64.b64encode(image).decode('utf8') +def _check_image_file(path): + img_end = {'jpg', 'bmp', 'png', 'jpeg', 'rgb', 'tif', 'tiff', 'gif'} + return any([path.lower().endswith(e) for e in img_end]) + + url = "http://127.0.0.1:9998/ocr/prediction" test_img_dir = args.image_dir -for idx, img_file in enumerate(os.listdir(test_img_dir)): - with open(os.path.join(test_img_dir, img_file), 'rb') as file: +test_img_list = [] +if os.path.isfile(test_img_dir) and _check_image_file(test_img_dir): + test_img_list.append(test_img_dir) +elif os.path.isdir(test_img_dir): + for single_file in os.listdir(test_img_dir): + file_path = os.path.join(test_img_dir, single_file) + if os.path.isfile(file_path) and _check_image_file(file_path): + test_img_list.append(file_path) +if len(test_img_list) == 0: + raise Exception("not found any img file in {}".format(test_img_dir)) + +for idx, img_file in enumerate(test_img_list): + with open(img_file, 'rb') as file: image_data1 = file.read() # print file name print('{}{}{}'.format('*' * 10, img_file, '*' * 10)) @@ -70,4 +86,4 @@ for idx, img_file in enumerate(os.listdir(test_img_dir)): print( "For details about error message, see PipelineServingLogs/pipeline.log" ) -print("==> total number of test imgs: ", len(os.listdir(test_img_dir))) +print("==> total number of test imgs: ", len(test_img_list)) diff --git a/deploy/pdserving/serving_client_conf.prototxt b/deploy/pdserving/serving_client_conf.prototxt new file mode 100644 index 0000000000000000000000000000000000000000..33960540a2ea1a7a1e37bda07ab62197a54e272d --- /dev/null +++ b/deploy/pdserving/serving_client_conf.prototxt @@ -0,0 +1,16 @@ +feed_var { + name: "x" + alias_name: "x" + is_lod_tensor: false + feed_type: 20 + shape: 1 +} +fetch_var { + name: "save_infer_model/scale_0.tmp_1" + alias_name: "save_infer_model/scale_0.tmp_1" + is_lod_tensor: false + fetch_type: 1 + shape: 1 + shape: 640 + shape: 640 +} diff --git a/deploy/pdserving/web_service.py b/deploy/pdserving/web_service.py index f05806ce030238144568a3ca137798a9132027e4..b6fadb91d59d6a27c6ba8ba80459f5acc6aa3516 100644 --- a/deploy/pdserving/web_service.py +++ b/deploy/pdserving/web_service.py @@ -19,7 +19,7 @@ import copy import cv2 import base64 # from paddle_serving_app.reader import OCRReader -from ocr_reader import OCRReader, DetResizeForTest +from ocr_reader import OCRReader, DetResizeForTest, ArgsParser from paddle_serving_app.reader import Sequential, ResizeByFactor from paddle_serving_app.reader import Div, Normalize, Transpose from paddle_serving_app.reader import DBPostProcess, FilterBoxes, GetRotateCropImage, SortedBoxes @@ -63,7 +63,6 @@ class DetOp(Op): dt_boxes_list = self.post_func(det_out, [ratio_list]) dt_boxes = self.filter_func(dt_boxes_list[0], [self.ori_h, self.ori_w]) out_dict = {"dt_boxes": dt_boxes, "image": self.raw_im} - return out_dict, None, "" @@ -86,7 +85,7 @@ class RecOp(Op): dt_boxes = copy.deepcopy(self.dt_list) feed_list = [] img_list = [] - max_wh_ratio = 0 + max_wh_ratio = 320 / 48. ## Many mini-batchs, the type of feed_data is list. max_batch_size = 6 # len(dt_boxes) @@ -150,7 +149,8 @@ class RecOp(Op): for i in range(dt_num): text = rec_list[i] dt_box = self.dt_list[i] - result_list.append([text, dt_box.tolist()]) + if text[1] >= 0.5: + result_list.append([text, dt_box.tolist()]) res = {"result": str(result_list)} return res, None, "" @@ -163,5 +163,6 @@ class OcrService(WebService): uci_service = OcrService(name="ocr") -uci_service.prepare_pipeline_config("config.yml") +FLAGS = ArgsParser().parse_args() +uci_service.prepare_pipeline_config(yml_dict=FLAGS.conf_dict) uci_service.run_service() diff --git a/doc/doc_ch/FAQ.md b/doc/doc_ch/FAQ.md index 24f8a3e92be1c003ec7c37b74d14f4ae4117086a..a4437b8b783ca28fed60bb0a9648191e7ec4d0db 100644 --- a/doc/doc_ch/FAQ.md +++ b/doc/doc_ch/FAQ.md @@ -682,7 +682,7 @@ lr: #### Q: 关于dygraph分支中,文本识别模型训练,要使用数据增强应该如何设置? -**A**:可以参考[配置文件](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml)在Train['dataset']['transforms']添加RecAug字段,使数据增强生效。可以通过添加对aug_prob设置,表示每种数据增强采用的概率。aug_prob默认是0.4.由于tia数据增强特殊性,默认不采用,可以通过添加use_tia设置,使tia数据增强生效。详细设置可以参考[ISSUE 1744](https://github.com/PaddlePaddle/PaddleOCR/issues/1744)。 +**A**:可以参考[配置文件](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml)在Train['dataset']['transforms']添加RecAug字段,使数据增强生效。可以通过添加对aug_prob设置,表示每种数据增强采用的概率。aug_prob默认是0.4。详细设置可以参考[ISSUE 1744](https://github.com/PaddlePaddle/PaddleOCR/issues/1744)。 #### Q: 训练过程中,训练程序意外退出/挂起,应该如何解决? @@ -720,6 +720,13 @@ C++TensorRT预测需要使用支持TRT的预测库并在编译时打开[-DWITH_T 注:建议使用TensorRT大于等于6.1.0.5以上的版本。 +#### Q: 为什么识别模型做预测的时候,预测图片的数量数量还会影响预测的精度 +**A**: 推理时识别模型默认的batch_size=6, 如预测图片长度变化大,可能影响预测效果。如果出现上述问题可在推理的时候设置识别bs=1,命令如下: + +``` +python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/ch/word_4.jpg" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --rec_batch_num=1 +``` + ### 2.13 推理部署 diff --git a/doc/doc_ch/dataset/layout_datasets.md b/doc/doc_ch/dataset/layout_datasets.md index e7055b4e607aae358a9ec1e93f3640b2b68ea4a1..728a9be5fdd33a78482adb1e705afea7117a3037 100644 --- a/doc/doc_ch/dataset/layout_datasets.md +++ b/doc/doc_ch/dataset/layout_datasets.md @@ -15,8 +15,8 @@ - **数据简介**:publaynet数据集的训练集合中包含35万张图像,验证集合中包含1.1万张图像。总共包含5个类别,分别是: `text, title, list, table, figure`。部分图像以及标注框可视化如下所示。
- - + +
- **下载地址**:https://developer.ibm.com/exchanges/data/all/publaynet/ @@ -30,8 +30,8 @@ - **数据简介**:CDLA据集的训练集合中包含5000张图像,验证集合中包含1000张图像。总共包含10个类别,分别是: `Text, Title, Figure, Figure caption, Table, Table caption, Header, Footer, Reference, Equation`。部分图像以及标注框可视化如下所示。
- - + +
- **下载地址**:https://github.com/buptlihang/CDLA @@ -45,8 +45,8 @@ - **数据简介**:TableBank数据集包含Latex(训练集187199张,验证集7265张,测试集5719张)与Word(训练集73383张,验证集2735张,测试集2281张)两种类别的文档。仅包含`Table` 1个类别。部分图像以及标注框可视化如下所示。
- - + +
- **下载地址**:https://doc-analysis.github.io/tablebank-page/index.html diff --git a/doc/doc_ch/detection.md b/doc/doc_ch/detection.md index 8a71b75c249b794e7ecda0ad14dc8cd2f07447e0..2cf0732219ac9cd2309ae24896d7de1499986461 100644 --- a/doc/doc_ch/detection.md +++ b/doc/doc_ch/detection.md @@ -13,6 +13,7 @@ - [2.5 分布式训练](#25-分布式训练) - [2.6 知识蒸馏训练](#26-知识蒸馏训练) - [2.7 其他训练环境](#27-其他训练环境) + - [2.8 模型微调](#28-模型微调) - [3. 模型评估与预测](#3-模型评估与预测) - [3.1 指标评估](#31-指标评估) - [3.2 测试检测效果](#32-测试检测效果) @@ -141,7 +142,8 @@ python3 tools/train.py -c configs/det/det_mv3_db.yml \ Global.use_amp=True Global.scale_loss=1024.0 Global.use_dynamic_loss_scaling=True ``` - + + ## 2.5 分布式训练 多机多卡训练时,通过 `--ips` 参数设置使用的机器IP地址,通过 `--gpus` 参数设置使用的GPU ID: @@ -151,7 +153,7 @@ python3 -m paddle.distributed.launch --ips="xx.xx.xx.xx,xx.xx.xx.xx" --gpus '0,1 -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained ``` -**注意:** 采用多机多卡训练时,需要替换上面命令中的ips值为您机器的地址,机器之间需要能够相互ping通。另外,训练时需要在多个机器上分别启动命令。查看机器ip地址的命令为`ifconfig`。 +**注意:** (1)采用多机多卡训练时,需要替换上面命令中的ips值为您机器的地址,机器之间需要能够相互ping通;(2)训练时需要在多个机器上分别启动命令。查看机器ip地址的命令为`ifconfig`;(3)更多关于分布式训练的性能优势等信息,请参考:[分布式训练教程](./distributed_training.md)。 @@ -177,6 +179,13 @@ Windows平台只支持`单卡`的训练与预测,指定GPU进行训练`set CUD - Linux DCU DCU设备上运行需要设置环境变量 `export HIP_VISIBLE_DEVICES=0,1,2,3`,其余训练评估预测命令与Linux GPU完全相同。 + + +## 2.8 模型微调 + +实际使用过程中,建议加载官方提供的预训练模型,在自己的数据集中进行微调,关于检测模型的微调方法,请参考:[模型微调教程](./finetune.md)。 + + # 3. 模型评估与预测 @@ -196,6 +205,7 @@ python3 tools/eval.py -c configs/det/det_mv3_db.yml -o Global.checkpoints="{pat ## 3.2 测试检测效果 测试单张图像的检测效果: + ```shell python3 tools/infer_det.py -c configs/det/det_mv3_db.yml -o Global.infer_img="./doc/imgs_en/img_10.jpg" Global.pretrained_model="./output/det_db/best_accuracy" ``` @@ -226,14 +236,19 @@ python3 tools/export_model.py -c configs/det/det_mv3_db.yml -o Global.pretrained ``` DB检测模型inference 模型预测: + ```shell python3 tools/infer/predict_det.py --det_algorithm="DB" --det_model_dir="./output/det_db_inference/" --image_dir="./doc/imgs/" --use_gpu=True ``` 如果是其他检测,比如EAST模型,det_algorithm参数需要修改为EAST,默认为DB算法: + ```shell python3 tools/infer/predict_det.py --det_algorithm="EAST" --det_model_dir="./output/det_db_inference/" --image_dir="./doc/imgs/" --use_gpu=True ``` +更多关于推理超参数的配置与解释,请参考:[模型推理超参数解释教程](./inference_args.md)。 + + # 5. FAQ diff --git a/doc/doc_ch/distributed_training.md b/doc/doc_ch/distributed_training.md index e0251b21ea1157084e4e1b1d77429264d452aa20..6afa4a5b9f77ce238cb18fcb4160e49f7b465369 100644 --- a/doc/doc_ch/distributed_training.md +++ b/doc/doc_ch/distributed_training.md @@ -41,11 +41,16 @@ python3 -m paddle.distributed.launch \ ## 性能效果测试 -* 基于单机8卡P40,和2机8卡P40,在26W公开识别数据集(LSVT, RCTW, MTWI)上进行训练,最终耗时如下。 +* 在2机8卡P40的机器上,基于26W公开识别数据集(LSVT, RCTW, MTWI)上进行训练,最终耗时如下。 -| 模型 | 配置文件 | 机器数量 | 每台机器的GPU数量 | 训练时间 | 识别Acc | 加速比 | -| :----------------------: | :------------: | :------------: | :---------------: | :----------: | :-----------: | :-----------: | -| CRNN | configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml | 1 | 8 | 60h | 66.7% | - | -| CRNN | configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml | 2 | 8 | 40h | 67.0% | 150% | +| 模型 | 配置 | 精度 | 单机8卡耗时 | 2机8卡耗时 | 加速比 | +|------|-----|--------|--------|--------|-----| +| CRNN | [rec_chinese_lite_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml) | 67.0% | 2.50d | 1.67d | **1.5** | -可以看出,精度没有下降的情况下,训练时间由60h缩短为了40h,加速比可以达到60h/40h=150%,效率为60h/(40h*2)=75%。 + +* 在4机8卡V100的机器上,基于全量数据训练,最终耗时如下 + + +| 模型 | 配置 | 精度 | 单机8卡耗时 | 4机8卡耗时 | 加速比 | +|------|-----|--------|--------|--------|-----| +| SVTR | [ch_PP-OCRv3_rec_distillation.yml](../../configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml) | 74.0% | 10d | 2.84d | **3.5** | diff --git a/doc/doc_ch/inference_args.md b/doc/doc_ch/inference_args.md new file mode 100644 index 0000000000000000000000000000000000000000..fa188ab7c800eaabae8a4ff54413af162dd60e43 --- /dev/null +++ b/doc/doc_ch/inference_args.md @@ -0,0 +1,120 @@ +# PaddleOCR模型推理参数解释 + +在使用PaddleOCR进行模型推理时,可以自定义修改参数,来修改模型、数据、预处理、后处理等内容(参数文件:[utility.py](../../tools/infer/utility.py)),详细的参数解释如下所示。 + +* 全局信息 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| image_dir | str | 无,必须显式指定 | 图像或者文件夹路径 | +| vis_font_path | str | "./doc/fonts/simfang.ttf" | 用于可视化的字体路径 | +| drop_score | float | 0.5 | 识别得分小于该值的结果会被丢弃,不会作为返回结果 | +| use_pdserving | bool | False | 是否使用Paddle Serving进行预测 | +| warmup | bool | False | 是否开启warmup,在统计预测耗时的时候,可以使用这种方法 | +| draw_img_save_dir | str | "./inference_results" | 系统串联预测OCR结果的保存文件夹 | +| save_crop_res | bool | False | 是否保存OCR的识别文本图像 | +| crop_res_save_dir | str | "./output" | 保存OCR识别出来的文本图像路径 | +| use_mp | bool | False | 是否开启多进程预测 | +| total_process_num | int | 6 | 开启的进城数,`use_mp`为`True`时生效 | +| process_id | int | 0 | 当前进程的id号,无需自己修改 | +| benchmark | bool | False | 是否开启benchmark,对预测速度、显存占用等进行统计 | +| save_log_path | str | "./log_output/" | 开启`benchmark`时,日志结果的保存文件夹 | +| show_log | bool | True | 是否显示预测中的日志信息 | +| use_onnx | bool | False | 是否开启onnx预测 | + + +* 预测引擎相关 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| use_gpu | bool | True | 是否使用GPU进行预测 | +| ir_optim | bool | True | 是否对计算图进行分析与优化,开启后可以加速预测过程 | +| use_tensorrt | bool | False | 是否开启tensorrt | +| min_subgraph_size | int | 15 | tensorrt中最小子图size,当子图的size大于该值时,才会尝试对该子图使用trt engine计算 | +| precision | str | fp32 | 预测的精度,支持`fp32`, `fp16`, `int8` 3种输入 | +| enable_mkldnn | bool | True | 是否开启mkldnn | +| cpu_threads | int | 10 | 开启mkldnn时,cpu预测的线程数 | + +* 文本检测模型相关 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| det_algorithm | str | "DB" | 文本检测算法名称,目前支持`DB`, `EAST`, `SAST`, `PSE` | +| det_model_dir | str | xx | 检测inference模型路径 | +| det_limit_side_len | int | 960 | 检测的图像边长限制 | +| det_limit_type | str | "max" | 检测的变成限制类型,目前支持`min`, `max`,`min`表示保证图像最短边不小于`det_limit_side_len`,`max`表示保证图像最长边不大于`det_limit_side_len` | + +其中,DB算法相关参数如下 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| det_db_thresh | float | 0.3 | DB输出的概率图中,得分大于该阈值的像素点才会被认为是文字像素点 | +| det_db_box_thresh | float | 0.6 | 检测结果边框内,所有像素点的平均得分大于该阈值时,该结果会被认为是文字区域 | +| det_db_unclip_ratio | float | 1.5 | `Vatti clipping`算法的扩张系数,使用该方法对文字区域进行扩张 | +| max_batch_size | int | 10 | 预测的batch size | +| use_dilation | bool | False | 是否对分割结果进行膨胀以获取更优检测效果 | +| det_db_score_mode | str | "fast" | DB的检测结果得分计算方法,支持`fast`和`slow`,`fast`是根据polygon的外接矩形边框内的所有像素计算平均得分,`slow`是根据原始polygon内的所有像素计算平均得分,计算速度相对较慢一些,但是更加准确一些。 | + +EAST算法相关参数如下 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| det_east_score_thresh | float | 0.8 | EAST后处理中score map的阈值 | +| det_east_cover_thresh | float | 0.1 | EAST后处理中文本框的平均得分阈值 | +| det_east_nms_thresh | float | 0.2 | EAST后处理中nms的阈值 | + +SAST算法相关参数如下 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| det_sast_score_thresh | float | 0.5 | SAST后处理中的得分阈值 | +| det_sast_nms_thresh | float | 0.5 | SAST后处理中nms的阈值 | +| det_sast_polygon | bool | False | 是否多边形检测,弯曲文本场景(如Total-Text)设置为True | + +PSE算法相关参数如下 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| det_pse_thresh | float | 0.0 | 对输出图做二值化的阈值 | +| det_pse_box_thresh | float | 0.85 | 对box进行过滤的阈值,低于此阈值的丢弃 | +| det_pse_min_area | float | 16 | box的最小面积,低于此阈值的丢弃 | +| det_pse_box_type | str | "box" | 返回框的类型,box:四点坐标,poly: 弯曲文本的所有点坐标 | +| det_pse_scale | int | 1 | 输入图像相对于进后处理的图的比例,如`640*640`的图像,网络输出为`160*160`,scale为2的情况下,进后处理的图片shape为`320*320`。这个值调大可以加快后处理速度,但是会带来精度的下降 | + +* 文本识别模型相关 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| rec_algorithm | str | "CRNN" | 文本识别算法名称,目前支持`CRNN`, `SRN`, `RARE`, `NETR`, `SAR` | +| rec_model_dir | str | 无,如果使用识别模型,该项是必填项 | 识别inference模型路径 | +| rec_image_shape | list | [3, 32, 320] | 识别时的图像尺寸, | +| rec_batch_num | int | 6 | 识别的batch size | +| max_text_length | int | 25 | 识别结果最大长度,在`SRN`中有效 | +| rec_char_dict_path | str | "./ppocr/utils/ppocr_keys_v1.txt" | 识别的字符字典文件 | +| use_space_char | bool | True | 是否包含空格,如果为`True`,则会在最后字符字典中补充`空格`字符 | + + +* 端到端文本检测与识别模型相关 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| e2e_algorithm | str | "PGNet" | 端到端算法名称,目前支持`PGNet` | +| e2e_model_dir | str | 无,如果使用端到端模型,该项是必填项 | 端到端模型inference模型路径 | +| e2e_limit_side_len | int | 768 | 端到端的输入图像边长限制 | +| e2e_limit_type | str | "max" | 端到端的边长限制类型,目前支持`min`, `max`,`min`表示保证图像最短边不小于`e2e_limit_side_len`,`max`表示保证图像最长边不大于`e2e_limit_side_len` | +| e2e_pgnet_score_thresh | float | 0.5 | 端到端得分阈值,小于该阈值的结果会被丢弃 | +| e2e_char_dict_path | str | "./ppocr/utils/ic15_dict.txt" | 识别的字典文件路径 | +| e2e_pgnet_valid_set | str | "totaltext" | 验证集名称,目前支持`totaltext`, `partvgg`,不同数据集对应的后处理方式不同,与训练过程保持一致即可 | +| e2e_pgnet_mode | str | "fast" | PGNet的检测结果得分计算方法,支持`fast`和`slow`,`fast`是根据polygon的外接矩形边框内的所有像素计算平均得分,`slow`是根据原始polygon内的所有像素计算平均得分,计算速度相对较慢一些,但是更加准确一些。 | + + +* 方向分类器模型相关 + +| 参数名称 | 类型 | 默认值 | 含义 | +| :--: | :--: | :--: | :--: | +| use_angle_cls | bool | False | 是否使用方向分类器 | +| cls_model_dir | str | 无,如果需要使用,则必须显式指定路径 | 方向分类器inference模型路径 | +| cls_image_shape | list | [3, 48, 192] | 预测尺度 | +| label_list | list | ['0', '180'] | class id对应的角度值 | +| cls_batch_num | int | 6 | 方向分类器预测的batch size | +| cls_thresh | float | 0.9 | 预测阈值,模型预测结果为180度,且得分大于该阈值时,认为最终预测结果为180度,需要翻转 | diff --git a/doc/doc_ch/ppocr_introduction.md b/doc/doc_ch/ppocr_introduction.md index 59de124e2ab855d0b4abb90d0a356aefd6db586d..bd62087c8b212098cba6b0ee1cbaf413ab23015f 100644 --- a/doc/doc_ch/ppocr_introduction.md +++ b/doc/doc_ch/ppocr_introduction.md @@ -30,11 +30,11 @@ PP-OCR系统pipeline如下: PP-OCR系统在持续迭代优化,目前已发布PP-OCR和PP-OCRv2两个版本: -PP-OCR从骨干网络选择和调整、预测头部的设计、数据增强、学习率变换策略、正则化参数选择、预训练模型使用以及模型自动裁剪量化8个方面,采用19个有效策略,对各个模块的模型进行效果调优和瘦身(如绿框所示),最终得到整体大小为3.5M的超轻量中英文OCR和2.8M的英文数字OCR。更多细节请参考PP-OCR技术方案 https://arxiv.org/abs/2009.09941 +PP-OCR从骨干网络选择和调整、预测头部的设计、数据增强、学习率变换策略、正则化参数选择、预训练模型使用以及模型自动裁剪量化8个方面,采用19个有效策略,对各个模块的模型进行效果调优和瘦身(如绿框所示),最终得到整体大小为3.5M的超轻量中英文OCR和2.8M的英文数字OCR。更多细节请参考[PP-OCR技术报告](https://arxiv.org/abs/2009.09941)。 #### PP-OCRv2 -PP-OCRv2在PP-OCR的基础上,进一步在5个方面重点优化,检测模型采用CML协同互学习知识蒸馏策略和CopyPaste数据增广策略;识别模型采用LCNet轻量级骨干网络、UDML 改进知识蒸馏策略和[Enhanced CTC loss](./enhanced_ctc_loss.md)损失函数改进(如上图红框所示),进一步在推理速度和预测效果上取得明显提升。更多细节请参考PP-OCRv2[技术报告](https://arxiv.org/abs/2109.03144)。 +PP-OCRv2在PP-OCR的基础上,进一步在5个方面重点优化,检测模型采用CML协同互学习知识蒸馏策略和CopyPaste数据增广策略;识别模型采用LCNet轻量级骨干网络、UDML 改进知识蒸馏策略和[Enhanced CTC loss](./enhanced_ctc_loss.md)损失函数改进(如上图红框所示),进一步在推理速度和预测效果上取得明显提升。更多细节请参考[PP-OCRv2技术报告](https://arxiv.org/abs/2109.03144)。 #### PP-OCRv3 @@ -48,7 +48,7 @@ PP-OCRv3系统pipeline如下: -更多细节请参考PP-OCRv3[技术报告](./PP-OCRv3_introduction.md)。 +更多细节请参考[PP-OCRv3技术报告](https://arxiv.org/abs/2206.03001v2) 👉[中文简洁版](./PP-OCRv3_introduction.md) diff --git a/doc/doc_ch/quickstart.md b/doc/doc_ch/quickstart.md index 29ca48fa838be4a60f08d31d5031180b951e33bc..e425cdd8a87d320554e61c72e05001875d022e43 100644 --- a/doc/doc_ch/quickstart.md +++ b/doc/doc_ch/quickstart.md @@ -101,8 +101,17 @@ cd /path/to/ppocr_img ['韩国小馆', 0.994467] ``` +**版本说明** +paddleocr默认使用PP-OCRv3模型(`--ocr_version PP-OCRv3`),如需使用其他版本可通过设置参数`--ocr_version`,具体版本说明如下: +| 版本名称 | 版本说明 | +| --- | --- | +| PP-OCRv3 | 支持中、英文检测和识别,方向分类器,支持多语种识别 | +| PP-OCRv2 | 支持中英文的检测和识别,方向分类器,多语言暂未更新 | +| PP-OCR | 支持中、英文检测和识别,方向分类器,支持多语种识别 | -如需使用2.0模型,请指定参数`--ocr_version PP-OCR`,paddleocr默认使用PP-OCRv3模型(`--ocr_version PP-OCRv3`)。更多whl包使用可参考[whl包文档](./whl.md) +如需新增自己训练的模型,可以在[paddleocr](../../paddleocr.py)中增加模型链接和字段,重新编译即可。 + +更多whl包使用可参考[whl包文档](./whl.md) diff --git a/doc/doc_ch/recognition.md b/doc/doc_ch/recognition.md index 8457df69ff4c09b196b0f0f91271a92344217d75..acf09f7bdecf41adfeee26efde6afaff8db7a41e 100644 --- a/doc/doc_ch/recognition.md +++ b/doc/doc_ch/recognition.md @@ -18,6 +18,7 @@ - [2.6. 知识蒸馏训练](#26-知识蒸馏训练) - [2.7. 多语言模型训练](#27-多语言模型训练) - [2.8. 其他训练环境](#28-其他训练环境) + - [2.9. 模型微调](#29-模型微调) - [3. 模型评估与预测](#3-模型评估与预测) - [3.1. 指标评估](#31-指标评估) - [3.2. 测试识别效果](#32-测试识别效果) @@ -217,6 +218,30 @@ python3 tools/train.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pre python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/train.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pretrained_model=./pretrain_models/en_PP-OCRv3_rec_train/best_accuracy ``` +正常启动训练后,会看到以下log输出: + +``` +[2022/02/22 07:58:05] root INFO: epoch: [1/800], iter: 10, lr: 0.000000, loss: 0.754281, acc: 0.000000, norm_edit_dis: 0.000008, reader_cost: 0.55541 s, batch_cost: 0.91654 s, samples: 1408, ips: 153.62133 +[2022/02/22 07:58:13] root INFO: epoch: [1/800], iter: 20, lr: 0.000001, loss: 0.924677, acc: 0.000000, norm_edit_dis: 0.000008, reader_cost: 0.00236 s, batch_cost: 0.28528 s, samples: 1280, ips: 448.68599 +[2022/02/22 07:58:23] root INFO: epoch: [1/800], iter: 30, lr: 0.000002, loss: 0.967231, acc: 0.000000, norm_edit_dis: 0.000008, reader_cost: 0.14527 s, batch_cost: 0.42714 s, samples: 1280, ips: 299.66507 +[2022/02/22 07:58:31] root INFO: epoch: [1/800], iter: 40, lr: 0.000003, loss: 0.895318, acc: 0.000000, norm_edit_dis: 0.000008, reader_cost: 0.00173 s, batch_cost: 0.27719 s, samples: 1280, ips: 461.77252 +``` + +log 中自动打印如下信息: + +| 字段 | 含义 | +| :----: | :------: | +| epoch | 当前迭代轮次 | +| iter | 当前迭代次数 | +| lr | 当前学习率 | +| loss | 当前损失函数 | +| acc | 当前batch的准确率 | +| norm_edit_dis | 当前 batch 的编辑距离 | +| reader_cost | 当前 batch 数据处理耗时 | +| batch_cost | 当前 batch 总耗时 | +| samples | 当前 batch 内的样本数 | +| ips | 每秒处理图片的数量 | + PaddleOCR支持训练和评估交替进行, 可以在 `configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml` 中修改 `eval_batch_step` 设置评估频率,默认每500个iter评估一次。评估过程中默认将最佳acc模型,保存为 `output/en_PP-OCRv3_rec/best_accuracy` 。 @@ -363,7 +388,7 @@ python3 -m paddle.distributed.launch --ips="xx.xx.xx.xx,xx.xx.xx.xx" --gpus '0,1 -o Global.pretrained_model=./pretrain_models/en_PP-OCRv3_rec_train/best_accuracy ``` -**注意:** 采用多机多卡训练时,需要替换上面命令中的ips值为您机器的地址,机器之间需要能够相互ping通。另外,训练时需要在多个机器上分别启动命令。查看机器ip地址的命令为`ifconfig`。 +**注意:** (1)采用多机多卡训练时,需要替换上面命令中的ips值为您机器的地址,机器之间需要能够相互ping通;(2)训练时需要在多个机器上分别启动命令。查看机器ip地址的命令为`ifconfig`;(3)更多关于分布式训练的性能优势等信息,请参考:[分布式训练教程](./distributed_training.md)。 ## 2.6. 知识蒸馏训练 @@ -438,6 +463,11 @@ Windows平台只支持`单卡`的训练与预测,指定GPU进行训练`set CUD - Linux DCU DCU设备上运行需要设置环境变量 `export HIP_VISIBLE_DEVICES=0,1,2,3`,其余训练评估预测命令与Linux GPU完全相同。 +## 2.9 模型微调 + +实际使用过程中,建议加载官方提供的预训练模型,在自己的数据集中进行微调,关于识别模型的微调方法,请参考:[模型微调教程](./finetune.md)。 + + # 3. 模型评估与预测 ## 3.1. 指标评估 @@ -540,12 +570,13 @@ inference/en_PP-OCRv3_rec/ - 自定义模型推理 - 如果训练时修改了文本的字典,在使用inference模型预测时,需要通过`--rec_char_dict_path`指定使用的字典路径 + 如果训练时修改了文本的字典,在使用inference模型预测时,需要通过`--rec_char_dict_path`指定使用的字典路径,更多关于推理超参数的配置与解释,请参考:[模型推理超参数解释教程](./inference_args.md)。 ``` python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./your inference model" --rec_image_shape="3, 48, 320" --rec_char_dict_path="your text dict path" ``` + # 5. FAQ Q1: 训练模型转inference 模型之后预测效果不一致? diff --git a/doc/doc_en/PP-OCRv3_introduction_en.md b/doc/doc_en/PP-OCRv3_introduction_en.md index 07894340c2de9fe2fe2d677167439ec581aa43e8..481e0b8174b1e5ebce84eb1745c49dccd2c565f5 100644 --- a/doc/doc_en/PP-OCRv3_introduction_en.md +++ b/doc/doc_en/PP-OCRv3_introduction_en.md @@ -76,7 +76,7 @@ LK-PAN (Large Kernel PAN) is a lightweight [PAN](https://arxiv.org/pdf/1803.0153 **(2) DML: Deep Mutual Learning Strategy for Teacher Model** -[DML](https://arxiv.org/abs/1706.00384)(Collaborative Mutual Learning), as shown in the figure below, can effectively improve the accuracy of the text detection model by learning from each other with two models with the same structure. The DML strategy is adopted in the teacher model training, and the hmean is increased from 85% to 86%. By updating the teacher model of CML in PP-OCRv2 to the above-mentioned higher-precision one, the hmean of the student model can be further improved from 83.2% to 84.3%. +[DML](https://arxiv.org/abs/1706.00384)(Deep Mutual Learning), as shown in the figure below, can effectively improve the accuracy of the text detection model by learning from each other with two models with the same structure. The DML strategy is adopted in the teacher model training, and the hmean is increased from 85% to 86%. By updating the teacher model of CML in PP-OCRv2 to the above-mentioned higher-precision one, the hmean of the student model can be further improved from 83.2% to 84.3%.
@@ -100,7 +100,7 @@ Considering that the features of some channels will be suppressed if the convolu The recognition module of PP-OCRv3 is optimized based on the text recognition algorithm [SVTR](https://arxiv.org/abs/2205.00159). RNN is abandoned in SVTR, and the context information of the text line image is more effectively mined by introducing the Transformers structure, thereby improving the text recognition ability. -The recognition accuracy of SVTR_inty outperforms PP-OCRv2 recognition model by 5.3%, while the prediction speed nearly 11 times slower. It takes nearly 100ms to predict a text line on CPU. Therefore, as shown in the figure below, PP-OCRv3 adopts the following six optimization strategies to accelerate the recognition model. +The recognition accuracy of SVTR_tiny outperforms PP-OCRv2 recognition model by 5.3%, while the prediction speed nearly 11 times slower. It takes nearly 100ms to predict a text line on CPU. Therefore, as shown in the figure below, PP-OCRv3 adopts the following six optimization strategies to accelerate the recognition model.
diff --git a/doc/doc_en/algorithm_rec_starnet.md b/doc/doc_en/algorithm_rec_starnet.md new file mode 100644 index 0000000000000000000000000000000000000000..dbb53a9c737c16fa249483fa97b0b49cf25b2137 --- /dev/null +++ b/doc/doc_en/algorithm_rec_starnet.md @@ -0,0 +1,139 @@ +# STAR-Net + +- [1. Introduction](#1) +- [2. Environment](#2) +- [3. Model Training / Evaluation / Prediction](#3) + - [3.1 Training](#3-1) + - [3.2 Evaluation](#3-2) + - [3.3 Prediction](#3-3) +- [4. Inference and Deployment](#4) + - [4.1 Python Inference](#4-1) + - [4.2 C++ Inference](#4-2) + - [4.3 Serving](#4-3) + - [4.4 More](#4-4) +- [5. FAQ](#5) + + +## 1. Introduction + +Paper information: +> [STAR-Net: a spatial attention residue network for scene text recognition.](http://www.bmva.org/bmvc/2016/papers/paper043/paper043.pdf) +> Wei Liu, Chaofeng Chen, Kwan-Yee K. Wong, Zhizhong Su and Junyu Han. +> BMVC, pages 43.1-43.13, 2016 + +Refer to [DTRB](https://arxiv.org/abs/1904.01906) text Recognition Training and Evaluation Process . Using MJSynth and SynthText two text recognition datasets for training, and evaluating on IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE datasets, the algorithm reproduction effect is as follows: + +|Models|Backbone Networks|Avg Accuracy|Configuration Files|Download Links| +| --- | --- | --- | --- | --- | +|StarNet|Resnet34_vd|84.44%|[configs/rec/rec_r34_vd_tps_bilstm_ctc.yml](../../configs/rec/rec_r34_vd_tps_bilstm_ctc.yml)|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar)| +|StarNet|MobileNetV3|81.42%|[configs/rec/rec_mv3_tps_bilstm_ctc.yml](../../configs/rec/rec_mv3_tps_bilstm_ctc.yml)|[ trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_ctc_v2.0_train.tar)| + + + +## 2. Environment +Please refer to [Operating Environment Preparation](./environment_en.md) to configure the PaddleOCR operating environment, and refer to [Project Clone](./clone_en.md) to clone the project code. + + +## 3. Model Training / Evaluation / Prediction + +Please refer to [Text Recognition Training Tutorial](./recognition_en.md). PaddleOCR modularizes the code, and training different recognition models only requires **changing the configuration file**. Take the backbone network based on Resnet34_vd as an example: + + +### 3.1 Training +After the data preparation is complete, the training can be started. The training command is as follows: + +```` +#Single card training (long training period, not recommended) +python3 tools/train.py -c configs/rec/rec_r34_vd_tps_bilstm_ctc.yml #Multi-card training, specify the card number through the --gpus parameter +python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/train.py -c rec_r34_vd_tps_bilstm_ctc.yml + ```` + + +### 3.2 Evaluation + +```` +# GPU evaluation, Global.pretrained_model is the model to be evaluated +python3 -m paddle.distributed.launch --gpus '0' tools/eval.py -c configs/rec/rec_r34_vd_tps_bilstm_ctc.yml -o Global.pretrained_model={path/to/weights}/best_accuracy + ```` + + +### 3.3 Prediction + +```` +# The configuration file used for prediction must match the training +python3 tools/infer_rec.py -c configs/rec/rec_r34_vd_tps_bilstm_ctc.yml -o Global.pretrained_model={path/to/weights}/best_accuracy Global.infer_img=doc/imgs_words/en/word_1.png + ```` + + +## 4. Inference + + +### 4.1 Python Inference +First, convert the model saved during the STAR-Net text recognition training process into an inference model. Take the model trained on the MJSynth and SynthText text recognition datasets based on the Resnet34_vd backbone network as an example [Model download address]( https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_bilstm_ctc_v2.0_train.tar) , which can be converted using the following command: + +```shell +python3 tools/export_model.py -c configs/rec/rec_r34_vd_tps_bilstm_ctc.yml -o Global.pretrained_model=./rec_r34_vd_tps_bilstm_ctc_v2.0_train/best_accuracy Global.save_inference_dir=./inference/rec_starnet + ```` + +STAR-Net text recognition model inference, you can execute the following commands: + +```shell +python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./inference/rec_starnet/" --rec_image_shape="3, 32, 100" --rec_char_dict_path="./ppocr/utils/ic15_dict.txt" + ```` + +![](../imgs_words_en/word_336.png) + +The inference results are as follows: + + +```bash +Predicts of ./doc/imgs_words_en/word_336.png:('super', 0.9999073) +``` + +**Attention** Since the above model refers to the [DTRB](https://arxiv.org/abs/1904.01906) text recognition training and evaluation process, it is different from the ultra-lightweight Chinese recognition model training in two aspects: + +- The image resolutions used during training are different. The image resolutions used for training the above models are [3, 32, 100], while for Chinese model training, in order to ensure the recognition effect of long texts, the image resolutions used during training are [ 3, 32, 320]. The default shape parameter of the predictive inference program is the image resolution used for training Chinese, i.e. [3, 32, 320]. Therefore, when inferring the above English model here, it is necessary to set the shape of the recognized image through the parameter rec_image_shape. + +- Character list, the experiment in the DTRB paper is only for 26 lowercase English letters and 10 numbers, a total of 36 characters. All uppercase and lowercase characters are converted to lowercase characters, and characters not listed above are ignored and considered spaces. Therefore, there is no input character dictionary here, but a dictionary is generated by the following command. Therefore, the parameter rec_char_dict_path needs to be set during inference, which is specified as an English dictionary "./ppocr/utils/ic15_dict.txt". + +``` +self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz" +dict_character = list(self.character_str) + + + ``` + + +### 4.2 C++ Inference + +After preparing the inference model, refer to the [cpp infer](../../deploy/cpp_infer/) tutorial to operate. + + +### 4.3 Serving + +After preparing the inference model, refer to the [pdserving](../../deploy/pdserving/) tutorial for Serving deployment, including two modes: Python Serving and C++ Serving. + + +### 4.4 More + +The STAR-Net model also supports the following inference deployment methods: + +- Paddle2ONNX Inference: After preparing the inference model, refer to the [paddle2onnx](../../deploy/paddle2onnx/) tutorial. + + +## 5. FAQ + +## Quote + +```bibtex +@inproceedings{liu2016star, + title={STAR-Net: a spatial attention residue network for scene text recognition.}, + author={Liu, Wei and Chen, Chaofeng and Wong, Kwan-Yee K and Su, Zhizhong and Han, Junyu}, + booktitle={BMVC}, + volume={2}, + pages={7}, + year={2016} +} +``` + + diff --git a/doc/doc_en/detection_en.md b/doc/doc_en/detection_en.md index 76e0f8509b92dfaae62dce7ba2b4b73d39da1600..f85bf585cb66332d90de8d66ed315cb04ece7636 100644 --- a/doc/doc_en/detection_en.md +++ b/doc/doc_en/detection_en.md @@ -159,7 +159,7 @@ python3 -m paddle.distributed.launch --ips="xx.xx.xx.xx,xx.xx.xx.xx" --gpus '0,1 -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained ``` -**Note:** When using multi-machine and multi-gpu training, you need to replace the ips value in the above command with the address of your machine, and the machines need to be able to ping each other. In addition, training needs to be launched separately on multiple machines. The command to view the ip address of the machine is `ifconfig`. +**Note:** (1) When using multi-machine and multi-gpu training, you need to replace the ips value in the above command with the address of your machine, and the machines need to be able to ping each other. (2) Training needs to be launched separately on multiple machines. The command to view the ip address of the machine is `ifconfig`. (3) For more details about the distributed training speedup ratio, please refer to [Distributed Training Tutorial](./distributed_training_en.md). ### 2.6 Training with knowledge distillation diff --git a/doc/doc_en/distributed_training.md b/doc/doc_en/distributed_training_en.md similarity index 70% rename from doc/doc_en/distributed_training.md rename to doc/doc_en/distributed_training_en.md index 2822ee5e4ea52720a458e4060d8a09be7b98846b..5a219ed2b494d6239096ff634dfdc702c4be9419 100644 --- a/doc/doc_en/distributed_training.md +++ b/doc/doc_en/distributed_training_en.md @@ -40,11 +40,17 @@ python3 -m paddle.distributed.launch \ ## Performance comparison -* Based on 26W public recognition dataset (LSVT, rctw, mtwi), training on single 8-card P40 and dual 8-card P40, the final time consumption is as follows. +* On two 8-card P40 graphics cards, the final time consumption and speedup ratio for public recognition dataset (LSVT, RCTW, MTWI) containing 260k images are as follows. -| Model | Config file | Number of machines | Number of GPUs per machine | Training time | Recognition acc | Speedup ratio | -| :-------: | :------------: | :----------------: | :----------------------------: | :------------------: | :--------------: | :-----------: | -| CRNN | configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml | 1 | 8 | 60h | 66.7% | - | -| CRNN | configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml | 2 | 8 | 40h | 67.0% | 150% | -It can be seen that the training time is shortened from 60h to 40h, the speedup ratio can reach 150% (60h / 40h), and the efficiency is 75% (60h / (40h * 2)). +| Model | Config file | Recognition acc | single 8-card training time | two 8-card training time | Speedup ratio | +|------|-----|--------|--------|--------|-----| +| CRNN | [rec_chinese_lite_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml) | 67.0% | 2.50d | 1.67d | **1.5** | + + +* On four 8-card V100 graphics cards, the final time consumption and speedup ratio for full data are as follows. + + +| Model | Config file | Recognition acc | single 8-card training time | four 8-card training time | Speedup ratio | +|------|-----|--------|--------|--------|-----| +| SVTR | [ch_PP-OCRv3_rec_distillation.yml](../../configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml) | 74.0% | 10d | 2.84d | **3.5** | diff --git a/doc/doc_en/ppocr_introduction_en.md b/doc/doc_en/ppocr_introduction_en.md index b13d7f9bf1915de4bbbbec7b384d278e1d7ab8b4..d28ccb3529a46bdf0d3fd1d1c81f14137d10f2ea 100644 --- a/doc/doc_en/ppocr_introduction_en.md +++ b/doc/doc_en/ppocr_introduction_en.md @@ -29,10 +29,10 @@ PP-OCR pipeline is as follows: PP-OCR system is in continuous optimization. At present, PP-OCR and PP-OCRv2 have been released: -PP-OCR adopts 19 effective strategies from 8 aspects including backbone network selection and adjustment, prediction head design, data augmentation, learning rate transformation strategy, regularization parameter selection, pre-training model use, and automatic model tailoring and quantization to optimize and slim down the models of each module (as shown in the green box above). The final results are an ultra-lightweight Chinese and English OCR model with an overall size of 3.5M and a 2.8M English digital OCR model. For more details, please refer to the PP-OCR technical article (https://arxiv.org/abs/2009.09941). +PP-OCR adopts 19 effective strategies from 8 aspects including backbone network selection and adjustment, prediction head design, data augmentation, learning rate transformation strategy, regularization parameter selection, pre-training model use, and automatic model tailoring and quantization to optimize and slim down the models of each module (as shown in the green box above). The final results are an ultra-lightweight Chinese and English OCR model with an overall size of 3.5M and a 2.8M English digital OCR model. For more details, please refer to [PP-OCR technical report](https://arxiv.org/abs/2009.09941). #### PP-OCRv2 -On the basis of PP-OCR, PP-OCRv2 is further optimized in five aspects. The detection model adopts CML(Collaborative Mutual Learning) knowledge distillation strategy and CopyPaste data expansion strategy. The recognition model adopts LCNet lightweight backbone network, U-DML knowledge distillation strategy and enhanced CTC loss function improvement (as shown in the red box above), which further improves the inference speed and prediction effect. For more details, please refer to the technical report of PP-OCRv2 (https://arxiv.org/abs/2109.03144). +On the basis of PP-OCR, PP-OCRv2 is further optimized in five aspects. The detection model adopts CML(Collaborative Mutual Learning) knowledge distillation strategy and CopyPaste data expansion strategy. The recognition model adopts LCNet lightweight backbone network, U-DML knowledge distillation strategy and enhanced CTC loss function improvement (as shown in the red box above), which further improves the inference speed and prediction effect. For more details, please refer to [PP-OCRv2 technical report](https://arxiv.org/abs/2109.03144). #### PP-OCRv3 @@ -46,7 +46,7 @@ PP-OCRv3 pipeline is as follows:
-For more details, please refer to [PP-OCRv3 technical report](./PP-OCRv3_introduction_en.md). +For more details, please refer to [PP-OCRv3 technical report](https://arxiv.org/abs/2206.03001v2). ## 2. Features diff --git a/doc/doc_en/quickstart_en.md b/doc/doc_en/quickstart_en.md index d7aeb7773021aa6cf8f4d71298588915e5938fab..c678dc47625f4289a93621144bf5577b059d52b3 100644 --- a/doc/doc_en/quickstart_en.md +++ b/doc/doc_en/quickstart_en.md @@ -119,7 +119,18 @@ If you do not use the provided test image, you can replace the following `--imag ['PAIN', 0.9934559464454651] ``` -If you need to use the 2.0 model, please specify the parameter `--ocr_version PP-OCR`, paddleocr uses the PP-OCRv3 model by default(`--ocr_version PP-OCRv3`). More whl package usage can be found in [whl package](./whl_en.md) +**Version** +paddleocr uses the PP-OCRv3 model by default(`--ocr_version PP-OCRv3`). If you want to use other versions, you can set the parameter `--ocr_version`, the specific version description is as follows: +| version name | description | +| --- | --- | +| PP-OCRv3 | support Chinese and English detection and recognition, direction classifier, support multilingual recognition | +| PP-OCRv2 | only supports Chinese and English detection and recognition, direction classifier, multilingual model is not updated | +| PP-OCR | support Chinese and English detection and recognition, direction classifier, support multilingual recognition | + +If you want to add your own trained model, you can add model links and keys in [paddleocr](../../paddleocr.py) and recompile. + +More whl package usage can be found in [whl package](./whl_en.md) + #### 2.1.2 Multi-language Model diff --git a/doc/doc_en/recognition_en.md b/doc/doc_en/recognition_en.md index 60b4a1b26b373adc562ab9624e55ffe59a775a35..7d31b0ffe28c59ad3397d06fa178bcf8cbb822e9 100644 --- a/doc/doc_en/recognition_en.md +++ b/doc/doc_en/recognition_en.md @@ -306,7 +306,7 @@ python3 -m paddle.distributed.launch --ips="xx.xx.xx.xx,xx.xx.xx.xx" --gpus '0,1 -o Global.pretrained_model=./pretrain_models/rec_mv3_none_bilstm_ctc_v2.0_train ``` -**Note:** When using multi-machine and multi-gpu training, you need to replace the ips value in the above command with the address of your machine, and the machines need to be able to ping each other. In addition, training needs to be launched separately on multiple machines. The command to view the ip address of the machine is `ifconfig`. +**Note:** (1) When using multi-machine and multi-gpu training, you need to replace the ips value in the above command with the address of your machine, and the machines need to be able to ping each other. (2) Training needs to be launched separately on multiple machines. The command to view the ip address of the machine is `ifconfig`. (3) For more details about the distributed training speedup ratio, please refer to [Distributed Training Tutorial](./distributed_training_en.md). ### 2.6 Training with Knowledge Distillation diff --git a/paddleocr.py b/paddleocr.py index a1265f79def7018a5586be954127e5b7fdba011e..470dc60da3b15195bcd401aff5e50be5a2cfd13e 100644 --- a/paddleocr.py +++ b/paddleocr.py @@ -154,7 +154,13 @@ MODEL_URLS = { 'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar', 'dict_path': './ppocr/utils/ppocr_keys_v1.txt' } - } + }, + 'cls': { + 'ch': { + 'url': + 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar', + } + }, }, 'PP-OCR': { 'det': { diff --git a/ppocr/data/imaug/__init__.py b/ppocr/data/imaug/__init__.py index 548832fb0d116ba2de622bd97562b591d74501d8..f0fd578f61452d319ba9ea88eb6a5f37ab55afcf 100644 --- a/ppocr/data/imaug/__init__.py +++ b/ppocr/data/imaug/__init__.py @@ -22,7 +22,7 @@ from .make_shrink_map import MakeShrinkMap from .random_crop_data import EastRandomCropData, RandomCropImgMask from .make_pse_gt import MakePseGt -from .rec_img_aug import RecAug, RecConAug, RecResizeImg, ClsResizeImg, \ +from .rec_img_aug import BaseDataAugmentation, RecAug, RecConAug, RecResizeImg, ClsResizeImg, \ SRNRecResizeImg, NRTRRecResizeImg, SARRecResizeImg, PRENResizeImg from .ssl_img_aug import SSLRotateResize from .randaugment import RandAugment diff --git a/ppocr/data/imaug/rec_img_aug.py b/ppocr/data/imaug/rec_img_aug.py index 7483dffe5b6d9a0a2204702757fcb49762a1cc7a..32de2b3fc36757fee954de41686d09999ce4c640 100644 --- a/ppocr/data/imaug/rec_img_aug.py +++ b/ppocr/data/imaug/rec_img_aug.py @@ -22,13 +22,74 @@ from .text_image_aug import tia_perspective, tia_stretch, tia_distort class RecAug(object): - def __init__(self, use_tia=True, aug_prob=0.4, **kwargs): - self.use_tia = use_tia - self.aug_prob = aug_prob + def __init__(self, + tia_prob=0.4, + crop_prob=0.4, + reverse_prob=0.4, + noise_prob=0.4, + jitter_prob=0.4, + blur_prob=0.4, + hsv_aug_prob=0.4, + **kwargs): + self.tia_prob = tia_prob + self.bda = BaseDataAugmentation(crop_prob, reverse_prob, noise_prob, + jitter_prob, blur_prob, hsv_aug_prob) def __call__(self, data): img = data['image'] - img = warp(img, 10, self.use_tia, self.aug_prob) + h, w, _ = img.shape + + # tia + if random.random() <= self.tia_prob: + if h >= 20 and w >= 20: + img = tia_distort(img, random.randint(3, 6)) + img = tia_stretch(img, random.randint(3, 6)) + img = tia_perspective(img) + + # bda + data['image'] = img + data = self.bda(data) + return data + + +class BaseDataAugmentation(object): + def __init__(self, + crop_prob=0.4, + reverse_prob=0.4, + noise_prob=0.4, + jitter_prob=0.4, + blur_prob=0.4, + hsv_aug_prob=0.4, + **kwargs): + self.crop_prob = crop_prob + self.reverse_prob = reverse_prob + self.noise_prob = noise_prob + self.jitter_prob = jitter_prob + self.blur_prob = blur_prob + self.hsv_aug_prob = hsv_aug_prob + + def __call__(self, data): + img = data['image'] + h, w, _ = img.shape + + if random.random() <= self.crop_prob and h >= 20 and w >= 20: + img = get_crop(img) + + if random.random() <= self.blur_prob: + img = blur(img) + + if random.random() <= self.hsv_aug_prob: + img = hsv_aug(img) + + if random.random() <= self.jitter_prob: + img = jitter(img) + + if random.random() <= self.noise_prob: + img = add_gasuss_noise(img) + + if random.random() <= self.reverse_prob: + img = 255 - img + data['image'] = img return data @@ -359,7 +420,7 @@ def flag(): return 1 if random.random() > 0.5000001 else -1 -def cvtColor(img): +def hsv_aug(img): """ cvtColor """ @@ -427,50 +488,6 @@ def get_crop(image): return crop_img -class Config: - """ - Config - """ - - def __init__(self, use_tia): - self.anglex = random.random() * 30 - self.angley = random.random() * 15 - self.anglez = random.random() * 10 - self.fov = 42 - self.r = 0 - self.shearx = random.random() * 0.3 - self.sheary = random.random() * 0.05 - self.borderMode = cv2.BORDER_REPLICATE - self.use_tia = use_tia - - def make(self, w, h, ang): - """ - make - """ - self.anglex = random.random() * 5 * flag() - self.angley = random.random() * 5 * flag() - self.anglez = -1 * random.random() * int(ang) * flag() - self.fov = 42 - self.r = 0 - self.shearx = 0 - self.sheary = 0 - self.borderMode = cv2.BORDER_REPLICATE - self.w = w - self.h = h - - self.perspective = self.use_tia - self.stretch = self.use_tia - self.distort = self.use_tia - - self.crop = True - self.affine = False - self.reverse = True - self.noise = True - self.jitter = True - self.blur = True - self.color = True - - def rad(x): """ rad @@ -554,48 +571,3 @@ def get_warpAffine(config): rz = np.array([[np.cos(rad(anglez)), np.sin(rad(anglez)), 0], [-np.sin(rad(anglez)), np.cos(rad(anglez)), 0]], np.float32) return rz - - -def warp(img, ang, use_tia=True, prob=0.4): - """ - warp - """ - h, w, _ = img.shape - config = Config(use_tia=use_tia) - config.make(w, h, ang) - new_img = img - - if config.distort: - img_height, img_width = img.shape[0:2] - if random.random() <= prob and img_height >= 20 and img_width >= 20: - new_img = tia_distort(new_img, random.randint(3, 6)) - - if config.stretch: - img_height, img_width = img.shape[0:2] - if random.random() <= prob and img_height >= 20 and img_width >= 20: - new_img = tia_stretch(new_img, random.randint(3, 6)) - - if config.perspective: - if random.random() <= prob: - new_img = tia_perspective(new_img) - - if config.crop: - img_height, img_width = img.shape[0:2] - if random.random() <= prob and img_height >= 20 and img_width >= 20: - new_img = get_crop(new_img) - - if config.blur: - if random.random() <= prob: - new_img = blur(new_img) - if config.color: - if random.random() <= prob: - new_img = cvtColor(new_img) - if config.jitter: - new_img = jitter(new_img) - if config.noise: - if random.random() <= prob: - new_img = add_gasuss_noise(new_img) - if config.reverse: - if random.random() <= prob: - new_img = 255 - new_img - return new_img diff --git a/ppocr/data/simple_dataset.py b/ppocr/data/simple_dataset.py index b5da9b8898423facf888839f941dff01caa03643..402f1e38fed9e32722e2dd160f10f779028807a3 100644 --- a/ppocr/data/simple_dataset.py +++ b/ppocr/data/simple_dataset.py @@ -33,7 +33,7 @@ class SimpleDataSet(Dataset): self.delimiter = dataset_config.get('delimiter', '\t') label_file_list = dataset_config.pop('label_file_list') data_source_num = len(label_file_list) - ratio_list = dataset_config.get("ratio_list", [1.0]) + ratio_list = dataset_config.get("ratio_list", 1.0) if isinstance(ratio_list, (float, int)): ratio_list = [float(ratio_list)] * int(data_source_num) diff --git a/ppocr/losses/rec_aster_loss.py b/ppocr/losses/rec_aster_loss.py index fbb99d29a638540b02649a8912051339c08b22dd..52605e46db35339cc22f7f1e6642456bfaf02f11 100644 --- a/ppocr/losses/rec_aster_loss.py +++ b/ppocr/losses/rec_aster_loss.py @@ -27,12 +27,12 @@ class CosineEmbeddingLoss(nn.Layer): self.epsilon = 1e-12 def forward(self, x1, x2, target): - similarity = paddle.fluid.layers.reduce_sum( + similarity = paddle.sum( x1 * x2, dim=-1) / (paddle.norm( x1, axis=-1) * paddle.norm( x2, axis=-1) + self.epsilon) one_list = paddle.full_like(target, fill_value=1) - out = paddle.fluid.layers.reduce_mean( + out = paddle.mean( paddle.where( paddle.equal(target, one_list), 1. - similarity, paddle.maximum( diff --git a/ppocr/losses/table_att_loss.py b/ppocr/losses/table_att_loss.py index d7fd99e6952aacc0182a482ca5ae5ddaf959a026..51377efa2b5e802fe9f9fc1973c74deb00fc4816 100644 --- a/ppocr/losses/table_att_loss.py +++ b/ppocr/losses/table_att_loss.py @@ -19,7 +19,6 @@ from __future__ import print_function import paddle from paddle import nn from paddle.nn import functional as F -from paddle import fluid class TableAttentionLoss(nn.Layer): def __init__(self, structure_weight, loc_weight, use_giou=False, giou_weight=1.0, **kwargs): @@ -36,13 +35,13 @@ class TableAttentionLoss(nn.Layer): :param bbox:[[x1,y1,x2,y2], [x1,y1,x2,y2],,,] :return: loss ''' - ix1 = fluid.layers.elementwise_max(preds[:, 0], bbox[:, 0]) - iy1 = fluid.layers.elementwise_max(preds[:, 1], bbox[:, 1]) - ix2 = fluid.layers.elementwise_min(preds[:, 2], bbox[:, 2]) - iy2 = fluid.layers.elementwise_min(preds[:, 3], bbox[:, 3]) + ix1 = paddle.maximum(preds[:, 0], bbox[:, 0]) + iy1 = paddle.maximum(preds[:, 1], bbox[:, 1]) + ix2 = paddle.minimum(preds[:, 2], bbox[:, 2]) + iy2 = paddle.minimum(preds[:, 3], bbox[:, 3]) - iw = fluid.layers.clip(ix2 - ix1 + 1e-3, 0., 1e10) - ih = fluid.layers.clip(iy2 - iy1 + 1e-3, 0., 1e10) + iw = paddle.clip(ix2 - ix1 + 1e-3, 0., 1e10) + ih = paddle.clip(iy2 - iy1 + 1e-3, 0., 1e10) # overlap inters = iw * ih @@ -55,12 +54,12 @@ class TableAttentionLoss(nn.Layer): # ious ious = inters / uni - ex1 = fluid.layers.elementwise_min(preds[:, 0], bbox[:, 0]) - ey1 = fluid.layers.elementwise_min(preds[:, 1], bbox[:, 1]) - ex2 = fluid.layers.elementwise_max(preds[:, 2], bbox[:, 2]) - ey2 = fluid.layers.elementwise_max(preds[:, 3], bbox[:, 3]) - ew = fluid.layers.clip(ex2 - ex1 + 1e-3, 0., 1e10) - eh = fluid.layers.clip(ey2 - ey1 + 1e-3, 0., 1e10) + ex1 = paddle.minimum(preds[:, 0], bbox[:, 0]) + ey1 = paddle.minimum(preds[:, 1], bbox[:, 1]) + ex2 = paddle.maximum(preds[:, 2], bbox[:, 2]) + ey2 = paddle.maximum(preds[:, 3], bbox[:, 3]) + ew = paddle.clip(ex2 - ex1 + 1e-3, 0., 1e10) + eh = paddle.clip(ey2 - ey1 + 1e-3, 0., 1e10) # enclose erea enclose = ew * eh + eps diff --git a/ppocr/modeling/backbones/kie_unet_sdmgr.py b/ppocr/modeling/backbones/kie_unet_sdmgr.py index 545e4e7511e58c3d8220e9ec0be35474deba8806..4b1bd8030060b26acb9e60bd671a5b23d936347b 100644 --- a/ppocr/modeling/backbones/kie_unet_sdmgr.py +++ b/ppocr/modeling/backbones/kie_unet_sdmgr.py @@ -175,12 +175,7 @@ class Kie_backbone(nn.Layer): img, relations, texts, gt_bboxes, tag, img_size) x = self.img_feat(img) boxes, rois_num = self.bbox2roi(gt_bboxes) - feats = paddle.fluid.layers.roi_align( - x, - boxes, - spatial_scale=1.0, - pooled_height=7, - pooled_width=7, - rois_num=rois_num) + feats = paddle.vision.ops.roi_align( + x, boxes, spatial_scale=1.0, output_size=7, boxes_num=rois_num) feats = self.maxpool(feats).squeeze(-1).squeeze(-1) return [relations, texts, feats] diff --git a/ppocr/modeling/backbones/rec_resnet_fpn.py b/ppocr/modeling/backbones/rec_resnet_fpn.py index a7e876a2bd52a0ea70479c2009a291e4e2f8ce1f..79efd6e41e231ecad99aa4d01a8226a8550bd1ef 100644 --- a/ppocr/modeling/backbones/rec_resnet_fpn.py +++ b/ppocr/modeling/backbones/rec_resnet_fpn.py @@ -18,7 +18,6 @@ from __future__ import print_function from paddle import nn, ParamAttr from paddle.nn import functional as F -import paddle.fluid as fluid import paddle import numpy as np diff --git a/ppocr/modeling/heads/rec_srn_head.py b/ppocr/modeling/heads/rec_srn_head.py index 8d59e4711a043afd9234f430a62c9876c0a8f6f4..1070d8cd648eb686c0a2e66df092b7dc6de29c42 100644 --- a/ppocr/modeling/heads/rec_srn_head.py +++ b/ppocr/modeling/heads/rec_srn_head.py @@ -20,13 +20,11 @@ import math import paddle from paddle import nn, ParamAttr from paddle.nn import functional as F -import paddle.fluid as fluid import numpy as np from .self_attention import WrapEncoderForFeature from .self_attention import WrapEncoder from paddle.static import Program from ppocr.modeling.backbones.rec_resnet_fpn import ResNetFPN -import paddle.fluid.framework as framework from collections import OrderedDict gradient_clip = 10 diff --git a/ppocr/modeling/heads/self_attention.py b/ppocr/modeling/heads/self_attention.py index 6c27fdbe434166e9277cc8d695bce2743cbd8ec6..6e4c65e3931ae74a0fde2a16694a69fdfa69b5ed 100644 --- a/ppocr/modeling/heads/self_attention.py +++ b/ppocr/modeling/heads/self_attention.py @@ -22,7 +22,6 @@ import paddle from paddle import ParamAttr, nn from paddle import nn, ParamAttr from paddle.nn import functional as F -import paddle.fluid as fluid import numpy as np gradient_clip = 10 @@ -288,10 +287,10 @@ class PrePostProcessLayer(nn.Layer): "layer_norm_%d" % len(self.sublayers()), paddle.nn.LayerNorm( normalized_shape=d_model, - weight_attr=fluid.ParamAttr( - initializer=fluid.initializer.Constant(1.)), - bias_attr=fluid.ParamAttr( - initializer=fluid.initializer.Constant(0.))))) + weight_attr=paddle.ParamAttr( + initializer=paddle.nn.initializer.Constant(1.)), + bias_attr=paddle.ParamAttr( + initializer=paddle.nn.initializer.Constant(0.))))) elif cmd == "d": # add dropout self.functors.append(lambda x: F.dropout( x, p=dropout_rate, mode="downscale_in_infer") @@ -324,7 +323,7 @@ class PrepareEncoder(nn.Layer): def forward(self, src_word, src_pos): src_word_emb = src_word - src_word_emb = fluid.layers.cast(src_word_emb, 'float32') + src_word_emb = paddle.cast(src_word_emb, 'float32') src_word_emb = paddle.scale(x=src_word_emb, scale=self.src_emb_dim**0.5) src_pos = paddle.squeeze(src_pos, axis=-1) src_pos_enc = self.emb(src_pos) @@ -367,7 +366,7 @@ class PrepareDecoder(nn.Layer): self.dropout_rate = dropout_rate def forward(self, src_word, src_pos): - src_word = fluid.layers.cast(src_word, 'int64') + src_word = paddle.cast(src_word, 'int64') src_word = paddle.squeeze(src_word, axis=-1) src_word_emb = self.emb0(src_word) src_word_emb = paddle.scale(x=src_word_emb, scale=self.src_emb_dim**0.5) diff --git a/ppstructure/table/README.md b/ppstructure/table/README.md index d21ef4aa3813b4ff49dc0580be35c5e2e0483c8f..b6804c6f09b4ee3d17cd2b81e6cc6642c1c1be9a 100644 --- a/ppstructure/table/README.md +++ b/ppstructure/table/README.md @@ -18,7 +18,7 @@ The table recognition mainly contains three models The table recognition flow chart is as follows -![tableocr_pipeline](../../doc/table/tableocr_pipeline_en.jpg) +![tableocr_pipeline](../docs/table/tableocr_pipeline_en.jpg) 1. The coordinates of single-line text is detected by DB model, and then sends it to the recognition model to get the recognition result. 2. The table structure and cell coordinates is predicted by RARE model. diff --git a/ppstructure/table/predict_table.py b/ppstructure/table/predict_table.py index 402d6c24189d044e2ee6d359edef8624d4aae145..aa05459589208dde66a6710322593d091af41325 100644 --- a/ppstructure/table/predict_table.py +++ b/ppstructure/table/predict_table.py @@ -28,6 +28,7 @@ import numpy as np import time import tools.infer.predict_rec as predict_rec import tools.infer.predict_det as predict_det +import tools.infer.utility as utility from ppocr.utils.utility import get_image_file_list, check_and_read_gif from ppocr.utils.logging import get_logger from ppstructure.table.matcher import distance, compute_iou @@ -59,11 +60,37 @@ class TableSystem(object): self.text_recognizer = predict_rec.TextRecognizer( args) if text_recognizer is None else text_recognizer self.table_structurer = predict_strture.TableStructurer(args) + self.benchmark = args.benchmark + self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor( + args, 'table', logger) + if args.benchmark: + import auto_log + pid = os.getpid() + gpu_id = utility.get_infer_gpuid() + self.autolog = auto_log.AutoLogger( + model_name="table", + model_precision=args.precision, + batch_size=1, + data_shape="dynamic", + save_path=None, #args.save_log_path, + inference_config=self.config, + pids=pid, + process_name=None, + gpu_ids=gpu_id if args.use_gpu else None, + time_keys=[ + 'preprocess_time', 'inference_time', 'postprocess_time' + ], + warmup=0, + logger=logger) def __call__(self, img, return_ocr_result_in_table=False): result = dict() ori_im = img.copy() + if self.benchmark: + self.autolog.times.start() structure_res, elapse = self.table_structurer(copy.deepcopy(img)) + if self.benchmark: + self.autolog.times.stamp() dt_boxes, elapse = self.text_detector(copy.deepcopy(img)) dt_boxes = sorted_boxes(dt_boxes) if return_ocr_result_in_table: @@ -77,13 +104,11 @@ class TableSystem(object): box = [x_min, y_min, x_max, y_max] r_boxes.append(box) dt_boxes = np.array(r_boxes) - logger.debug("dt_boxes num : {}, elapse : {}".format( len(dt_boxes), elapse)) if dt_boxes is None: return None, None img_crop_list = [] - for i in range(len(dt_boxes)): det_box = dt_boxes[i] x0, y0, x1, y1 = expand(2, det_box, ori_im.shape) @@ -92,10 +117,14 @@ class TableSystem(object): rec_res, elapse = self.text_recognizer(img_crop_list) logger.debug("rec_res num : {}, elapse : {}".format( len(rec_res), elapse)) + if self.benchmark: + self.autolog.times.stamp() if return_ocr_result_in_table: result['rec_res'] = rec_res pred_html, pred = self.rebuild_table(structure_res, dt_boxes, rec_res) result['html'] = pred_html + if self.benchmark: + self.autolog.times.end(stamp=True) return result def rebuild_table(self, structure_res, dt_boxes, rec_res): @@ -213,6 +242,8 @@ def main(args): logger.info('excel saved to {}'.format(excel_path)) elapse = time.time() - starttime logger.info("Predict time : {:.3f}s".format(elapse)) + if args.benchmark: + text_sys.autolog.report() if __name__ == "__main__": diff --git a/test_tipc/build_server.sh b/test_tipc/build_server.sh new file mode 100644 index 0000000000000000000000000000000000000000..3173359785290ffa5c6f865efe96705e2b09fae1 --- /dev/null +++ b/test_tipc/build_server.sh @@ -0,0 +1,69 @@ +#使用镜像: +#registry.baidubce.com/paddlepaddle/paddle:latest-dev-cuda10.1-cudnn7-gcc82 + +#编译Serving Server: + +#client和app可以直接使用release版本 + +#server因为加入了自定义OP,需要重新编译 + +apt-get update +apt install -y libcurl4-openssl-dev libbz2-dev +wget https://paddle-serving.bj.bcebos.com/others/centos_ssl.tar && tar xf centos_ssl.tar && rm -rf centos_ssl.tar && mv libcrypto.so.1.0.2k /usr/lib/libcrypto.so.1.0.2k && mv libssl.so.1.0.2k /usr/lib/libssl.so.1.0.2k && ln -sf /usr/lib/libcrypto.so.1.0.2k /usr/lib/libcrypto.so.10 && ln -sf /usr/lib/libssl.so.1.0.2k /usr/lib/libssl.so.10 && ln -sf /usr/lib/libcrypto.so.10 /usr/lib/libcrypto.so && ln -sf /usr/lib/libssl.so.10 /usr/lib/libssl.so + +# 安装go依赖 +rm -rf /usr/local/go +wget -qO- https://paddle-ci.cdn.bcebos.com/go1.17.2.linux-amd64.tar.gz | tar -xz -C /usr/local +export GOROOT=/usr/local/go +export GOPATH=/root/gopath +export PATH=$PATH:$GOPATH/bin:$GOROOT/bin +go env -w GO111MODULE=on +go env -w GOPROXY=https://goproxy.cn,direct +go install github.com/grpc-ecosystem/grpc-gateway/protoc-gen-grpc-gateway@v1.15.2 +go install github.com/grpc-ecosystem/grpc-gateway/protoc-gen-swagger@v1.15.2 +go install github.com/golang/protobuf/protoc-gen-go@v1.4.3 +go install google.golang.org/grpc@v1.33.0 +go env -w GO111MODULE=auto + +# 下载opencv库 +wget https://paddle-qa.bj.bcebos.com/PaddleServing/opencv3.tar.gz && tar -xvf opencv3.tar.gz && rm -rf opencv3.tar.gz +export OPENCV_DIR=$PWD/opencv3 + +# clone Serving +git clone https://github.com/PaddlePaddle/Serving.git -b develop --depth=1 +cd Serving +export Serving_repo_path=$PWD +git submodule update --init --recursive +python -m pip install -r python/requirements.txt + + +export PYTHON_INCLUDE_DIR=$(python -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") +export PYTHON_LIBRARIES=$(python -c "import distutils.sysconfig as sysconfig; print(sysconfig.get_config_var('LIBDIR'))") +export PYTHON_EXECUTABLE=`which python` + +export CUDA_PATH='/usr/local/cuda' +export CUDNN_LIBRARY='/usr/local/cuda/lib64/' +export CUDA_CUDART_LIBRARY='/usr/local/cuda/lib64/' +export TENSORRT_LIBRARY_PATH='/usr/local/TensorRT6-cuda10.1-cudnn7/targets/x86_64-linux-gnu/' + +# cp 自定义OP代码 +cp -rf ../deploy/pdserving/general_detection_op.cpp ${Serving_repo_path}/core/general-server/op + +# 编译Server, export SERVING_BIN +mkdir server-build-gpu-opencv && cd server-build-gpu-opencv +cmake -DPYTHON_INCLUDE_DIR=$PYTHON_INCLUDE_DIR \ + -DPYTHON_LIBRARIES=$PYTHON_LIBRARIES \ + -DPYTHON_EXECUTABLE=$PYTHON_EXECUTABLE \ + -DCUDA_TOOLKIT_ROOT_DIR=${CUDA_PATH} \ + -DCUDNN_LIBRARY=${CUDNN_LIBRARY} \ + -DCUDA_CUDART_LIBRARY=${CUDA_CUDART_LIBRARY} \ + -DTENSORRT_ROOT=${TENSORRT_LIBRARY_PATH} \ + -DOPENCV_DIR=${OPENCV_DIR} \ + -DWITH_OPENCV=ON \ + -DSERVER=ON \ + -DWITH_GPU=ON .. +make -j32 + +python -m pip install python/dist/paddle* +export SERVING_BIN=$PWD/core/general-server/serving +cd ../../ diff --git a/test_tipc/common_func.sh b/test_tipc/common_func.sh index 85dfe217253bb1d4c8b92f17d26f138121a2a198..f7d8a1e04adee9d32332eda8cb5913bbaf168481 100644 --- a/test_tipc/common_func.sh +++ b/test_tipc/common_func.sh @@ -57,10 +57,11 @@ function status_check(){ last_status=$1 # the exit code run_command=$2 run_log=$3 + model_name=$4 if [ $last_status -eq 0 ]; then - echo -e "\033[33m Run successfully with command - ${run_command}! \033[0m" | tee -a ${run_log} + echo -e "\033[33m Run successfully with command - ${model_name} - ${run_command}! \033[0m" | tee -a ${run_log} else - echo -e "\033[33m Run failed with command - ${run_command}! \033[0m" | tee -a ${run_log} + echo -e "\033[33m Run failed with command - ${model_name} - ${run_command}! \033[0m" | tee -a ${run_log} fi } diff --git a/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..a0c49a0812c5cb47c848d4b6e68e0b10f835c760 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv2 +use_opencv:True +infer_model:./inference/ch_PP-OCRv2_det_infer/ +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +--rec_model_dir:./inference/ch_PP-OCRv2_rec_infer/ +--benchmark:True +--det:True +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index fcac6e3984cf3fd45fec9f7b736f794289278b25..32b290a9ed0ca04032e7854d9739e1612a6a095f 100644 --- a/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -6,10 +6,10 @@ infer_export:null infer_quant:False inference:tools/infer/predict_system.py --use_gpu:False|True ---enable_mkldnn:False|True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ diff --git a/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..24eb620eeb6fc0cf880bb88560805491d6e8e2d5 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -0,0 +1,17 @@ +===========================paddle2onnx_params=========================== +model_name:ch_PP-OCRv2 +python:python3.7 +2onnx: paddle2onnx +--det_model_dir:./inference/ch_PP-OCRv2_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_save_file:./inference/det_v2_onnx/model.onnx +--rec_model_dir:./inference/ch_PP-OCRv2_rec_infer/ +--rec_save_file:./inference/rec_v2_onnx/model.onnx +--opset_version:10 +--enable_onnx_checker:True +inference:tools/infer/predict_system.py --rec_image_shape="3,32,320" +--use_gpu:True|False +--det_model_dir: +--rec_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/00008790.jpg \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..f0456b5c351d20222e331df6a5019a51b79b6d28 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2 +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_client/ +--rec_dirname:./inference/ch_PP-OCRv2_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..4ad64db03c6bbd017644a947ccdc168fd721ad9f --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2 +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_client/ +--rec_dirname:./inference/ch_PP-OCRv2_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_client/ +serving_dir:./deploy/pdserving +web_service:web_service.py --config=config.yml --opt op.det.concurrency="1" op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..7eccbd725c25938aeabb32499e67536f45eed184 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv2_det +use_opencv:True +infer_model:./inference/ch_PP-OCRv2_det_infer/ +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +--det:True +--rec:False +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..2e7906076faf4d8002f7746afd6f0cbb4adb8253 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -0,0 +1,17 @@ +===========================paddle2onnx_params=========================== +model_name:ch_PP-OCRv2_det +python:python3.7 +2onnx: paddle2onnx +--det_model_dir:./inference/ch_PP-OCRv2_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_save_file:./inference/det_v2_onnx/model.onnx +--rec_model_dir: +--rec_save_file: +--opset_version:10 +--enable_onnx_checker:True +inference:tools/infer/predict_det.py +--use_gpu:True|False +--det_model_dir: +--rec_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..587a7d7ea6644f4eda200e7ed8f095d9428a1310 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_det +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null +serving_dir:./deploy/pdserving +web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2_det/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv2_det/train_infer_python.txt index 797cf53a1ded756670709dd1a30c3ef25a9c0906..cab0cb0aa390c7cb1efa6e5d3bc636e9c974acba 100644 --- a/test_tipc/configs/ch_PP-OCRv2_det/train_infer_python.txt +++ b/test_tipc/configs/ch_PP-OCRv2_det/train_infer_python.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv2_det +model_name:ch_PP-OCRv2_det python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:fp32 -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv2_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..91a6288eb0d4f3d2a8c968a65916295d25024c32 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:ch_PP-OCRv2_det +python:python3.7 +gpu_list:192.168.0.1,192.168.0.2;0,1 +Global.use_gpu:True +Global.auto_cast:fp32 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ +null:null +## +trainer:norm_train +norm_train:tools/train.py -c configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml -o +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml -o +quant_export:null +fpgm_export: +distill_export:null +export1:null +export2:null +inference_dir:Student +infer_model:./inference/ch_PP-OCRv2_det_infer/ +infer_export:null +infer_quant:False +inference:tools/infer/predict_det.py +--use_gpu:False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}] diff --git a/test_tipc/configs/ch_PP-OCRv2_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 033d40a80a3569f8bfd408cdb6df37e7ba5ecd0c..85b0ebcb9d747acdf520d4516722526d791b1151 100644 --- a/test_tipc/configs/ch_PP-OCRv2_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv2_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv2_det +model_name:ch_PP-OCRv2_det python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..1975e099d7f8328f521d976d76b1070b365164fe --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv2_det_KL +use_opencv:True +infer_model:./inference/ch_PP-OCRv2_det_klquant_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +--det:True +--rec:False +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index 1aad65b687992155133ed11533a14f642510361d..ccc9e5ced086c2c617359bafdc8772fe92eab8fa 100644 --- a/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -1,5 +1,5 @@ ===========================kl_quant_params=========================== -model_name:PPOCRv2_ocr_det_kl +model_name:ch_PP-OCRv2_det_KL python:python3.7 Global.pretrained_model:null Global.save_inference_dir:null @@ -8,10 +8,10 @@ infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_PP-OCRv2/ch_ infer_quant:True inference:tools/infer/predict_det.py --use_gpu:False|True ---enable_mkldnn:True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:int8 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ diff --git a/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..e306b0a92afdc720227704c2e526e7c3cfe98ae6 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_det_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_kl_client/ +--rec_dirname:./inference/ch_PP-OCRv2_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_kl_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..2c96d2bfd88ce43f7701ee92a2c2bb8c909feed8 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_det_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_kl_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null +serving_dir:./deploy/pdserving +web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..43ef97d5063d347071501ab4d8874ee3a42e50d7 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv2_det_PACT +use_opencv:True +infer_model:./inference/ch_PP-OCRv2_det_pact_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +--det:True +--rec:False +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..b2d929b99c80d02c48795dab820da1836f7a2ebe --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_det_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_pact_client/ +--rec_dirname:./inference/ch_PP-OCRv2_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_pact_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..d5d99ab56d0e17789d1b6b0c593ed42e5ffad320 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_det_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_pact_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null +serving_dir:./deploy/pdserving +web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2_det_PACT/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv2_det_PACT/train_infer_python.txt index 038fa850614d45dbefe076b866571cead57b8450..1a20f97fdbcd10881de6e94d0724740ba44edc5c 100644 --- a/test_tipc/configs/ch_PP-OCRv2_det_PACT/train_infer_python.txt +++ b/test_tipc/configs/ch_PP-OCRv2_det_PACT/train_infer_python.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv2_det_PACT +model_name:ch_PP-OCRv2_det_PACT python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:fp32 -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=1|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv2_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index d922a4a5dad67da81e3c9cf7bed48a0431a88b84..3afc0acb799153b44bfddf713c1057f06ce525dc 100644 --- a/test_tipc/configs/ch_PP-OCRv2_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv2_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv2_det_PACT +model_name:ch_PP-OCRv2_det_PACT python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..b1bff00b09cedbe5abac50a471091fb2daedf8f3 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv2_rec +use_opencv:True +infer_model:./inference/ch_PP-OCRv2_rec_infer/ +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..e374a5d8216f54eef52e0765be30a1dcc391dc7b --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -0,0 +1,17 @@ +===========================paddle2onnx_params=========================== +model_name:ch_PP-OCRv2_rec +python:python3.7 +2onnx: paddle2onnx +--det_model_dir: +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_save_file: +--rec_model_dir:./inference/ch_PP-OCRv2_rec_infer/ +--rec_save_file:./inference/rec_v2_onnx/model.onnx +--opset_version:10 +--enable_onnx_checker:True +inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320" +--use_gpu:True|False +--det_model_dir: +--rec_model_dir: +--image_dir:./inference/rec_inference/ \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..e9e90d372e4a2fed645962ce6ad3b8112588f24a --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_rec +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:null +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_PP-OCRv2_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_client/ +serving_dir:./deploy/pdserving +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_PP-OCRv2_rec/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv2_rec/train_infer_python.txt index 188eb3ccc5f7aa2b3724dc1fb7132af090c22ffa..df42b342ba5fa3947a69c2bde5548975ca92d857 100644 --- a/test_tipc/configs/ch_PP-OCRv2_rec/train_infer_python.txt +++ b/test_tipc/configs/ch_PP-OCRv2_rec/train_infer_python.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:PPOCRv2_ocr_rec +model_name:ch_PP-OCRv2_rec python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:fp32 -Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_PP-OCRv2_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..5795bc27e686164578fc246e1fa467efdc52f71f --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:ch_PP-OCRv2_rec +python:python3.7 +gpu_list:192.168.0.1,192.168.0.2;0,1 +Global.use_gpu:True +Global.auto_cast:fp32 +Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./inference/rec_inference +null:null +## +trainer:norm_train +norm_train:tools/train.py -c test_tipc/configs/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.yml -o +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c test_tipc/configs/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.yml -o +quant_export: +fpgm_export: +distill_export:null +export1:null +export2:null +inference_dir:Student +infer_model:./inference/ch_PP-OCRv2_rec_infer +infer_export:null +infer_quant:False +inference:tools/infer/predict_rec.py +--use_gpu:False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1|6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference +null:null +--benchmark:True +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,32,320]}] diff --git a/test_tipc/configs/ch_PP-OCRv2_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 7c438cb8a3b6907c9ca352e90605d8b4f6fb17fd..1b8800f5cf8f1f864a03dd6a0408aafdd2cec3af 100644 --- a/test_tipc/configs/ch_PP-OCRv2_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv2_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:PPOCRv2_ocr_rec +model_name:ch_PP-OCRv2_rec python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..95e4062d145b5c0fc390049dee322b0e85ecee98 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv2_rec_KL +use_opencv:True +infer_model:./inference/ch_PP-OCRv2_rec_klquant_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index 083a3ae26e726e290ffde4095821cbf3c40f7178..c30e0858efda4df8f9912183c5c31b56413a5252 100644 --- a/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -1,17 +1,17 @@ ===========================kl_quant_params=========================== -model_name:PPOCRv2_ocr_rec_kl +model_name:ch_PP-OCRv2_rec_KL python:python3.7 Global.pretrained_model:null Global.save_inference_dir:null infer_model:./inference/ch_PP-OCRv2_rec_infer/ infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.yml -o infer_quant:True -inference:tools/infer/predict_rec.py +inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320" --use_gpu:False|True ---enable_mkldnn:False|True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True +--use_tensorrt:False --precision:int8 --rec_model_dir: --image_dir:./inference/rec_inference diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..34d4007b150385657a69ae93ef4e04bdf1ce149d --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_rec_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_kl_client/ +--rec_dirname:./inference/ch_PP-OCRv2_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_kl_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..3405f2b5876609bf6d97cf3d379613bf38c16cda --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_rec_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:null +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_PP-OCRv2_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_kl_client/ +serving_dir:./deploy/pdserving +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..b807eadd3ff7f38ce670f0db9d28aaacd62e207a --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv2_rec_PACT +use_opencv:True +infer_model:./inference/ch_PP-OCRv2_rec_pact_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..2a174b9e31b24ca002a639b1e8675cc6d5592bcc --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_rec_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv2_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v2_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v2_pact_client/ +--rec_dirname:./inference/ch_PP-OCRv2_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_pact_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..2b7ed81172473a7924d1af48937048bbee9d1953 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv2_rec_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:null +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_PP-OCRv2_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v2_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v2_pact_client/ +serving_dir:./deploy/pdserving +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt index 98c125229d7f968cd3f650c3885ba4edb0de754c..0ac75eff07a5ed4c17d7fdbe554fd4b5c0f11aed 100644 --- a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt +++ b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv2_rec_PACT +model_name:ch_PP-OCRv2_rec_PACT python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:fp32 -Global.epoch_num:lite_train_lite_infer=6|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 Global.pretrained_model:pretrain_models/ch_PP-OCRv2_rec_train/best_accuracy @@ -39,11 +39,11 @@ infer_export:null infer_quant:True inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index e22d8a564b008206611469048b424b528dd379bd..e0f86d9020fb77aec5fe051dffdb4bc1018f907e 100644 --- a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -1,13 +1,13 @@ ===========================train_params=========================== -model_name:ch_PPOCRv2_rec_PACT +model_name:ch_PP-OCRv2_rec_PACT python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 -Global.pretrained_model:null +Global.pretrained_model:pretrain_models/ch_PP-OCRv2_rec_train/best_accuracy train_model_name:latest train_infer_img_dir:./inference/rec_inference null:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:True inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt index da17069a96a50e7cf3bdac6bc49a68cade9e1110..794af27d90edd54ff888ab167698d57a92eab7b6 100644 --- a/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -1,15 +1,15 @@ ===========================cpp_infer_params=========================== -model_name:ocr_system_v3 +model_name:ch_PP-OCRv3 use_opencv:True infer_model:./inference/ch_PP-OCRv3_det_infer/ infer_quant:False inference:./deploy/cpp_infer/build/ppocr --rec_img_h=48 --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --rec_model_dir:./inference/ch_PP-OCRv3_rec_infer/ diff --git a/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index a0448265010720a367249dad3e23c332583fee38..afacdc140515297c75f8674b245b34fce4c9fad9 100644 --- a/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -6,10 +6,10 @@ infer_export:null infer_quant:False inference:tools/infer/predict_system.py --rec_image_shape="3,48,320" --use_gpu:False|True ---enable_mkldnn:False|True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ diff --git a/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..bf2556ef17dcdbd66ff81abe6dbb10639511cde4 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -0,0 +1,17 @@ +===========================paddle2onnx_params=========================== +model_name:ch_PP-OCRv3 +python:python3.7 +2onnx: paddle2onnx +--det_model_dir:./inference/ch_PP-OCRv3_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_save_file:./inference/det_v3_onnx/model.onnx +--rec_model_dir:./inference/ch_PP-OCRv3_rec_infer/ +--rec_save_file:./inference/rec_v3_onnx/model.onnx +--opset_version:10 +--enable_onnx_checker:True +inference:tools/infer/predict_system.py --rec_image_shape="3,48,320" +--use_gpu:True|False +--det_model_dir: +--rec_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/00008790.jpg \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..91c57bed1b9e9bbafc6438766b81781433a06aa2 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3 +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv3_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v3_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_client/ +--rec_dirname:./inference/ch_PP-OCRv3_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..6f699ef5c02015d214ef08fb7047a6e9be84e24d --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3 +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv3_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v3_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_client/ +--rec_dirname:./inference/ch_PP-OCRv3_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_client/ +serving_dir:./deploy/pdserving +web_service:web_service.py --config=config.yml --opt op.det.concurrency="1" op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt index c7a37ddd590e9e082be8f3694b7c7ef136ee2123..aecd0dd437ea028c555ffedf4227b55843dd7f2e 100644 --- a/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -1,15 +1,15 @@ ===========================cpp_infer_params=========================== -model_name:ocr_det_v3 +model_name:ch_PP-OCRv3_det use_opencv:True infer_model:./inference/ch_PP-OCRv3_det_infer/ infer_quant:False inference:./deploy/cpp_infer/build/ppocr --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt index b4c681c0aa601ef75b0b24f565b2d63c21558d05..a448713b1c91dbd190770056b2ee403f2ac56cc6 100644 --- a/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -1,14 +1,17 @@ ===========================paddle2onnx_params=========================== -model_name:ocr_det_v3 +model_name:ch_PP-OCRv3_det python:python3.7 2onnx: paddle2onnx ---model_dir:./inference/ch_PP-OCRv3_det_infer/ +--det_model_dir:./inference/ch_PP-OCRv3_det_infer/ --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---save_file:./inference/det_v3_onnx/model.onnx +--det_save_file:./inference/det_v3_onnx/model.onnx +--rec_model_dir: +--rec_save_file: --opset_version:10 --enable_onnx_checker:True inference:tools/infer/predict_det.py --use_gpu:True|False --det_model_dir: +--rec_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt index 624b13e0d5bd19483934745c477f5549f3813abc..6e2ec22cbd51e686ab64ad832559de1e2442fc98 100644 --- a/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -1,18 +1,23 @@ ===========================serving_params=========================== -model_name:ocr_det_v3 +model_name:ch_PP-OCRv3_det python:python3.7 trans_model:-m paddle_serving_client.convert ---dirname:./inference/ch_PP-OCRv3_det_infer/ +--det_dirname:./inference/ch_PP-OCRv3_det_infer/ --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---serving_server:./deploy/pdserving/ppocr_det_v3_serving/ ---serving_client:./deploy/pdserving/ppocr_det_v3_client/ +--det_serving_server:./deploy/pdserving/ppocr_det_v3_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null serving_dir:./deploy/pdserving web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" op.det.local_service_conf.devices:gpu|null -op.det.local_service_conf.use_mkldnn:True|False -op.det.local_service_conf.thread_num:1|6 -op.det.local_service_conf.use_trt:False|True -op.det.local_service_conf.precision:fp32|fp16|int8 -pipline:pipeline_rpc_client.py|pipeline_http_client.py ---image_dir:../../doc/imgs +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3_det/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv3_det/train_infer_python.txt index 93f673289a2d3a3672a61c6f69aeca49cbc74906..a69e0ab81ec6963228e9ab2e39c5bb1d730b6323 100644 --- a/test_tipc/configs/ch_PP-OCRv3_det/train_infer_python.txt +++ b/test_tipc/configs/ch_PP-OCRv3_det/train_infer_python.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv3_det +model_name:ch_PP-OCRv3_det python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:fp32 -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..7e987125a6681629a592d43f05c2ecfe51dac3f1 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:ch_PP-OCRv3_det +python:python3.7 +gpu_list:192.168.0.1,192.168.0.2;0,1 +Global.use_gpu:True +Global.auto_cast:fp32 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ +null:null +## +trainer:norm_train +norm_train:tools/train.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml -o +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml -o +quant_export:null +fpgm_export: +distill_export:null +export1:null +export2:null +inference_dir:Student +infer_model:./inference/ch_PP-OCRv3_det_infer/ +infer_export:null +infer_quant:False +inference:tools/infer/predict_det.py +--use_gpu:False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}] diff --git a/test_tipc/configs/ch_PP-OCRv3_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 98bc36a80d6c2bbd273408dfb30a43023a343981..fe72cfb4e9ec50d24b1b115eca129a0bc9534b9c 100644 --- a/test_tipc/configs/ch_PP-OCRv3_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv3_det +model_name:ch_PP-OCRv3_det python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..a34ffe22ae02c698fcc757c913d3fcadd572df2f --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv3_det_KL +use_opencv:True +infer_model:./inference/ch_PP-OCRv3_det_klquant_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +--det:True +--rec:False +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index e4a3aa6c61899adff18e69da2777f07ada8cbaaa..c27e08a64075e15e4fbd8d4ffab7001752365417 100644 --- a/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -1,5 +1,5 @@ ===========================kl_quant_params=========================== -model_name:PPOCRv3_ocr_det_kl +model_name:ch_PP-OCRv3_det_KL python:python3.7 Global.pretrained_model:null Global.save_inference_dir:null @@ -8,10 +8,10 @@ infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_PP-OCRv3/ch_ infer_quant:True inference:tools/infer/predict_det.py --use_gpu:False|True ---enable_mkldnn:True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:int8 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ diff --git a/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..22b429760ce6e83293ddaf074898002a3b0c8995 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3_det_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv3_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v3_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_kl_client/ +--rec_dirname:./inference/ch_PP-OCRv3_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_kl_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..23dbc49a388b3ff9bfe65a775bf28cf70e0d9a0b --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3_det_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv3_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v3_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_kl_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null +serving_dir:./deploy/pdserving +web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..3198b87552bc8c5e29ad7dd6e158c5b592aa82d5 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv3_det_PACT +use_opencv:True +infer_model:./inference/ch_PP-OCRv3_det_pact_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +--det:True +--rec:False +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..7d300f4456b4761e885d46c1a4f8ece916d0c2ea --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3_det_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv3_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v3_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_pact_client/ +--rec_dirname:./inference/ch_PP-OCRv3_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_pact_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..4546644cbca46a8d11069f4149c3bae8683630c2 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3_det_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv3_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v3_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_pact_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null +serving_dir:./deploy/pdserving +web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3_det_PACT/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv3_det_PACT/train_infer_python.txt index f1ea7de5e5d9d6dd7d7b2f8b4cc24f3804bde369..b536e69b05878fac3c2672a063ed7869d7a784fe 100644 --- a/test_tipc/configs/ch_PP-OCRv3_det_PACT/train_infer_python.txt +++ b/test_tipc/configs/ch_PP-OCRv3_det_PACT/train_infer_python.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv3_det_PACT +model_name:ch_PP-OCRv3_det_PACT python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:fp32 -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=1|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 6d6862607ae9569207b505caf17876e49e5554d1..252378e4dc022be24f581f319801f4fbf2a5d0eb 100644 --- a/test_tipc/configs/ch_PP-OCRv3_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv3_det_PACT +model_name:ch_PP-OCRv3_det_PACT python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml b/test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml index 4c8ba0a6fa4a355e9bad1665a8de82399f919740..f704a1dfb5dc2335c353a495dfbc0ce42cf35bf4 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml +++ b/test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml @@ -153,7 +153,7 @@ Train: data_dir: ./train_data/ic15_data/ ext_op_transform_idx: 1 label_file_list: - - ./train_data/ic15_data/rec_gt_train.txt + - ./train_data/ic15_data/rec_gt_train_lite.txt transforms: - DecodeImage: img_mode: BGR @@ -183,7 +183,7 @@ Eval: name: SimpleDataSet data_dir: ./train_data/ic15_data label_file_list: - - ./train_data/ic15_data/rec_gt_test.txt + - ./train_data/ic15_data/rec_gt_test_lite.txt transforms: - DecodeImage: img_mode: BGR diff --git a/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt index 46b1c96c923549b7113b43a206eb20f4d45d200e..9d6ca2cf5ec6413cb675389218cbb3b82770ba73 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -1,15 +1,15 @@ ===========================cpp_infer_params=========================== -model_name:ocr_rec_v3 +model_name:ch_PP-OCRv3_rec use_opencv:True infer_model:./inference/ch_PP-OCRv3_rec_infer/ infer_quant:False inference:./deploy/cpp_infer/build/ppocr --rec_img_h=48 --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:6 ---use_tensorrt:False|True ---precision:fp32|fp16 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference/ null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt index eb1cbb9044f34ee9e189fbebbf25765a5396fce3..9114c0acfd8ea41952cbc301fcd53d639de050ef 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -1,14 +1,17 @@ ===========================paddle2onnx_params=========================== -model_name:ocr_rec_v3 +model_name:ch_PP-OCRv3_rec python:python3.7 2onnx: paddle2onnx ---model_dir:./inference/ch_PP-OCRv3_rec_infer/ +--det_model_dir: --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---save_file:./inference/rec_v3_onnx/model.onnx +--det_save_file: +--rec_model_dir:./inference/ch_PP-OCRv3_rec_infer/ +--rec_save_file:./inference/rec_v3_onnx/model.onnx --opset_version:10 --enable_onnx_checker:True inference:tools/infer/predict_rec.py --rec_image_shape="3,48,320" --use_gpu:True|False +--det_model_dir: --rec_model_dir: ---image_dir:./inference/rec_inference \ No newline at end of file +--image_dir:./inference/rec_inference/ \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt index 89bde9c8ce37aa0e8881f1531d1d719c5198a6c2..f01db2e9504ffd400609f0f6556d92ea33ee49ad 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -1,18 +1,23 @@ ===========================serving_params=========================== -model_name:ocr_rec_v3 +model_name:ch_PP-OCRv3_rec python:python3.7 trans_model:-m paddle_serving_client.convert ---dirname:./inference/ch_PP-OCRv3_rec_infer/ +--det_dirname:null --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---serving_server:./deploy/pdserving/ppocr_rec_v3_serving/ ---serving_client:./deploy/pdserving/ppocr_rec_v3_client/ +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_PP-OCRv3_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_client/ serving_dir:./deploy/pdserving web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" -op.rec.local_service_conf.devices:gpu|null -op.rec.local_service_conf.use_mkldnn:False -op.rec.local_service_conf.thread_num:1|6 -op.rec.local_service_conf.use_trt:False|True -op.rec.local_service_conf.precision:fp32|fp16|int8 -pipline:pipeline_rpc_client.py|pipeline_http_client.py +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False --image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_PP-OCRv3_rec/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv3_rec/train_infer_python.txt index c333c0833061538a840f2c02d2646128ddcd11c9..1feb9d49fce69d92ef141c3a942f858fc68cfaab 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec/train_infer_python.txt +++ b/test_tipc/configs/ch_PP-OCRv3_rec/train_infer_python.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:PPOCRv3_ocr_rec +model_name:ch_PP-OCRv3_rec python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:fp32 -Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_rec.py --rec_image_shape="3,48,320" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..7fcc8b4418c65b0f98624d92bd3896518f2ed465 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:ch_PP-OCRv3_rec +python:python3.7 +gpu_list:192.168.0.1,192.168.0.2;0,1 +Global.use_gpu:True +Global.auto_cast:fp32 +Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=64 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./inference/rec_inference +null:null +## +trainer:norm_train +norm_train:tools/train.py -c test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml -o +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml -o +quant_export: +fpgm_export: +distill_export:null +export1:null +export2:null +inference_dir:Student +infer_model:./inference/ch_PP-OCRv3_rec_infer +infer_export:null +infer_quant:False +inference:tools/infer/predict_rec.py --rec_image_shape="3,48,320" +--use_gpu:False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1|6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference +null:null +--benchmark:True +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,48,320]}] diff --git a/test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 47cc3e2f5387561f758d9c89edff06b3314a26c0..99e3c4247716bdf139440e22ea80c8542b2d9830 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:PPOCRv3_ocr_rec +model_name:ch_PP-OCRv3_rec python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_rec.py --rec_image_shape="3,48,320" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 ---rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..f1a308fcc8831f4d1ab66dffc69ee3deb9ac0bc3 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv3_rec_KL +use_opencv:True +infer_model:./inference/ch_PP-OCRv3_rec_klquant_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_img_h=48 --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index 51ad29a4edf81163a027f93ef1cb7f7c3b4168fd..d1a8c7c00137661bb1b5cced46f7616877f0b0a2 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -1,17 +1,17 @@ ===========================kl_quant_params=========================== -model_name:PPOCRv3_ocr_rec_kl +model_name:ch_PP-OCRv3_rec_KL python:python3.7 -Global.pretrained_model:null +Global.pretrained_model: Global.save_inference_dir:null infer_model:./inference/ch_PP-OCRv3_rec_infer/ infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml -o infer_quant:True inference:tools/infer/predict_rec.py --rec_image_shape="3,48,320" --use_gpu:False|True ---enable_mkldnn:False|True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True +--use_tensorrt:False --precision:int8 --rec_model_dir: --image_dir:./inference/rec_inference diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..fa6f04e48c99f732624f60cba8df67783969ced5 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3_rec_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv3_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v3_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_kl_client/ +--rec_dirname:./inference/ch_PP-OCRv3_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_kl_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..68586af0d97c658c07f0ce65b8ac5af44e909592 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3_rec_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:null +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_PP-OCRv3_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_kl_client/ +serving_dir:./deploy/pdserving +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..8fc1132ca6016d78846527345528db2e003d5ad1 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_PP-OCRv3_rec_PACT +use_opencv:True +infer_model:./inference/ch_PP-OCRv3_rec_pact_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_img_h=48 --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..008df50d6d32c701ec7ce3814b2f0490916f2d7a --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3_rec_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_PP-OCRv3_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_v3_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_v3_pact_client/ +--rec_dirname:./inference/ch_PP-OCRv3_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_pact_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..826f586f0c6759f1c13a45891e9ba9c0688554e8 --- /dev/null +++ b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_PP-OCRv3_rec_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:null +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_PP-OCRv3_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_v3_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_v3_pact_client/ +serving_dir:./deploy/pdserving +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_infer_python.txt index fd7d61c372584450da3547340e32872f8840179e..24469a91cfa0fa7d26ff24dba13c9c7e78a5ca10 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_infer_python.txt +++ b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_infer_python.txt @@ -1,10 +1,10 @@ ===========================train_params=========================== -model_name:ch_PPOCRv3_rec_PACT +model_name:ch_PP-OCRv3_rec_PACT python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:fp32 -Global.epoch_num:lite_train_lite_infer=6|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 Global.pretrained_model:pretrain_models/ch_PP-OCRv3_rec_train/best_accuracy @@ -34,16 +34,16 @@ distill_export:null export1:null export2:null inference_dir:Student -infer_model:./inference/ch_PP-OCRv3_rec_slim_quant_infer +infer_model:./inference/ch_PP-OCRv3_rec_slim_infer infer_export:null infer_quant:True inference:tools/infer/predict_rec.py --rec_image_shape="3,48,320" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 6049a377a625a6cdfb411c0534b18af666b5f663..c93b307debae630fccf41f29348c0b34761c1bf6 100644 --- a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -1,13 +1,13 @@ ===========================train_params=========================== -model_name:ch_PPOCRv3_rec_PACT +model_name:ch_PP-OCRv3_rec_PACT python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 -Global.pretrained_model:null +Global.pretrained_model:pretrain_models/ch_PP-OCRv3_rec_train/best_accuracy train_model_name:latest train_infer_img_dir:./inference/rec_inference null:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:True inference:tools/infer/predict_rec.py --rec_image_shape="3,48,320" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 ---rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..b42ab9db362b0ba56d795096fdc58a645b425480 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_mobile_v2.0 +use_opencv:True +infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/ +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +--rec_model_dir:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +--benchmark:True +--det:True +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index 4a46f0cf09dcf2bb812910f0cf322dda0749b87c..becad991eab2535b2df7862d0d25707ef37f08f8 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -6,10 +6,10 @@ infer_export:null infer_quant:False inference:tools/infer/predict_system.py --use_gpu:False|True ---enable_mkldnn:False|True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..17c2fbbae2e182c4a7631cb18908180d8c019b4f --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -0,0 +1,17 @@ +===========================paddle2onnx_params=========================== +model_name:ch_ppocr_mobile_v2.0 +python:python3.7 +2onnx: paddle2onnx +--det_model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_save_file:./inference/det_mobile_onnx/model.onnx +--rec_model_dir:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +--rec_save_file:./inference/rec_mobile_onnx/model.onnx +--opset_version:10 +--enable_onnx_checker:True +inference:tools/infer/predict_system.py --rec_image_shape="3,32,320" +--use_gpu:True|False +--det_model_dir: +--rec_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..d18e9f11fdd2ff605cdd8f6c1bcf51ca780eb766 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0 +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_client/ +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..842c9340176d696c1e43e59491bdcab817f9256e --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0 +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_client/ +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_client/ +serving_dir:./deploy/pdserving +web_service:web_service.py --config=config.yml --opt op.det.concurrency="1" op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt index d0ae17ccb55f40ddf65de936ca3cfc06bdd19475..1d1c2ae283b2103c2e7282186ab1f53bec05cda3 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -1,15 +1,15 @@ ===========================cpp_infer_params=========================== -model_name:ocr_det +model_name:ch_ppocr_mobile_v2.0_det use_opencv:True infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/ infer_quant:False inference:./deploy/cpp_infer/build/ppocr --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt index 7d3f60bd42aad18c045aeee70fc60d2c17a2af13..24bb8746ab7793dbcb4af99102a007aca8b8e16b 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt @@ -1,5 +1,5 @@ ===========================infer_params=========================== -model_name:ocr_det +model_name:ch_ppocr_mobile_v2.0_det python:python infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer infer_export:null @@ -7,10 +7,10 @@ infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False --enable_mkldnn:False ---cpu_threads:1|6 +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp16|fp32 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt index 160bcdbd88661c3d795eb2faf6b93965598c3e22..00473d1062615834a42e350a727f50233efd831f 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -1,14 +1,17 @@ ===========================paddle2onnx_params=========================== -model_name:ocr_det_mobile +model_name:ch_ppocr_mobile_v2.0_det python:python3.7 2onnx: paddle2onnx ---model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/ +--det_model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/ --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---save_file:./inference/det_mobile_onnx/model.onnx +--det_save_file:./inference/det_mobile_onnx/model.onnx +--rec_model_dir: +--rec_save_file: --opset_version:10 --enable_onnx_checker:True inference:tools/infer/predict_det.py --use_gpu:True|False --det_model_dir: +--rec_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt index ed72889970f499eae45eaf401c2905f8d841e534..c9dd5ad920d58f60ce36a7b489073279f23ba1b7 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -1,18 +1,23 @@ ===========================serving_params=========================== -model_name:ocr_det_mobile -python:python3.7|cpp +model_name:ch_ppocr_mobile_v2.0_det +python:python3.7 trans_model:-m paddle_serving_client.convert ---dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/ +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/ --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---serving_server:./deploy/pdserving/ppocr_det_mobile_2.0_serving/ ---serving_client:./deploy/pdserving/ppocr_det_mobile_2.0_client/ +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null serving_dir:./deploy/pdserving web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" op.det.local_service_conf.devices:gpu|null -op.det.local_service_conf.use_mkldnn:True|False -op.det.local_service_conf.thread_num:1|6 -op.det.local_service_conf.use_trt:False|True -op.det.local_service_conf.precision:fp32|fp16|int8 -pipline:pipeline_rpc_client.py|pipeline_http_client.py ---image_dir:../../doc/imgs +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt index 269693a86e9e371d52865f48d7fbaccce5d72393..789ed4d23d9c1fa3997daceee0627218aecd4c73 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=100|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=100|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2 infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt deleted file mode 100644 index bfb71b781039493b12875ed4e99c8cd004a2e295..0000000000000000000000000000000000000000 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt +++ /dev/null @@ -1,51 +0,0 @@ -===========================train_params=========================== -model_name:ocr_det -python:python3.7 -gpu_list:xx.xx.xx.xx,yy.yy.yy.yy;0,1 -Global.use_gpu:True -Global.auto_cast:fp32|amp -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300 -Global.save_model_dir:./output/ -Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 -Global.pretrained_model:null -train_model_name:latest -train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ -null:null -## -trainer:norm_train|pact_train|fpgm_train -norm_train:tools/train.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained -pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o -fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy -distill_train:null -null:null -null:null -## -===========================eval_params=========================== -eval:null -null:null -## -===========================infer_params=========================== -Global.save_inference_dir:./output/ -Global.pretrained_model: -norm_export:tools/export_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o -quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o -fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o -distill_export:null -export1:null -export2:null -inference_dir:null -train_model:./inference/ch_ppocr_mobile_v2.0_det_train/best_accuracy -infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o -infer_quant:False -inference:tools/infer/predict_det.py ---use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 ---rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 ---det_model_dir: ---image_dir:./inference/ch_det_data_50/all-sum-510/ -null:null ---benchmark:True -null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..5271f78bb778f9e419da7f9bbbb6b4a6fafb305b --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:ch_ppocr_mobile_v2.0_det +python:python3.7 +gpu_list:192.168.0.1,192.168.0.2;0,1 +Global.use_gpu:True +Global.auto_cast:null +Global.epoch_num:lite_train_lite_infer=100|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ +null:null +## +trainer:norm_train +norm_train:tools/train.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o +quant_export:null +fpgm_export:null +distill_export:null +export1:null +export2:null +inference_dir:null +train_model:./inference/ch_ppocr_mobile_v2.0_det_train/best_accuracy +infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o +infer_quant:False +inference:tools/infer/predict_det.py +--use_gpu:False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}] \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 593e7ec7ed42af9b65c520852ff6372f89890170..6b3352f741a56124eead2f71c03c783e5c81a70d 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=100|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=100|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2 infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt index 014dad5fc9d87c08a0725f57127f8bf2cb248be3..3f321a1903cdd1076e181c4bb901f1c9dc6d7f58 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt @@ -4,7 +4,7 @@ python:python gpu_list:-1 Global.use_gpu:False Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt index 6a63b39d976c0e9693deec097c37eb0ff212d8af..a3f6933a64bd64c8f39a90f72d139ad9fada55bb 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt @@ -4,7 +4,7 @@ python:python gpu_list:0 Global.use_gpu:True Global.auto_cast:fp32|amp -Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,10 +39,10 @@ infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2 infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False +--enable_mkldnn:False --cpu_threads:1|6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:fp32|fp16|int8 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_infer_python.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_infer_python.txt index 47ccf2e69e75bc8c215be8d1837e5248d1b4b513..dae3f8053a0264611b5baca0f45839f3550fe6a4 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_infer_python.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_infer_python.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 5a95f026850b750bfadb85e0955f7426e5e73cb6..150a8a0315b83e8c62765a4aa66429cfd0590928 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..eb2fd0a001ab506f241bed7eac75d96cf4b5d5cb --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_mobile_v2.0_det_KL +use_opencv:True +infer_model:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +--det:True +--rec:False +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index 1039dcad06d63bb1fc1a47b7cc4760cd8d75ed63..2bdec848833b6cf3799370b0337fa00f185a94d5 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -8,10 +8,10 @@ infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_ppocr_v2.0/c infer_quant:True inference:tools/infer/predict_det.py --use_gpu:False|True ---enable_mkldnn:True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:int8 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..d9de1cc19a729485845601fe929bf57d74002641 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0_det_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_kl_client/ +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_kl_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..049ec784581bddcce066bc049b66f6f0ceff9eed --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0_det_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_kl_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null +serving_dir:./deploy/pdserving +web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..17723f41ab762f5316cba59c08ec719aa54f03b1 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_mobile_v2.0_det_PACT +use_opencv:True +infer_model:./inference/ch_ppocr_mobile_v2.0_det_pact_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +--det:True +--rec:False +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..1a49a10f9b9d4e32916dd35bae3380e2ca5bebb9 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0_det_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_pact_client/ +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_pact_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..909d738919bed78d6db04e238818cd4fbbb75e5f --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0_det_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_pact_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null +serving_dir:./deploy/pdserving +web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt index 9d2855d8240a7c42295e6e2439d121504d307b09..04c8d0e194b687f58da1c449a6a0d8d9c1acd25e 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=20|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 1f9bec12ada6894fcffbe697ae4da2f0df95cc62..3a5d8faf3fd60b4d94030e488538a0ba12345ee1 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=20|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..480fb16cddfc4c2f4784cc8fa88512f063f7b2ae --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_mobile_v2.0_rec +use_opencv:True +infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt index f29b303879f555eaa9a392633aed6e0095f05cfb..5bab0c9e4c77edba302f6b536306816b09df9224 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -1,14 +1,17 @@ ===========================paddle2onnx_params=========================== -model_name:ocr_rec_mobile +model_name:ch_ppocr_mobile_v2.0_rec python:python3.7 2onnx: paddle2onnx ---model_dir:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +--det_model_dir: --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---save_file:./inference/rec_mobile_onnx/model.onnx +--det_save_file: +--rec_model_dir:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +--rec_save_file:./inference/rec_mobile_onnx/model.onnx --opset_version:10 --enable_onnx_checker:True -inference:tools/infer/predict_rec.py +inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320" --use_gpu:True|False +--det_model_dir: --rec_model_dir: ---image_dir:./inference/rec_inference \ No newline at end of file +--image_dir:./inference/rec_inference/ \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt index f890eff469ba82b87d2d83000add24cc9d380c49..c0c5291cc480f9f34aa5dcded3eafce7feac89e3 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -1,18 +1,23 @@ ===========================serving_params=========================== -model_name:ocr_rec_mobile -python:python3.7|cpp +model_name:ch_ppocr_mobile_v2.0_rec +python:python3.7 trans_model:-m paddle_serving_client.convert ---dirname:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +--det_dirname:null --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---serving_server:./deploy/pdserving/ppocr_rec_mobile_2.0_serving/ ---serving_client:./deploy/pdserving/ppocr_rec_mobile_2.0_client/ +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_client/ serving_dir:./deploy/pdserving -web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency=1 -op.rec.local_service_conf.devices:"0"|null -op.rec.local_service_conf.use_mkldnn:True|False -op.rec.local_service_conf.thread_num:1|6 -op.rec.local_service_conf.use_trt:False|True -op.rec.local_service_conf.precision:fp32|fp16|int8 -pipline:pipeline_rpc_client.py|pipeline_http_client.py ---image_dir:../../doc/imgs_words_en \ No newline at end of file +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_infer_python.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_infer_python.txt index 5086f80d7bad4fb359f152cc1dc7195017aa31c3..f02b93926cac8116844142fe3ecb03959abb0530 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_infer_python.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_infer_python.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/rec/rec_icdar15_train.yml -o infer_quant:False inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..631118c0a9ab98c10129f12ec1c1cf2bbac46115 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:ch_ppocr_mobile_v2.0_rec +python:python3.7 +gpu_list:192.168.0.1,192.168.0.2;0,1 +Global.use_gpu:True +Global.auto_cast:null +Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./inference/rec_inference +null:null +## +trainer:norm_train +norm_train:tools/train.py -c configs/rec/rec_icdar15_train.yml -o +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c configs/rec/rec_icdar15_train.yml -o +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c configs/rec/rec_icdar15_train.yml -o +quant_export:null +fpgm_export:null +distill_export:null +export1:null +export2:null +## +train_model:./inference/ch_ppocr_mobile_v2.0_rec_train/best_accuracy +infer_export:tools/export_model.py -c configs/rec/rec_icdar15_train.yml -o +infer_quant:False +inference:tools/infer/predict_rec.py +--use_gpu:False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1|6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference +--save_log_path:./test/output/ +--benchmark:True +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,32,100]}] diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 30fb939bff646adf301191f88a9a499acf9c61de..bd9c4a8df2565af73b6db24636b6dd132dac0cc2 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/rec/rec_icdar15_train.yml -o infer_quant:False inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_infer_python.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_infer_python.txt index 77494ac347a73f61d18c070075db476a093c3f62..89daceeb5f4a991699a490b51358d33240e74913 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_infer_python.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_infer_python.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index fda9cf4ddec6d3ab64045a4a7fdbb62183212021..7abc3e9340fe49a2b0bf0efd5e3c370817cd4e9d 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference null:null diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..adf06257a772cfd16d4109497c6e6ef7c3f8af8b --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_mobile_v2.0_rec_KL +use_opencv:True +infer_model:./inference/ch_ppocr_mobile_v2.0_rec_klquant_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index 4b77994f3f68c196b4d6e7a16eb44ec5fdef0d9e..f63fe4c2bb6a17353ecb008d83e2bee9d38aec23 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -6,12 +6,12 @@ Global.save_inference_dir:null infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/ infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/rec_chinese_lite_train_v2.0.yml -o infer_quant:True -inference:tools/infer/predict_rec.py +inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320" --use_gpu:False|True ---enable_mkldnn:True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:int8 --rec_model_dir: --image_dir:./inference/rec_inference diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..ab518de55ae6b157b26bf332ec3b0afcab71f97a --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0_rec_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_kl_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_kl_client/ +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_kl_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..948e3dceb3ef7e3f2199be5e417cfc5fc763d975 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0_rec_KL +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:null +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_klquant_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_kl_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_kl_client/ +serving_dir:./deploy/pdserving +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..ba2df90f75d2c70e043c45ea19d681aabc2b6fb2 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_mobile_v2.0_rec_PACT +use_opencv:True +infer_model:./inference/ch_ppocr_mobile_v2.0_rec_pact_infer +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..229f70cf353318bf9ccc81f4e5be79dbc096de25 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0_rec_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_mobile_pact_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_mobile_pact_client/ +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_pact_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..f123f365432ab68f2484cc11dd9ef94c8a60ea8e --- /dev/null +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_ppocr_mobile_v2.0_rec_PACT +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:null +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_ppocr_mobile_v2.0_rec_pact_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_mobile_pact_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_mobile_pact_client/ +serving_dir:./deploy/pdserving +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_infer_python.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_infer_python.txt index 94909ec340c1bbc582dd60aa947f1905580b8966..77472fbdfb21c81bb713df175a135ccf9e652f25 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_infer_python.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_infer_python.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128 Global.checkpoints:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_image_shape="3,32,100" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index abed3cfba9b3f8c0ed626dbfcbda8621d8787001..a1a2a8e63dae5122d540d96a802fdebd75f554ea 100644 --- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128 Global.checkpoints:null @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_image_shape="3,32,100" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:False|True ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..7c980b2baeef7161a93dea360089b333f2003a31 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_server_v2.0 +use_opencv:True +infer_model:./inference/ch_ppocr_server_v2.0_det_infer/ +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +--rec_model_dir:./inference/ch_ppocr_server_v2.0_rec_infer/ +--benchmark:True +--det:True +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt index 92d7031e884d10df3a5c98bf675d64d63b3cb335..b20596f7a1db6da04307a7e527ef596477d237d3 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -6,8 +6,8 @@ infer_export:null infer_quant:True inference:tools/infer/predict_system.py --use_gpu:False|True ---enable_mkldnn:False|True ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 --use_tensorrt:False --precision:fp32 diff --git a/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..e478896a54957481a3ce4c485ac02cd7979233dc --- /dev/null +++ b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -0,0 +1,17 @@ +===========================paddle2onnx_params=========================== +model_name:ch_ppocr_server_v2.0 +python:python3.7 +2onnx: paddle2onnx +--det_model_dir:./inference/ch_ppocr_server_v2.0_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_save_file:./inference/det_server_onnx/model.onnx +--rec_model_dir:./inference/ch_ppocr_server_v2.0_rec_infer/ +--rec_save_file:./inference/rec_server_onnx/model.onnx +--opset_version:10 +--enable_onnx_checker:True +inference:tools/infer/predict_system.py --rec_image_shape="3,32,320" +--use_gpu:True|False +--det_model_dir: +--rec_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/00008790.jpg \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..bbfec44dbab08dcfb932a922797448e541ea385b --- /dev/null +++ b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt @@ -0,0 +1,19 @@ +===========================serving_params=========================== +model_name:ch_ppocr_server_v2.0 +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_server_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_server_client/ +--rec_dirname:./inference/ch_ppocr_server_v2.0_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_server_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_server_client/ +serving_dir:./deploy/pdserving +web_service:-m paddle_serving_server.serve +--op:GeneralDetectionOp GeneralInferOp +--port:8181 +--gpu_id:"0"|null +cpp_client:ocr_cpp_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..8853e709d40a0fba6bedd7ce582425e39b9076ed --- /dev/null +++ b/test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -0,0 +1,23 @@ +===========================serving_params=========================== +model_name:ch_ppocr_server_v2.0 +python:python3.7 +trans_model:-m paddle_serving_client.convert +--det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/ +--model_filename:inference.pdmodel +--params_filename:inference.pdiparams +--det_serving_server:./deploy/pdserving/ppocr_det_server_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_server_client/ +--rec_dirname:./inference/ch_ppocr_server_v2.0_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_server_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_server_client/ +serving_dir:./deploy/pdserving +web_service:web_service.py --config=config.yml --opt op.det.concurrency="1" op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..69ae939e2b6cab5e07bc4e401a83c66324754223 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_server_v2.0_det +use_opencv:True +infer_model:./inference/ch_ppocr_server_v2.0_det_infer/ +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +null:null +--benchmark:True +--det:True +--rec:False +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt index 40fdc11241f3ac966ff01d4c51173f990cc594c5..c8bebf54f2ed2627cce9a22013d1566eb7a7b6ef 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -1,14 +1,17 @@ ===========================paddle2onnx_params=========================== -model_name:ocr_det_server +model_name:ch_ppocr_server_v2.0_det python:python3.7 2onnx: paddle2onnx ---model_dir:./inference/ch_ppocr_server_v2.0_det_infer/ +--det_model_dir:./inference/ch_ppocr_server_v2.0_det_infer/ --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---save_file:./inference/det_server_onnx/model.onnx +--det_save_file:./inference/det_server_onnx/model.onnx +--rec_model_dir: +--rec_save_file: --opset_version:10 --enable_onnx_checker:True inference:tools/infer/predict_det.py --use_gpu:True|False --det_model_dir: ---image_dir:./inference/det_inference \ No newline at end of file +--rec_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/00008790.jpg \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt index ec5464604697e15bdd4e0f7282d23a8e09f4a0b5..018dd1a227064479ebd60570113b122b035e7704 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -1,18 +1,23 @@ ===========================serving_params=========================== -model_name:ocr_det_server -python:python3.7|cpp +model_name:ch_ppocr_server_v2.0_det +python:python3.7 trans_model:-m paddle_serving_client.convert ---dirname:./inference/ch_ppocr_server_v2.0_det_infer/ +--det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/ --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---serving_server:./deploy/pdserving/ppocr_det_server_2.0_serving/ ---serving_client:./deploy/pdserving/ppocr_det_server_2.0_client/ +--det_serving_server:./deploy/pdserving/ppocr_det_server_serving/ +--det_serving_client:./deploy/pdserving/ppocr_det_server_client/ +--rec_dirname:null +--rec_serving_server:null +--rec_serving_client:null serving_dir:./deploy/pdserving -web_service:web_service_det.py --config=config.yml --opt op.det.concurrency=1 -op.det.local_service_conf.devices:"0"|null -op.det.local_service_conf.use_mkldnn:True|False -op.det.local_service_conf.thread_num:1|6 -op.det.local_service_conf.use_trt:False|True -op.det.local_service_conf.precision:fp32|fp16|int8 -pipline:pipeline_rpc_client.py|pipeline_http_client.py ---image_dir:../../doc/imgs \ No newline at end of file +web_service:web_service_det.py --config=config.yml --opt op.det.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py +--image_dir:../../doc/imgs/1.jpg diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_det/train_infer_python.txt b/test_tipc/configs/ch_ppocr_server_v2.0_det/train_infer_python.txt index 52489fe5298dbeba31ff0ff5abe03c0c49b46e0a..c16ca150029d03052396ca28a6396520e63b3f84 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0_det/train_infer_python.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0_det/train_infer_python.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_lite_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_res18_db_ infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --save_log_path:null diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..12388d967755c54a46efdb915ef047896dddaef7 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:ch_ppocr_server_v2.0_det +python:python3.7 +gpu_list:192.168.0.1,192.168.0.2;0,1 +Global.use_gpu:True +Global.auto_cast:null +Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_lite_infer=4 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ +null:null +## +trainer:norm_train +norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o +quant_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o +quant_export:null +fpgm_export:null +distill_export:null +export1:null +export2:null +## +train_model:./inference/ch_ppocr_server_v2.0_det_train/best_accuracy +infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml -o +infer_quant:False +inference:tools/infer/predict_det.py +--use_gpu:False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--det_model_dir: +--image_dir:./inference/ch_det_data_50/all-sum-510/ +--save_log_path:null +--benchmark:True +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}] \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 3e3764e8c6f62c72ffb8ceb268c8ceee660d02de..93ed14cb600229e744167f26573cba406880db8e 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:amp -Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=300 +Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_lite_infer=4 Global.pretrained_model:null @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_res18_db_ infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --save_log_path:null diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..cbec272cce544e332fd908d4946321a15543fcae --- /dev/null +++ b/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt @@ -0,0 +1,20 @@ +===========================cpp_infer_params=========================== +model_name:ch_ppocr_server_v2.0_rec +use_opencv:True +infer_model:./inference/ch_ppocr_server_v2.0_rec_infer/ +infer_quant:False +inference:./deploy/cpp_infer/build/ppocr --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_img_h=32 +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference/ +null:null +--benchmark:True +--det:False +--rec:True +--cls:False +--use_angle_cls:False \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt index 05542332e94eab38d8a433a727e04bf0be15f423..462f6090d987ac2c58656136e896e71bcdc3bee1 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt @@ -1,14 +1,17 @@ ===========================paddle2onnx_params=========================== -model_name:ocr_rec_server +model_name:ch_ppocr_server_v2.0_rec python:python3.7 2onnx: paddle2onnx ---model_dir:./inference/ch_ppocr_server_v2.0_rec_infer/ +--det_model_dir: --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---save_file:./inference/rec_server_onnx/model.onnx +--det_save_file: +--rec_model_dir:./inference/ch_ppocr_server_v2.0_rec_infer/ +--rec_save_file:./inference/rec_server_onnx/model.onnx --opset_version:10 --enable_onnx_checker:True -inference:tools/infer/predict_rec.py +inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320" --use_gpu:True|False +--det_model_dir: --rec_model_dir: ---image_dir:./inference/rec_inference \ No newline at end of file +--image_dir:./inference/rec_inference/ \ No newline at end of file diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt index d72abc6054d5f2eccf35f305076b7062fdf49848..7f456320b687549fbcd6d4f0be7a1b4a2969684a 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt @@ -1,18 +1,23 @@ ===========================serving_params=========================== -model_name:ocr_rec_server -python:python3.7|cpp +model_name:ch_ppocr_server_v2.0_rec +python:python3.7 trans_model:-m paddle_serving_client.convert ---dirname:./inference/ch_ppocr_server_v2.0_rec_infer/ +--det_dirname:null --model_filename:inference.pdmodel --params_filename:inference.pdiparams ---serving_server:./deploy/pdserving/ppocr_rec_server_2.0_serving/ ---serving_client:./deploy/pdserving/ppocr_rec_server_2.0_client/ +--det_serving_server:null +--det_serving_client:null +--rec_dirname:./inference/ch_ppocr_server_v2.0_rec_infer/ +--rec_serving_server:./deploy/pdserving/ppocr_rec_server_serving/ +--rec_serving_client:./deploy/pdserving/ppocr_rec_server_client/ serving_dir:./deploy/pdserving -web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency=1 -op.rec.local_service_conf.devices:"0"|null -op.rec.local_service_conf.use_mkldnn:True|False -op.rec.local_service_conf.thread_num:1|6 -op.rec.local_service_conf.use_trt:False|True -op.rec.local_service_conf.precision:fp32|fp16|int8 -pipline:pipeline_rpc_client.py|pipeline_http_client.py ---image_dir:../../doc/imgs_words_en \ No newline at end of file +web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency="1" +op.det.local_service_conf.devices:gpu|null +op.det.local_service_conf.use_mkldnn:False +op.det.local_service_conf.thread_num:6 +op.det.local_service_conf.use_trt:False +op.det.local_service_conf.precision:fp32 +op.det.local_service_conf.model_config: +op.rec.local_service_conf.model_config: +pipline:pipeline_http_client.py --det=False +--image_dir:../../inference/rec_inference diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_infer_python.txt b/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_infer_python.txt index 78a046c503686762688ce08097d68479f1023879..64c0cf455cdd058d1840a9ad1f86954293d2e219 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_infer_python.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec infer_quant:False inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..9884ab247b80de4ca700bf084cea4faa89c86396 --- /dev/null +++ b/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:ch_ppocr_server_v2.0_rec +python:python3.7 +gpu_list:192.168.0.1,192.168.0.2;0,1 +Global.use_gpu:True +Global.auto_cast:null +Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=100 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./inference/rec_inference +null:null +## +trainer:norm_train +norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o +quant_export:null +fpgm_export:null +distill_export:null +export1:null +export2:null +## +train_model:./inference/ch_ppocr_server_v2.0_rec_train/best_accuracy +infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o +infer_quant:False +inference:tools/infer/predict_rec.py +--use_gpu:False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1|6 +--use_tensorrt:False +--precision:fp32 +--rec_model_dir: +--image_dir:./inference/rec_inference +--save_log_path:./test/output/ +--benchmark:True +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,32,100]}] diff --git a/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt index 78c15047fb522127075591cc9687392af77a300a..63ddaa4a8b2dcb19823034ee85af14b248b109b2 100644 --- a/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +++ b/test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec infer_quant:False inference:tools/infer/predict_rec.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/det_mv3_db_v2_0/train_infer_python.txt b/test_tipc/configs/det_mv3_db_v2_0/train_infer_python.txt index fab8f50d5451f90183d02e30c6529d63af42fe7f..ab3aa59b601db58b48cf18de79f77710611e2596 100644 --- a/test_tipc/configs/det_mv3_db_v2_0/train_infer_python.txt +++ b/test_tipc/configs/det_mv3_db_v2_0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/det_mv3_east_v2.0/train_infer_python.txt b/test_tipc/configs/det_mv3_east_v2.0/train_infer_python.txt index 5634297973bafbdad6c168e369d15520db09aba3..1ec1597a4d50ba1c41cfb076fa7431f170e183bf 100644 --- a/test_tipc/configs/det_mv3_east_v2.0/train_infer_python.txt +++ b/test_tipc/configs/det_mv3_east_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/det_mv3_east_v2.0/det_mv infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 --use_tensorrt:False ---precision:fp32|fp16|int8 +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --save_log_path:null diff --git a/test_tipc/configs/det_mv3_pse_v2.0/train_infer_python.txt b/test_tipc/configs/det_mv3_pse_v2.0/train_infer_python.txt index 661adc4a324e0d51846d05d52a4cf1862661c095..daeec69f84a766e1d6cd2f8906772c27f5f8d048 100644 --- a/test_tipc/configs/det_mv3_pse_v2.0/train_infer_python.txt +++ b/test_tipc/configs/det_mv3_pse_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/det_mv3_pse_v2.0/det_mv3 infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 --use_tensorrt:False ---precision:fp32|fp16 +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --save_log_path:null diff --git a/test_tipc/configs/det_r18_vd_db_v2_0/train_infer_python.txt b/test_tipc/configs/det_r18_vd_db_v2_0/train_infer_python.txt index 77023ef2c18ba1a189b8b066773370c8bb060d87..33e4dbf2337f3799328516119a213bc0f14af9fe 100644 --- a/test_tipc/configs/det_r18_vd_db_v2_0/train_infer_python.txt +++ b/test_tipc/configs/det_r18_vd_db_v2_0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:null infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --save_log_path:null diff --git a/test_tipc/configs/det_r50_db_v2.0/train_infer_python.txt b/test_tipc/configs/det_r50_db_v2.0/train_infer_python.txt index 3fd875711e03f1c31db0948e68f573ba7e113b51..151f2769cc2d97d6a3546f338383dd811aa06ace 100644 --- a/test_tipc/configs/det_r50_db_v2.0/train_infer_python.txt +++ b/test_tipc/configs/det_r50_db_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/det/det_r50_vd_db.yml -o infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 +--use_tensorrt:False +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --save_log_path:null diff --git a/test_tipc/configs/det_r50_vd_east_v2_0/train_infer_python.txt b/test_tipc/configs/det_r50_vd_east_v2_0/train_infer_python.txt index c1748c5d2fca9690926f6645205084fb9a858185..8477a4fa74f7a0617104aa83617fc6f61b8234b3 100644 --- a/test_tipc/configs/det_r50_vd_east_v2_0/train_infer_python.txt +++ b/test_tipc/configs/det_r50_vd_east_v2_0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_east_v2_0/det infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 --use_tensorrt:False ---precision:fp32|fp16|int8 +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --save_log_path:null diff --git a/test_tipc/configs/det_r50_vd_pse_v2_0/train_infer_python.txt b/test_tipc/configs/det_r50_vd_pse_v2_0/train_infer_python.txt index 55ebcd3547b2e92c86e1c0007e0a1bcb9758cced..62da89fe1c8e3a7c2b7586eae6b2589f94237a2e 100644 --- a/test_tipc/configs/det_r50_vd_pse_v2_0/train_infer_python.txt +++ b/test_tipc/configs/det_r50_vd_pse_v2_0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_pse_v2_0/det_ infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 --use_tensorrt:False ---precision:fp32|fp16|int8 +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ --save_log_path:null diff --git a/test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/train_infer_python.txt b/test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/train_infer_python.txt index 16f37ace6fbc469cdd6fd2928e26978508a0841f..b70ef46b4afb3a39f3bbd3d6274f0135a0646a37 100644 --- a/test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/train_infer_python.txt +++ b/test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/train_infer_python.txt @@ -4,16 +4,16 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=5000 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 -Global.pretrained_model:null +Global.pretrained_model:./pretrain_models/det_r50_vd_sast_icdar15_v2.0_train/best_accuracy train_model_name:latest train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ null:null ## trainer:norm_train -norm_train:tools/train.py -c test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml -o Global.pretrained_model=./pretrain_models/ResNet50_vd_ssld_pretrained +norm_train:tools/train.py -c test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml -o pact_train:null fpgm_train:null distill_train:null @@ -39,13 +39,13 @@ infer_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_icdar15_ infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 --use_tensorrt:False ---precision:fp32|int8 +--precision:fp32 --det_model_dir: ---image_dir:./inference/ch_det_data_50/all-sum-510/ +--image_dir:./inference/ch_det_data_50/all-sum-510/00008790.jpg null:null --benchmark:True --det_algorithm:SAST diff --git a/test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/train_infer_python.txt b/test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/train_infer_python.txt index 5e4c5666b7b90b754c77153612661aa5e01f4cb2..7be5af7ddee0ed0f688980f5d5dca5a99c9705a0 100644 --- a/test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/train_infer_python.txt +++ b/test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_totaltex infer_quant:False inference:tools/infer/predict_det.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 --use_tensorrt:False ---precision:fp32|int8 +--precision:fp32 --det_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/en_server_pgnetA/train_infer_python.txt b/test_tipc/configs/en_server_pgnetA/train_infer_python.txt index 8a1509baab46d4c52c56b3afbaf23350adc86584..a9dd4e676bf607d654b40f1f5ff21ec735bc9d40 100644 --- a/test_tipc/configs/en_server_pgnetA/train_infer_python.txt +++ b/test_tipc/configs/en_server_pgnetA/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c configs/e2e/e2e_r50_vd_pg.yml -o infer_quant:False inference:tools/infer/predict_e2e.py --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1 --use_tensorrt:False ---precision:fp32|fp16|int8 +--precision:fp32 --e2e_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ null:null diff --git a/test_tipc/configs/en_table_structure/table_mv3.yml b/test_tipc/configs/en_table_structure/table_mv3.yml new file mode 100755 index 0000000000000000000000000000000000000000..adf326bd02aeff4683c8f37a704125b4e426efa9 --- /dev/null +++ b/test_tipc/configs/en_table_structure/table_mv3.yml @@ -0,0 +1,117 @@ +Global: + use_gpu: true + epoch_num: 10 + log_smooth_window: 20 + print_batch_step: 5 + save_model_dir: ./output/table_mv3/ + save_epoch_step: 3 + # evaluation is run every 400 iterations after the 0th iteration + eval_batch_step: [0, 400] + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: doc/table/table.jpg + # for data or label process + character_dict_path: ppocr/utils/dict/table_structure_dict.txt + character_type: en + max_text_length: 100 + max_elem_length: 800 + max_cell_num: 500 + infer_mode: False + process_total_num: 0 + process_cut_num: 0 + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + clip_norm: 5.0 + lr: + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0.00000 + +Architecture: + model_type: table + algorithm: TableAttn + Backbone: + name: MobileNetV3 + scale: 1.0 + model_name: large + Head: + name: TableAttentionHead + hidden_size: 256 + l2_decay: 0.00001 + loc_type: 2 + max_text_length: 100 + max_elem_length: 800 + max_cell_num: 500 + +Loss: + name: TableAttentionLoss + structure_weight: 100.0 + loc_weight: 10000.0 + +PostProcess: + name: TableLabelDecode + +Metric: + name: TableMetric + main_indicator: acc + +Train: + dataset: + name: PubTabDataSet + data_dir: ./train_data/pubtabnet/train + label_file_path: ./train_data/pubtabnet/train.jsonl + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - ResizeTableImage: + max_len: 488 + - TableLabelEncode: + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - PaddingTableImage: + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'structure', 'bbox_list', 'sp_tokens', 'bbox_list_mask'] + loader: + shuffle: True + batch_size_per_card: 32 + drop_last: True + num_workers: 1 + +Eval: + dataset: + name: PubTabDataSet + data_dir: ./train_data/pubtabnet/test/ + label_file_path: ./train_data/pubtabnet/test.jsonl + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - ResizeTableImage: + max_len: 488 + - TableLabelEncode: + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - PaddingTableImage: + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'structure', 'bbox_list', 'sp_tokens', 'bbox_list_mask'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 16 + num_workers: 1 diff --git a/test_tipc/configs/en_table_structure/train_infer_python.txt b/test_tipc/configs/en_table_structure/train_infer_python.txt new file mode 100644 index 0000000000000000000000000000000000000000..d9f3b30e16c75281a929130d877b947a23c16190 --- /dev/null +++ b/test_tipc/configs/en_table_structure/train_infer_python.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:en_table_structure +python:python3.7 +gpu_list:0|0,1 +Global.use_gpu:True|True +Global.auto_cast:fp32 +Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 +Global.pretrained_model:./pretrain_models/en_ppocr_mobile_v2.0_table_structure_train/best_accuracy +train_model_name:latest +train_infer_img_dir:./ppstructure/docs/table/table.jpg +null:null +## +trainer:norm_train +norm_train:tools/train.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +quant_export: +fpgm_export: +distill_export:null +export1:null +export2:null +## +infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer +infer_export:null +infer_quant:False +inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--table_model_dir: +--image_dir:./ppstructure/docs/table/table.jpg +null:null +--benchmark:False +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,488,488]}] diff --git a/test_tipc/configs/en_table_structure/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/en_table_structure/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..31ac1ed53f2adc9810bc4fd2cf4f874d89d49606 --- /dev/null +++ b/test_tipc/configs/en_table_structure/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:en_table_structure +python:python3.7 +gpu_list:0|0,1 +Global.use_gpu:True|True +Global.auto_cast:amp +Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 +Global.pretrained_model:./pretrain_models/en_ppocr_mobile_v2.0_table_structure_train/best_accuracy +train_model_name:latest +train_infer_img_dir:./ppstructure/docs/table/table.jpg +null:null +## +trainer:norm_train +norm_train:tools/train.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +pact_train:null +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:tools/export_model.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +quant_export: +fpgm_export: +distill_export:null +export1:null +export2:null +## +infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer +infer_export:null +infer_quant:False +inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--table_model_dir: +--image_dir:./ppstructure/docs/table/table.jpg +null:null +--benchmark:False +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,488,488]}] diff --git a/test_tipc/configs/en_table_structure_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/en_table_structure_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..e8f7bbaa50417b97f79596634677fff0a95cb47f --- /dev/null +++ b/test_tipc/configs/en_table_structure_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,21 @@ +===========================train_params=========================== +model_name:en_table_structure_KL +python:python3.7 +Global.pretrained_model: +Global.save_inference_dir:null +infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer/ +infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +infer_quant:True +inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:int8 +--table_model_dir: +--image_dir:./ppstructure/docs/table/table.jpg +null:null +--benchmark:False +null:null +null:null diff --git a/test_tipc/configs/en_table_structure_PACT/train_infer_python.txt b/test_tipc/configs/en_table_structure_PACT/train_infer_python.txt new file mode 100644 index 0000000000000000000000000000000000000000..f62e8b68bc6c1af06a65a8dfb438d5d63576e123 --- /dev/null +++ b/test_tipc/configs/en_table_structure_PACT/train_infer_python.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:en_table_structure_PACT +python:python3.7 +gpu_list:0|0,1 +Global.use_gpu:True|True +Global.auto_cast:fp32 +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 +Global.pretrained_model:./pretrain_models/en_ppocr_mobile_v2.0_table_structure_train/best_accuracy +train_model_name:latest +train_infer_img_dir:./ppstructure/docs/table/table.jpg +null:null +## +trainer:pact_train +norm_train:null +pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:null +quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +fpgm_export: +distill_export:null +export1:null +export2:null +## +infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer +infer_export:null +infer_quant:True +inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--table_model_dir: +--image_dir:./ppstructure/docs/table/table.jpg +null:null +--benchmark:False +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,488,488]}] diff --git a/test_tipc/configs/en_table_structure_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/en_table_structure_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..d7c847fcdc26834c96f033caa3ba97d323439445 --- /dev/null +++ b/test_tipc/configs/en_table_structure_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,53 @@ +===========================train_params=========================== +model_name:en_table_structure_PACT +python:python3.7 +gpu_list:0|0,1 +Global.use_gpu:True|True +Global.auto_cast:amp +Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128 +Global.pretrained_model:./pretrain_models/en_ppocr_mobile_v2.0_table_structure_train/best_accuracy +train_model_name:latest +train_infer_img_dir:./ppstructure/docs/table/table.jpg +null:null +## +trainer:pact_train +norm_train:null +pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:null +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.checkpoints: +norm_export:null +quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o +fpgm_export: +distill_export:null +export1:null +export2:null +## +infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer +infer_export:null +infer_quant:True +inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table +--use_gpu:True|False +--enable_mkldnn:False +--cpu_threads:6 +--rec_batch_num:1 +--use_tensorrt:False +--precision:fp32 +--table_model_dir: +--image_dir:./ppstructure/docs/table/table.jpg +null:null +--benchmark:False +null:null +===========================infer_benchmark_params========================== +random_infer_input:[{float32,[3,488,488]}] diff --git a/test_tipc/configs/rec_mtb_nrtr/train_infer_python.txt b/test_tipc/configs/rec_mtb_nrtr/train_infer_python.txt index de6de5a0caa36fb3ff89d8dbf5c7ff8b7965ca7f..fed8ba26753bb770e062f751a9ba1e8e35fc6843 100644 --- a/test_tipc/configs/rec_mtb_nrtr/train_infer_python.txt +++ b/test_tipc/configs/rec_mtb_nrtr/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_mtb_nrtr/rec_mtb_nrt infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/EN_symbol_dict.txt --rec_image_shape="1,32,100" --rec_algorithm="NRTR" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/train_infer_python.txt b/test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/train_infer_python.txt index e67dd1509054b34bfac6a36eaaca16fa31c0f1a0..39bf9227902480ffe4ed37d454c21d6a163c41bd 100644 --- a/test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/train_infer_python.txt +++ b/test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_ infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_mv3_none_none_ctc_v2.0/train_infer_python.txt b/test_tipc/configs/rec_mv3_none_none_ctc_v2.0/train_infer_python.txt index aa3e88d284fe557c109cb8d794e2caecbec7a7ee..593de3ff20aa9890e7d9a02a9e5ca5b130e5a266 100644 --- a/test_tipc/configs/rec_mv3_none_none_ctc_v2.0/train_infer_python.txt +++ b/test_tipc/configs/rec_mv3_none_none_ctc_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2 infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/train_infer_python.txt b/test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/train_infer_python.txt index c22767c60fa8294aa244536b4c04135f7f7ade02..1b2d9abb0f00467ce92c4f51f97c283bc3e85c5e 100644 --- a/test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/train_infer_python.txt +++ b/test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="RARE" --min_subgraph_size=5 --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/train_infer_python.txt b/test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/train_infer_python.txt index 7a3096eb1e3a94bf3967a80d49b622603ae06ff8..1367c7abd4c9ca5b0c6f1eb291dd2af8d9fa4de4 100644 --- a/test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/train_infer_python.txt +++ b/test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="StarNet" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_r31_sar/train_infer_python.txt b/test_tipc/configs/rec_r31_sar/train_infer_python.txt index 1a32a3d507d8923a8b51be726c7624ea2049ae14..03ec54abb65ac41d3b5ad4f6e2fdcf7abb34c344 100644 --- a/test_tipc/configs/rec_r31_sar/train_infer_python.txt +++ b/test_tipc/configs/rec_r31_sar/train_infer_python.txt @@ -38,12 +38,12 @@ train_model:./inference/rec_r31_sar_train/best_accuracy infer_export:tools/export_model.py -c test_tipc/configs/rec_r31_sar/rec_r31_sar.yml -o infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/dict90.txt --rec_image_shape="3,48,48,160" --rec_algorithm="SAR" ---use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--use_gpu:True +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/train_infer_python.txt b/test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/train_infer_python.txt index 02cea56fbe922bb94cceb77c079371f180cac618..46aa3d719051a4f124583f88709026569d95c1c7 100644 --- a/test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/train_infer_python.txt +++ b/test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_bilstm_c infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/train_infer_python.txt b/test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/train_infer_python.txt index 5e7c1d34314cfc8aab1c97d5f6e74b0dd75f496a..3e066d7b72a6a707322b3aabe41ca6d698496433 100644 --- a/test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/train_infer_python.txt +++ b/test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_none_ctc infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/train_infer_python.txt b/test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/train_infer_python.txt index 55e937881bec1852fade4f99d81a319b8b2c5b67..1e4f46633efbf36fc78ed2beb7ed883d1483b3b0 100644 --- a/test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/train_infer_python.txt +++ b/test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_at infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="RARE" --min_subgraph_size=5 --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/train_infer_python.txt b/test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/train_infer_python.txt index 5b5ba0fd01c02b3b16d147edaf93495aeeaab7bf..9e795b66453039696ed5eedb92fba5e25150413c 100644 --- a/test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/train_infer_python.txt +++ b/test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ct infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="StarNet" --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/configs/rec_r50_fpn_vd_none_srn/train_infer_python.txt b/test_tipc/configs/rec_r50_fpn_vd_none_srn/train_infer_python.txt index 4877512b689ec87b7b2cd0258a2fac706968322b..b5a5286010a5830dc23031b3e0885247fb6ae53f 100644 --- a/test_tipc/configs/rec_r50_fpn_vd_none_srn/train_infer_python.txt +++ b/test_tipc/configs/rec_r50_fpn_vd_none_srn/train_infer_python.txt @@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_r50_fpn_vd_none_srn/ infer_quant:False inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="1,64,256" --rec_algorithm="SRN" --use_space_char=False --min_subgraph_size=3 --use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 +--enable_mkldnn:False +--cpu_threads:6 --rec_batch_num:1|6 ---use_tensorrt:True|False ---precision:fp32|int8 +--use_tensorrt:False +--precision:fp32 --rec_model_dir: --image_dir:./inference/rec_inference --save_log_path:./test/output/ diff --git a/test_tipc/docs/test_serving.md b/test_tipc/docs/test_serving.md index 8600eff3b95b1fec7d0519c1d26cf2a3232b59e5..71f01c0d5ff47004d70baa17b404c10714a6fb64 100644 --- a/test_tipc/docs/test_serving.md +++ b/test_tipc/docs/test_serving.md @@ -1,6 +1,6 @@ # PaddleServing预测功能测试 -PaddleServing预测功能测试的主程序为`test_serving.sh`,可以测试基于PaddleServing的部署功能。 +PaddleServing预测功能测试的主程序为`test_serving_infer_python.sh`和`test_serving_infer_cpp.sh`,可以测试基于PaddleServing的部署功能。 ## 1. 测试结论汇总 @@ -17,13 +17,23 @@ PaddleServing预测功能测试的主程序为`test_serving.sh`,可以测试 运行环境配置请参考[文档](./install.md)的内容配置TIPC的运行环境。 ### 2.1 功能测试 -先运行`prepare.sh`准备数据和模型,然后运行`test_serving.sh`进行测试,最终在```test_tipc/output```目录下生成`serving_infer_*.log`后缀的日志文件。 +**python serving** +先运行`prepare.sh`准备数据和模型,然后运行`test_serving_infer_python.sh`进行测试,最终在```test_tipc/output```目录下生成`serving_infer_python*.log`后缀的日志文件。 ```shell bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt "serving_infer" # 用法: -bash test_tipc/test_serving.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt +bash test_tipc/test_serving_infer_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt "serving_infer" +``` +**cpp serving** +先运行`prepare.sh`准备数据和模型,然后运行`test_serving_infer_cpp.sh`进行测试,最终在```test_tipc/output```目录下生成`serving_infer_cpp*.log`后缀的日志文件。 + +```shell +bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt "serving_infer" + +# 用法: +bash test_tipc/test_serving_infer_cpp.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt "serving_infer" ``` #### 运行结果 diff --git a/test_tipc/docs/test_train_fleet_inference_python.md b/test_tipc/docs/test_train_fleet_inference_python.md new file mode 100644 index 0000000000000000000000000000000000000000..9fddb5d1634b452f1906a83bca4157dbaec47c81 --- /dev/null +++ b/test_tipc/docs/test_train_fleet_inference_python.md @@ -0,0 +1,107 @@ +# Linux GPU/CPU 多机多卡训练推理测试 + +Linux GPU/CPU 多机多卡训练推理测试的主程序为`test_train_inference_python.sh`,可以测试基于Python的模型训练、评估、推理等基本功能。 + +## 1. 测试结论汇总 + +- 训练相关: + +| 算法名称 | 模型名称 | 多机多卡 | +| :----: | :----: | :----: | +| PP-OCRv3 | ch_PP-OCRv3_rec | 分布式训练 | + + +- 推理相关: + +| 算法名称 | 模型名称 | device_CPU | device_GPU | batchsize | +| :----: | :----: | :----: | :----: | :----: | +| PP-OCRv3 | ch_PP-OCRv3_rec | 支持 | - | 1/6 | + + +## 2. 测试流程 + +运行环境配置请参考[文档](./install.md)的内容配置TIPC的运行环境。 + +### 2.1 功能测试 + +#### 2.1.1 修改配置文件 + +首先,修改配置文件中的`ip`设置: 假设两台机器的`ip`地址分别为`192.168.0.1`和`192.168.0.2`,则对应的配置文件`gpu_list`字段需要修改为`gpu_list:192.168.0.1,192.168.0.2;0,1`; `ip`地址查看命令为`ifconfig`。 + + +#### 2.1.2 准备数据 + +运行`prepare.sh`准备数据和模型,以配置文件`test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt`为例,数据准备命令如下所示。 + +```shell +bash test_tipc/prepare.sh test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt lite_train_lite_infer +``` + +**注意:** 由于是多机训练,这里需要在所有的节点上均运行启动上述命令,准备数据。 + +#### 2.1.3 修改起始端口并开始测试 + +在多机的节点上使用下面的命令设置分布式的起始端口(否则后面运行的时候会由于无法找到运行端口而hang住),一般建议设置在`10000~20000`之间。 + +```shell +export FLAGS_START_PORT=17000 +``` + +以配置文件`test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt`为例,测试方法如下所示。 + +```shell +bash test_tipc/test_train_inference_python.sh test_tipc/configs/ch_PP-OCRv3_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt lite_train_lite_infer +``` + +**注意:** 由于是多机训练,这里需要在所有的节点上均运行启动上述命令进行测试。 + + +#### 2.1.4 输出结果 + +输出结果如下,表示命令运行成功。 + +```bash + Run successfully with command - ch_PP-OCRv3_rec - python3.7 -m paddle.distributed.launch --ips=192.168.0.1,192.168.0.2 --gpus=0,1 tools/train.py -c test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml -o Global.use_gpu=True Global.save_model_dir=./test_tipc/output/ch_PP-OCRv3_rec/lite_train_lite_infer/norm_train_gpus_0,1_autocast_fp32_nodes_2 Global.epoch_num=3 Global.auto_cast=fp32 Train.loader.batch_size_per_card=16 ! + ...... + Run successfully with command - ch_PP-OCRv3_rec - python3.7 tools/infer/predict_rec.py --rec_image_shape="3,48,320" --use_gpu=False --enable_mkldnn=False --cpu_threads=6 --rec_model_dir=./test_tipc/output/ch_PP-OCRv3_rec/lite_train_lite_infer/norm_train_gpus_0,1_autocast_fp32_nodes_2/Student --rec_batch_num=1 --image_dir=./inference/rec_inference --benchmark=True --precision=fp32 > ./test_tipc/output/ch_PP-OCRv3_rec/lite_train_lite_infer/python_infer_cpu_usemkldnn_False_threads_6_precision_fp32_batchsize_1.log 2>&1 ! +``` + +在开启benchmark参数时,可以得到测试的详细数据,包含运行环境信息(系统版本、CUDA版本、CUDNN版本、驱动版本),Paddle版本信息,参数设置信息(运行设备、线程数、是否开启内存优化等),模型信息(模型名称、精度),数据信息(batchsize、是否为动态shape等),性能信息(CPU,GPU的占用、运行耗时、预处理耗时、推理耗时、后处理耗时),内容如下所示: + +``` +[2022/06/02 22:53:35] ppocr INFO: + +[2022/06/02 22:53:35] ppocr INFO: ---------------------- Env info ---------------------- +[2022/06/02 22:53:35] ppocr INFO: OS_version: Ubuntu 16.04 +[2022/06/02 22:53:35] ppocr INFO: CUDA_version: 10.1.243 +[2022/06/02 22:53:35] ppocr INFO: CUDNN_version: 7.6.5 +[2022/06/02 22:53:35] ppocr INFO: drivier_version: 460.32.03 +[2022/06/02 22:53:35] ppocr INFO: ---------------------- Paddle info ---------------------- +[2022/06/02 22:53:35] ppocr INFO: paddle_version: 2.3.0-rc0 +[2022/06/02 22:53:35] ppocr INFO: paddle_commit: 5d4980c052583fec022812d9c29460aff7cdc18b +[2022/06/02 22:53:35] ppocr INFO: log_api_version: 1.0 +[2022/06/02 22:53:35] ppocr INFO: ----------------------- Conf info ----------------------- +[2022/06/02 22:53:35] ppocr INFO: runtime_device: cpu +[2022/06/02 22:53:35] ppocr INFO: ir_optim: True +[2022/06/02 22:53:35] ppocr INFO: enable_memory_optim: True +[2022/06/02 22:53:35] ppocr INFO: enable_tensorrt: False +[2022/06/02 22:53:35] ppocr INFO: enable_mkldnn: False +[2022/06/02 22:53:35] ppocr INFO: cpu_math_library_num_threads: 6 +[2022/06/02 22:53:35] ppocr INFO: ----------------------- Model info ---------------------- +[2022/06/02 22:53:35] ppocr INFO: model_name: rec +[2022/06/02 22:53:35] ppocr INFO: precision: fp32 +[2022/06/02 22:53:35] ppocr INFO: ----------------------- Data info ----------------------- +[2022/06/02 22:53:35] ppocr INFO: batch_size: 1 +[2022/06/02 22:53:35] ppocr INFO: input_shape: dynamic +[2022/06/02 22:53:35] ppocr INFO: data_num: 6 +[2022/06/02 22:53:35] ppocr INFO: ----------------------- Perf info ----------------------- +[2022/06/02 22:53:35] ppocr INFO: cpu_rss(MB): 288.957, gpu_rss(MB): None, gpu_util: None% +[2022/06/02 22:53:35] ppocr INFO: total time spent(s): 0.4824 +[2022/06/02 22:53:35] ppocr INFO: preprocess_time(ms): 0.1136, inference_time(ms): 79.5877, postprocess_time(ms): 0.6945 +``` + +该信息可以在运行log中查看,以上面的`ch_PP-OCRv3_rec`为例,log位置在`./test_tipc/output/ch_PP-OCRv3_rec/lite_train_lite_infer/results_python.log`。 + +如果运行失败,也会在终端中输出运行失败的日志信息以及对应的运行命令。可以基于该命令,分析运行失败的原因。 + +**注意:** 由于分布式训练时,仅在`trainer_id=0`所在的节点中保存模型,因此其他的节点中在运行模型导出与推理时会报错,为正常现象。 diff --git a/test_tipc/prepare.sh b/test_tipc/prepare.sh index a5c5bd2d06f03a34783eb46bf737d1597e72a0ae..cac373dedc264c20e958fa32c7072fe29f7f9b05 100644 --- a/test_tipc/prepare.sh +++ b/test_tipc/prepare.sh @@ -44,37 +44,46 @@ if [ ${MODE} = "lite_train_lite_infer" ];then # pretrain lite train data wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate - if [[ ${model_name} =~ "PPOCRv2_det" ]];then + if [[ ${model_name} =~ "ch_PP-OCRv2_det" ]];then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv2_det_distill_train.tar && cd ../ fi - if [[ ${model_name} =~ "PPOCRv3_det" ]];then - # TODO check model link + if [[ ${model_name} =~ "ch_PP-OCRv3_det" ]];then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv3_det_distill_train.tar && cd ../ fi + if [ ${model_name} == "en_table_structure" ];then + wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar --no-check-certificate + cd ./pretrain_models/ && tar xf en_ppocr_mobile_v2.0_table_structure_train.tar && cd ../ + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar --no-check-certificate + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar --no-check-certificate + cd ./inference/ && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar && cd ../ + fi cd ./pretrain_models/ && tar xf det_mv3_db_v2.0_train.tar && cd ../ rm -rf ./train_data/icdar2015 rm -rf ./train_data/ic15_data + rm -rf ./train_data/pubtabnet wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate + wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/pubtabnet.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./deploy/slim/prune https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/sen.pickle --no-check-certificate - cd ./train_data/ && tar xf icdar2015_lite.tar && tar xf ic15_data.tar + cd ./train_data/ && tar xf icdar2015_lite.tar && tar xf ic15_data.tar && tar xf pubtabnet.tar ln -s ./icdar2015_lite ./icdar2015 + wget -nc -P ./ic15_data/ https://paddleocr.bj.bcebos.com/dataset/rec_gt_train_lite.txt --no-check-certificate + wget -nc -P ./ic15_data/ https://paddleocr.bj.bcebos.com/dataset/rec_gt_test_lite.txt --no-check-certificate cd ../ cd ./inference && tar xf rec_inference.tar && cd ../ - if [ ${model_name} == "ch_PPOCRv2_det" ] || [ ${model_name} == "ch_PPOCRv2_det_PACT" ]; then + if [ ${model_name} == "ch_PP-OCRv2_det" ] || [ ${model_name} == "ch_PP-OCRv2_det_PACT" ]; then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_ppocr_server_v2.0_det_train.tar && cd ../ fi - if [ ${model_name} == "ch_PPOCRv2_rec" ] || [ ${model_name} == "ch_PPOCRv2_rec_PACT" ]; then + if [ ${model_name} == "ch_PP-OCRv2_rec" ] || [ ${model_name} == "ch_PP-OCRv2_rec_PACT" ]; then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv2_rec_train.tar && cd ../ fi - if [ ${model_name} == "ch_PPOCRv3_rec" ] || [ ${model_name} == "ch_PPOCRv3_rec_PACT" ]; then - # TODO check model link + if [ ${model_name} == "ch_PP-OCRv3_rec" ] || [ ${model_name} == "ch_PP-OCRv3_rec_PACT" ]; then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv3_rec_train.tar && cd ../ fi @@ -89,8 +98,9 @@ if [ ${MODE} = "lite_train_lite_infer" ];then fi if [ ${model_name} == "det_r50_vd_sast_icdar15_v2.0" ] || [ ${model_name} == "det_r50_vd_sast_totaltext_v2.0" ]; then wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate + wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate - cd ./train_data && tar xf total_text_lite.tar && ln -s total_text_lite total_text && cd ../ + cd ./train_data && tar xf total_text_lite.tar && ln -s total_text_lite total_text && tar xf det_r50_vd_sast_icdar15_v2.0_train.tar && cd ../ fi if [ ${model_name} == "det_mv3_db_v2_0" ]; then wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate @@ -114,15 +124,19 @@ elif [ ${MODE} = "whole_train_whole_infer" ];then wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate rm -rf ./train_data/icdar2015 rm -rf ./train_data/ic15_data + rm -rf ./train_data/pubtabnet wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate - cd ./train_data/ && tar xf icdar2015.tar && tar xf ic15_data.tar && cd ../ - if [ ${model_name} == "ch_PPOCRv2_det" ]; then + wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/pubtabnet.tar --no-check-certificate + cd ./train_data/ && tar xf icdar2015.tar && tar xf ic15_data.tar && tar xf pubtabnet.tar + wget -nc -P ./ic15_data/ https://paddleocr.bj.bcebos.com/dataset/rec_gt_train_lite.txt --no-check-certificate + wget -nc -P ./ic15_data/ https://paddleocr.bj.bcebos.com/dataset/rec_gt_test_lite.txt --no-check-certificate + cd ../ + if [ ${model_name} == "ch_PP-OCRv2_det" ]; then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv2_det_distill_train.tar && cd ../ fi - if [ ${model_name} == "ch_PPOCRv3_det" ]; then - # TODO check model link + if [ ${model_name} == "ch_PP-OCRv3_det" ]; then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv3_det_distill_train.tar && cd ../ fi @@ -137,24 +151,41 @@ elif [ ${MODE} = "whole_train_whole_infer" ];then wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text && cd ../ fi + if [[ ${model_name} =~ "en_table_structure" ]];then + wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar --no-check-certificate + cd ./pretrain_models/ && tar xf en_ppocr_mobile_v2.0_table_structure_train.tar && cd ../ + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar --no-check-certificate + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar --no-check-certificate + cd ./inference/ && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar && cd ../ + fi elif [ ${MODE} = "lite_train_whole_infer" ];then wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate rm -rf ./train_data/icdar2015 rm -rf ./train_data/ic15_data + rm -rf ./train_data/pubtabnet wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_infer.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate - cd ./train_data/ && tar xf icdar2015_infer.tar && tar xf ic15_data.tar + wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/pubtabnet.tar --no-check-certificate + cd ./train_data/ && tar xf icdar2015_infer.tar && tar xf ic15_data.tar && tar xf pubtabnet.tar ln -s ./icdar2015_infer ./icdar2015 + wget -nc -P ./ic15_data/ https://paddleocr.bj.bcebos.com/dataset/rec_gt_train_lite.txt --no-check-certificate + wget -nc -P ./ic15_data/ https://paddleocr.bj.bcebos.com/dataset/rec_gt_test_lite.txt --no-check-certificate cd ../ - if [ ${model_name} == "ch_PPOCRv2_det" ]; then + if [ ${model_name} == "ch_PP-OCRv2_det" ]; then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv2_det_distill_train.tar && cd ../ fi - if [ ${model_name} == "ch_PPOCRv3_det" ]; then - # TODO check model link + if [ ${model_name} == "ch_PP-OCRv3_det" ]; then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv3_det_distill_train.tar && cd ../ fi + if [[ ${model_name} =~ "en_table_structure" ]];then + wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar --no-check-certificate + cd ./pretrain_models/ && tar xf en_ppocr_mobile_v2.0_table_structure_train.tar && cd ../ + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar --no-check-certificate + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar --no-check-certificate + cd ./inference/ && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar && cd ../ + fi elif [ ${MODE} = "whole_infer" ];then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate @@ -199,31 +230,31 @@ elif [ ${MODE} = "whole_infer" ];then wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar --no-check-certificate cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_PP-OCRv3_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../ fi - if [[ ${model_name} =~ "ch_PPOCRv2_det" ]]; then + if [[ ${model_name} =~ "ch_PP-OCRv2_det" ]]; then eval_model_name="ch_PP-OCRv2_det_infer" wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && cd ../ fi - if [[ ${model_name} =~ "ch_PPOCRv3_det" ]]; then - # TODO check model link + if [[ ${model_name} =~ "ch_PP-OCRv3_det" ]]; then eval_model_name="ch_PP-OCRv3_det_infer" wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && cd ../ fi - if [[ ${model_name} =~ "PPOCRv2_ocr_rec" ]]; then + if [[ ${model_name} =~ "ch_PP-OCRv2_rec" ]]; then eval_model_name="ch_PP-OCRv2_rec_infer" wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_slim_quant_infer.tar --no-check-certificate cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_PP-OCRv2_rec_slim_quant_infer.tar && cd ../ fi - if [[ ${model_name} =~ "PPOCRv3_ocr_rec" ]]; then - # TODO check model link + if [[ ${model_name} =~ "ch_PP-OCRv3_rec" ]]; then eval_model_name="ch_PP-OCRv3_rec_infer" - echo $(pwd) wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar --no-check-certificate - # wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_slim_quant_infer.tar --no-check-certificate - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - # cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_PP-OCRv3_rec_slim_quant_infer.tar && cd ../ + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_slim_infer.tar --no-check-certificate + cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_PP-OCRv3_rec_slim_infer.tar && cd ../ + fi + if [[ ${model_name} == "ch_PP-OCRv3_rec_PACT" ]]; then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_slim_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_rec_slim_infer.tar && cd ../ fi if [ ${model_name} == "en_server_pgnetA" ]; then wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar --no-check-certificate @@ -314,6 +345,12 @@ elif [ ${MODE} = "whole_infer" ];then wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar --no-check-certificate cd ./inference/ && tar xf det_r50_vd_east_v2.0_train.tar & cd ../ fi + if [[ ${model_name} =~ "en_table_structure" ]];then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar --no-check-certificate + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar --no-check-certificate + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar --no-check-certificate + cd ./inference/ && tar xf en_ppocr_mobile_v2.0_table_structure_infer.tar && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar && cd ../ + fi fi if [ ${MODE} = "klquant_whole_infer" ]; then @@ -324,28 +361,29 @@ if [ ${MODE} = "klquant_whole_infer" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ fi - if [ ${model_name} = "PPOCRv2_ocr_rec_kl" ]; then + if [ ${model_name} = "ch_PP-OCRv2_rec_KL" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate cd ./train_data/ && tar xf ic15_data.tar && cd ../ cd ./inference && tar xf rec_inference.tar && tar xf ch_PP-OCRv2_rec_infer.tar && cd ../ fi - if [ ${model_name} = "PPOCRv3_ocr_rec_kl" ]; then - # TODO check model link + if [ ${model_name} = "ch_PP-OCRv3_rec_KL" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate - cd ./train_data/ && tar xf ic15_data.tar && cd ../ + cd ./train_data/ && tar xf ic15_data.tar + wget -nc -P ./ic15_data/ https://paddleocr.bj.bcebos.com/dataset/rec_gt_train_lite.txt --no-check-certificate + wget -nc -P ./ic15_data/ https://paddleocr.bj.bcebos.com/dataset/rec_gt_test_lite.txt --no-check-certificate + cd ../ cd ./inference && tar xf rec_inference.tar && tar xf ch_PP-OCRv3_rec_infer.tar && cd ../ fi - if [ ${model_name} = "PPOCRv2_ocr_det_kl" ]; then + if [ ${model_name} = "ch_PP-OCRv2_det_KL" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate cd ./inference && tar xf ch_PP-OCRv2_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ fi - if [ ${model_name} = "PPOCRv3_ocr_det_kl" ]; then - # TODO check model link + if [ ${model_name} = "ch_PP-OCRv3_det_KL" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ @@ -356,32 +394,114 @@ if [ ${MODE} = "klquant_whole_infer" ]; then wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate cd ./train_data/ && tar xf ic15_data.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf rec_inference.tar && cd ../ - fi + fi + if [ ${model_name} = "en_table_structure_KL" ];then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar --no-check-certificate + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar --no-check-certificate + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar --no-check-certificate + wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/pubtabnet.tar --no-check-certificate + cd ./inference/ && tar xf en_ppocr_mobile_v2.0_table_structure_infer.tar && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar && cd ../ + cd ./train_data/ && tar xf pubtabnet.tar && cd ../ + fi fi if [ ${MODE} = "cpp_infer" ];then - if [ ${model_name} = "ocr_det" ]; then + if [ ${model_name} = "ch_ppocr_mobile_v2.0_det" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ - elif [ ${model_name} = "ocr_det_v3" ]; then + elif [ ${model_name} = "ch_ppocr_mobile_v2.0_det_KL" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_klquant_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_ppocr_mobile_v2.0_det_PACT" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_pact_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec" ]; then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec_KL" ]; then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_klquant_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec_PACT" ]; then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_pact_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_ppocr_server_v2.0_det" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_ppocr_server_v2.0_rec" ]; then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_server_v2.0_rec_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv2_det" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv2_det_KL" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv2_det_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_det_klquant_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv2_det_PACT" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv2_det_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_det_pact_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv2_rec" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_rec_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv2_rec_KL" ]; then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv2_rec_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_rec_klquant_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv2_rec_PACT" ]; then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv2_rec_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_rec_pact_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv3_det" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ - elif [ ${model_name} = "ocr_rec_v3" ]; then + elif [ ${model_name} = "ch_PP-OCRv3_det_KL" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_det_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_det_klquant_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv3_det_PACT" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_det_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_det_pact_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv3_rec" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar --no-check-certificate cd ./inference && tar xf ch_PP-OCRv3_rec_infer.tar && tar xf rec_inference.tar && cd ../ - elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec" ]; then + elif [ ${model_name} = "ch_PP-OCRv3_rec_KL" ]; then wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate - cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf rec_inference.tar && cd ../ - elif [ ${model_name} = "ocr_system" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_rec_klquant_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv3_rec_PACT" ]; then + wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_rec_pact_infer.tar && tar xf rec_inference.tar && cd ../ + elif [ ${model_name} = "ch_ppocr_mobile_v2.0" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../ - elif [ ${model_name} = "ocr_system_v3" ]; then + elif [ ${model_name} = "ch_ppocr_server_v2.0" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv2" ]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_det_infer.tar && tar xf ch_PP-OCRv2_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../ + elif [ ${model_name} = "ch_PP-OCRv3" ]; then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar --no-check-certificate @@ -395,36 +515,84 @@ if [ ${MODE} = "serving_infer" ];then IFS='|' array=(${python_name_list}) python_name=${array[0]} - ${python_name} -m pip install paddle-serving-server-gpu==0.8.3.post101 - ${python_name} -m pip install paddle_serving_client==0.8.3 - ${python_name} -m pip install paddle-serving-app==0.8.3 - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar + ${python_name} -m pip install paddle-serving-server-gpu + ${python_name} -m pip install paddle_serving_client + ${python_name} -m pip install paddle-serving-app + # wget model + if [ ${model_name} == "ch_ppocr_mobile_v2.0_det_KL" ] || [ ${model_name} == "ch_ppocr_mobile_v2.0_rec_KL" ] ; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_klquant_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_klquant_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_klquant_infer.tar && cd ../ + elif [ ${model_name} == "ch_PP-OCRv2_det_KL" ] || [ ${model_name} == "ch_PP-OCRv2_rec_KL" ] ; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv2_det_klquant_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv2_rec_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_det_klquant_infer.tar && tar xf ch_PP-OCRv2_rec_klquant_infer.tar && cd ../ + elif [ ${model_name} == "ch_PP-OCRv3_det_KL" ] || [ ${model_name} == "ch_PP-OCRv3_rec_KL" ] ; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_det_klquant_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_klquant_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_det_klquant_infer.tar && tar xf ch_PP-OCRv3_rec_klquant_infer.tar && cd ../ + elif [ ${model_name} == "ch_ppocr_mobile_v2.0_det_PACT" ] || [ ${model_name} == "ch_ppocr_mobile_v2.0_rec_PACT" ] ; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_pact_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_pact_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_pact_infer.tar && cd ../ + elif [ ${model_name} == "ch_PP-OCRv2_det_PACT" ] || [ ${model_name} == "ch_PP-OCRv2_rec_PACT" ] ; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv2_det_pact_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv2_rec_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_det_pact_infer.tar && tar xf ch_PP-OCRv2_rec_pact_infer.tar && cd ../ + elif [ ${model_name} == "ch_PP-OCRv3_det_PACT" ] || [ ${model_name} == "ch_PP-OCRv3_rec_PACT" ] ; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_det_pact_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_pact_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_det_pact_infer.tar && tar xf ch_PP-OCRv3_rec_pact_infer.tar && cd ../ + elif [[ ${model_name} =~ "ch_ppocr_mobile_v2.0" ]]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && cd ../ + elif [[ ${model_name} =~ "ch_ppocr_server_v2.0" ]]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && cd ../ + elif [[ ${model_name} =~ "ch_PP-OCRv2" ]]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_det_infer.tar && tar xf ch_PP-OCRv2_rec_infer.tar && cd ../ + elif [[ ${model_name} =~ "ch_PP-OCRv3" ]]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_PP-OCRv3_rec_infer.tar && cd ../ + fi + # wget data + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate - cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_PP-OCRv3_rec_infer.tar && tar xf rec_inference.tar && cd ../ - cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && tar xf ch_ppocr_server_v2.0_det_infer.tar && cd ../ + cd ./inference && tar xf ch_det_data_50.tar && tar xf rec_inference.tar && cd ../ fi if [ ${MODE} = "paddle2onnx_infer" ];then # prepare serving env python_name=$(func_parser_value "${lines[2]}") ${python_name} -m pip install paddle2onnx - ${python_name} -m pip install onnxruntime==1.4.0 + ${python_name} -m pip install onnxruntime # wget model - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar - cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_PP-OCRv3_rec_infer.tar && cd ../ + if [[ ${model_name} =~ "ch_ppocr_mobile_v2.0" ]]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && cd ../ + elif [[ ${model_name} =~ "ch_ppocr_server_v2.0" ]]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && cd ../ + elif [[ ${model_name} =~ "ch_PP-OCRv2" ]]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv2_det_infer.tar && tar xf ch_PP-OCRv2_rec_infer.tar && cd ../ + elif [[ ${model_name} =~ "ch_PP-OCRv3" ]]; then + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate + wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar --no-check-certificate + cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_PP-OCRv3_rec_infer.tar && cd ../ + fi + # wget data wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar - cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && tar xf rec_inference.tar && cd ../ + cd ./inference && tar xf ch_det_data_50.tar && tar xf rec_inference.tar && cd ../ fi diff --git a/test_tipc/readme.md b/test_tipc/readme.md index 8110f0073be248259c7cdd002d209c150a52fb71..effb2f168b6cc91012bef3de120de9e98a21dbda 100644 --- a/test_tipc/readme.md +++ b/test_tipc/readme.md @@ -138,6 +138,7 @@ bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobil ## 4. 开始测试 各功能测试中涉及混合精度、裁剪、量化等训练相关,及mkldnn、Tensorrt等多种预测相关参数配置,请点击下方相应链接了解更多细节和使用教程: - [test_train_inference_python 使用](docs/test_train_inference_python.md) :测试基于Python的模型训练、评估、推理等基本功能,包括裁剪、量化、蒸馏。 +- [test_train_fleet_inference_python 使用](./docs/test_train_fleet_inference_python.md):测试基于Python的多机多卡训练与推理等基本功能。 - [test_inference_cpp 使用](docs/test_inference_cpp.md):测试基于C++的模型推理。 - [test_serving 使用](docs/test_serving.md):测试基于Paddle Serving的服务化部署功能。 - [test_lite_arm_cpp 使用](docs/test_lite_arm_cpp.md):测试基于Paddle-Lite的ARM CPU端c++预测部署功能。 diff --git a/test_tipc/test_inference_cpp.sh b/test_tipc/test_inference_cpp.sh index 2bef621d9893799e82ef9132a7527d6abc11e75b..c0c7c18a38a46b00c839757e303049135a508691 100644 --- a/test_tipc/test_inference_cpp.sh +++ b/test_tipc/test_inference_cpp.sh @@ -43,7 +43,7 @@ cpp_cls_value=$(func_parser_value "${lines[18]}") cpp_use_angle_cls_key=$(func_parser_key "${lines[19]}") cpp_use_angle_cls_value=$(func_parser_value "${lines[19]}") -LOG_PATH="./test_tipc/output/cpp_infer/${model_name}" +LOG_PATH="./test_tipc/output/${model_name}/cpp_infer" mkdir -p ${LOG_PATH} status_log="${LOG_PATH}/results_cpp.log" @@ -84,7 +84,7 @@ function func_cpp_inference(){ eval $command last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" - status_check $last_status "${command}" "${status_log}" + status_check $last_status "${command}" "${status_log}" "${model_name}" done done done @@ -117,7 +117,7 @@ function func_cpp_inference(){ eval $command last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" - status_check $last_status "${command}" "${status_log}" + status_check $last_status "${command}" "${status_log}" "${model_name}" done done @@ -178,6 +178,22 @@ if [ ${use_opencv} = "True" ]; then else OPENCV_DIR='' fi +if [ -d "paddle_inference/" ] ;then + echo "################### download paddle inference skipped ###################" +else + echo "################### download paddle inference ###################" + PADDLEInfer=$3 + if [ "" = "$PADDLEInfer" ];then + wget -nc https://paddle-inference-lib.bj.bcebos.com/2.3.0/cxx_c/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddle_inference.tgz --no-check-certificate + else + wget -nc $PADDLEInfer --no-check-certificate + fi + tar zxf paddle_inference.tgz + if [ ! -d "paddle_inference" ]; then + ln -s paddle_inference_install_dir paddle_inference + fi + echo "################### download paddle inference finished ###################" +fi LIB_DIR=$(pwd)/paddle_inference/ CUDA_LIB_DIR=$(dirname `find /usr -name libcudart.so`) CUDNN_LIB_DIR=$(dirname `find /usr -name libcudnn.so`) @@ -205,11 +221,10 @@ echo "################### build PaddleOCR demo finished ###################" # set cuda device GPUID=$2 if [ ${#GPUID} -le 0 ];then - env=" " + env="export CUDA_VISIBLE_DEVICES=0" else env="export CUDA_VISIBLE_DEVICES=${GPUID}" fi -set CUDA_VISIBLE_DEVICES eval $env diff --git a/test_tipc/test_inference_python.sh b/test_tipc/test_inference_python.sh index a416d623d8565a04c5abfb823d97dd6c5bf6eb8f..2a31a468f0d54d1979e82c8f0da98cac6f4edcec 100644 --- a/test_tipc/test_inference_python.sh +++ b/test_tipc/test_inference_python.sh @@ -88,7 +88,7 @@ function func_inference(){ eval $command last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" - status_check $last_status "${command}" "${status_log}" + status_check $last_status "${command}" "${status_log}" "${model_name}" done done done @@ -119,7 +119,7 @@ function func_inference(){ eval $command last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" - status_check $last_status "${command}" "${status_log}" + status_check $last_status "${command}" "${status_log}" "${model_name}" done done @@ -153,7 +153,7 @@ if [ ${MODE} = "whole_infer" ]; then echo ${infer_run_exports[Count]} eval $export_cmd status_export=$? - status_check $status_export "${export_cmd}" "${status_log}" + status_check $status_export "${export_cmd}" "${status_log}" "${model_name}" else save_infer_dir=${infer_model} fi diff --git a/test_tipc/test_paddle2onnx.sh b/test_tipc/test_paddle2onnx.sh index 4d1712cfdaa0c2036c5ccfdee4a322b8bf625262..4ad2035f48ea43227caa16900bd186bfd62f11e6 100644 --- a/test_tipc/test_paddle2onnx.sh +++ b/test_tipc/test_paddle2onnx.sh @@ -11,7 +11,7 @@ python=$(func_parser_value "${lines[2]}") # parser params -dataline=$(awk 'NR==1, NR==14{print}' $FILENAME) +dataline=$(awk 'NR==1, NR==17{print}' $FILENAME) IFS=$'\n' lines=(${dataline}) @@ -19,27 +19,32 @@ lines=(${dataline}) model_name=$(func_parser_value "${lines[1]}") python=$(func_parser_value "${lines[2]}") padlle2onnx_cmd=$(func_parser_value "${lines[3]}") -infer_model_dir_key=$(func_parser_key "${lines[4]}") -infer_model_dir_value=$(func_parser_value "${lines[4]}") +det_infer_model_dir_key=$(func_parser_key "${lines[4]}") +det_infer_model_dir_value=$(func_parser_value "${lines[4]}") model_filename_key=$(func_parser_key "${lines[5]}") model_filename_value=$(func_parser_value "${lines[5]}") params_filename_key=$(func_parser_key "${lines[6]}") params_filename_value=$(func_parser_value "${lines[6]}") -save_file_key=$(func_parser_key "${lines[7]}") -save_file_value=$(func_parser_value "${lines[7]}") -opset_version_key=$(func_parser_key "${lines[8]}") -opset_version_value=$(func_parser_value "${lines[8]}") -enable_onnx_checker_key=$(func_parser_key "${lines[9]}") -enable_onnx_checker_value=$(func_parser_value "${lines[9]}") +det_save_file_key=$(func_parser_key "${lines[7]}") +det_save_file_value=$(func_parser_value "${lines[7]}") +rec_infer_model_dir_key=$(func_parser_key "${lines[8]}") +rec_infer_model_dir_value=$(func_parser_value "${lines[8]}") +rec_save_file_key=$(func_parser_key "${lines[9]}") +rec_save_file_value=$(func_parser_value "${lines[9]}") +opset_version_key=$(func_parser_key "${lines[10]}") +opset_version_value=$(func_parser_value "${lines[10]}") +enable_onnx_checker_key=$(func_parser_key "${lines[11]}") +enable_onnx_checker_value=$(func_parser_value "${lines[11]}") # parser onnx inference -inference_py=$(func_parser_value "${lines[10]}") -use_gpu_key=$(func_parser_key "${lines[11]}") -use_gpu_list=$(func_parser_value "${lines[11]}") -det_model_key=$(func_parser_key "${lines[12]}") -image_dir_key=$(func_parser_key "${lines[13]}") -image_dir_value=$(func_parser_value "${lines[13]}") +inference_py=$(func_parser_value "${lines[12]}") +use_gpu_key=$(func_parser_key "${lines[13]}") +use_gpu_list=$(func_parser_value "${lines[13]}") +det_model_key=$(func_parser_key "${lines[14]}") +rec_model_key=$(func_parser_key "${lines[15]}") +image_dir_key=$(func_parser_key "${lines[16]}") +image_dir_value=$(func_parser_value "${lines[16]}") -LOG_PATH="./test_tipc/output/paddle2onnx/${model_name}" +LOG_PATH="./test_tipc/output/${model_name}/paddle2onnx" mkdir -p ${LOG_PATH} status_log="${LOG_PATH}/results_paddle2onnx.log" @@ -49,38 +54,95 @@ function func_paddle2onnx(){ _script=$1 # paddle2onnx - set_dirname=$(func_set_params "${infer_model_dir_key}" "${infer_model_dir_value}") - set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") - set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") - set_save_model=$(func_set_params "${save_file_key}" "${save_file_value}") - set_opset_version=$(func_set_params "${opset_version_key}" "${opset_version_value}") - set_enable_onnx_checker=$(func_set_params "${enable_onnx_checker_key}" "${enable_onnx_checker_value}") - trans_model_cmd="${padlle2onnx_cmd} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_save_model} ${set_opset_version} ${set_enable_onnx_checker}" - eval $trans_model_cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${trans_model_cmd}" "${status_log}" + if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then + # trans det + set_dirname=$(func_set_params "--model_dir" "${det_infer_model_dir_value}") + set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") + set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") + set_save_model=$(func_set_params "--save_file" "${det_save_file_value}") + set_opset_version=$(func_set_params "${opset_version_key}" "${opset_version_value}") + set_enable_onnx_checker=$(func_set_params "${enable_onnx_checker_key}" "${enable_onnx_checker_value}") + trans_model_cmd="${padlle2onnx_cmd} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_save_model} ${set_opset_version} ${set_enable_onnx_checker}" + eval $trans_model_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${trans_model_cmd}" "${status_log}" "${model_name}" + # trans rec + set_dirname=$(func_set_params "--model_dir" "${rec_infer_model_dir_value}") + set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") + set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") + set_save_model=$(func_set_params "--save_file" "${rec_save_file_value}") + set_opset_version=$(func_set_params "${opset_version_key}" "${opset_version_value}") + set_enable_onnx_checker=$(func_set_params "${enable_onnx_checker_key}" "${enable_onnx_checker_value}") + trans_model_cmd="${padlle2onnx_cmd} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_save_model} ${set_opset_version} ${set_enable_onnx_checker}" + eval $trans_model_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${trans_model_cmd}" "${status_log}" "${model_name}" + elif [[ ${model_name} =~ "det" ]]; then + # trans det + set_dirname=$(func_set_params "--model_dir" "${det_infer_model_dir_value}") + set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") + set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") + set_save_model=$(func_set_params "--save_file" "${det_save_file_value}") + set_opset_version=$(func_set_params "${opset_version_key}" "${opset_version_value}") + set_enable_onnx_checker=$(func_set_params "${enable_onnx_checker_key}" "${enable_onnx_checker_value}") + trans_model_cmd="${padlle2onnx_cmd} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_save_model} ${set_opset_version} ${set_enable_onnx_checker}" + eval $trans_model_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${trans_model_cmd}" "${status_log}" "${model_name}" + elif [[ ${model_name} =~ "rec" ]]; then + # trans rec + set_dirname=$(func_set_params "--model_dir" "${rec_infer_model_dir_value}") + set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") + set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") + set_save_model=$(func_set_params "--save_file" "${rec_save_file_value}") + set_opset_version=$(func_set_params "${opset_version_key}" "${opset_version_value}") + set_enable_onnx_checker=$(func_set_params "${enable_onnx_checker_key}" "${enable_onnx_checker_value}") + trans_model_cmd="${padlle2onnx_cmd} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_save_model} ${set_opset_version} ${set_enable_onnx_checker}" + eval $trans_model_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${trans_model_cmd}" "${status_log}" "${model_name}" + fi + # python inference for use_gpu in ${use_gpu_list[*]}; do if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then _save_log_path="${LOG_PATH}/paddle2onnx_infer_cpu.log" set_gpu=$(func_set_params "${use_gpu_key}" "${use_gpu}") - set_model_dir=$(func_set_params "${det_model_key}" "${save_file_value}") set_img_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}") - infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " + if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then + set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}") + set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}") + infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " + elif [[ ${model_name} =~ "det" ]]; then + set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}") + infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " + elif [[ ${model_name} =~ "rec" ]]; then + set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}") + infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " + fi eval $infer_model_cmd last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" - status_check $last_status "${infer_model_cmd}" "${status_log}" + status_check $last_status "${infer_model_cmd}" "${status_log}" "${model_name}" elif [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then _save_log_path="${LOG_PATH}/paddle2onnx_infer_gpu.log" set_gpu=$(func_set_params "${use_gpu_key}" "${use_gpu}") - set_model_dir=$(func_set_params "${det_model_key}" "${save_file_value}") set_img_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}") - infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " + if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then + set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}") + set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}") + infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " + elif [[ ${model_name} =~ "det" ]]; then + set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}") + infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " + elif [[ ${model_name} =~ "rec" ]]; then + set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}") + infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " + fi eval $infer_model_cmd last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" - status_check $last_status "${infer_model_cmd}" "${status_log}" + status_check $last_status "${infer_model_cmd}" "${status_log}" "${model_name}" else echo "Does not support hardware other than CPU and GPU Currently!" fi diff --git a/test_tipc/test_serving.sh b/test_tipc/test_serving.sh deleted file mode 100644 index 3a6c88f31333da7972dcaf4de4cc5ced55a9ba49..0000000000000000000000000000000000000000 --- a/test_tipc/test_serving.sh +++ /dev/null @@ -1,191 +0,0 @@ -#!/bin/bash -source test_tipc/common_func.sh - -FILENAME=$1 -dataline=$(awk 'NR==1, NR==18{print}' $FILENAME) - -# parser params -IFS=$'\n' -lines=(${dataline}) - -# parser serving -model_name=$(func_parser_value "${lines[1]}") -python_list=$(func_parser_value "${lines[2]}") -trans_model_py=$(func_parser_value "${lines[3]}") -infer_model_dir_key=$(func_parser_key "${lines[4]}") -infer_model_dir_value=$(func_parser_value "${lines[4]}") -model_filename_key=$(func_parser_key "${lines[5]}") -model_filename_value=$(func_parser_value "${lines[5]}") -params_filename_key=$(func_parser_key "${lines[6]}") -params_filename_value=$(func_parser_value "${lines[6]}") -serving_server_key=$(func_parser_key "${lines[7]}") -serving_server_value=$(func_parser_value "${lines[7]}") -serving_client_key=$(func_parser_key "${lines[8]}") -serving_client_value=$(func_parser_value "${lines[8]}") -serving_dir_value=$(func_parser_value "${lines[9]}") -web_service_py=$(func_parser_value "${lines[10]}") -web_use_gpu_key=$(func_parser_key "${lines[11]}") -web_use_gpu_list=$(func_parser_value "${lines[11]}") -web_use_mkldnn_key=$(func_parser_key "${lines[12]}") -web_use_mkldnn_list=$(func_parser_value "${lines[12]}") -web_cpu_threads_key=$(func_parser_key "${lines[13]}") -web_cpu_threads_list=$(func_parser_value "${lines[13]}") -web_use_trt_key=$(func_parser_key "${lines[14]}") -web_use_trt_list=$(func_parser_value "${lines[14]}") -web_precision_key=$(func_parser_key "${lines[15]}") -web_precision_list=$(func_parser_value "${lines[15]}") -pipeline_py=$(func_parser_value "${lines[16]}") -image_dir_key=$(func_parser_key "${lines[17]}") -image_dir_value=$(func_parser_value "${lines[17]}") - -LOG_PATH="$(pwd)/test_tipc/output/pdserving/${model_name}" -mkdir -p ${LOG_PATH} -status_log="${LOG_PATH}/results_serving.log" - -function func_serving(){ - IFS='|' - _python=$1 - _script=$2 - _model_dir=$3 - # pdserving - set_dirname=$(func_set_params "${infer_model_dir_key}" "${infer_model_dir_value}") - set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") - set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") - set_serving_server=$(func_set_params "${serving_server_key}" "${serving_server_value}") - set_serving_client=$(func_set_params "${serving_client_key}" "${serving_client_value}") - set_image_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}") - python_list=(${python_list}) - trans_model_cmd="${python_list[0]} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}" - eval $trans_model_cmd - cd ${serving_dir_value} - unset https_proxy - unset http_proxy - for python in ${python_list[*]}; do - if [ ${python} = "cpp" ]; then - for use_gpu in ${web_use_gpu_list[*]}; do - if [ ${use_gpu} = "null" ]; then - if [ ${model_name} = "ocr_det_mobile" ]; then - web_service_cpp_cmd="${python_list[0]} -m paddle_serving_server.serve --model ppocr_det_mobile_2.0_serving/ ppocr_rec_mobile_2.0_serving/ --op GeneralDetectionOp GeneralInferOp --port 9293" - elif [ ${model_name} = "ocr_det_v3" ] || [ ${model_name} = "ocr_rec_v3" ]; then - web_service_cpp_cmd="${python_list[0]} -m paddle_serving_server.serve --model ppocr_det_v3_serving/ ppocr_rec_v3_serving/ --op GeneralDetectionOp GeneralInferOp --port 9293" - fi - eval $web_service_cpp_cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${web_service_cpp_cmd}" "${status_log}" - sleep 2s - _save_log_path="${LOG_PATH}/server_infer_cpp_cpu_pipeline_usemkldnn_False_threads_4_batchsize_1.log" - if [ ${model_name} = "ocr_det_mobile" ]; then - pipeline_cmd="${python_list[0]} ocr_cpp_client.py ppocr_det_mobile_2.0_client/ ppocr_rec_mobile_2.0_client/" - elif [ ${model_name} = "ocr_det_v3" ] || [ ${model_name} = "ocr_rec_v3" ]; then - pipeline_cmd="${python_list[0]} ocr_cpp_client.py ppocr_det_v3_client/ ppocr_rec_v3_client/" - fi - eval $pipeline_cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${pipeline_cmd}" "${status_log}" - sleep 2s - ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9 - else - if [ ${model_name} = "ocr_det_mobile" ]; then - web_service_cpp_cmd="${python_list[0]} -m paddle_serving_server.serve --model ppocr_det_mobile_2.0_serving/ ppocr_rec_mobile_2.0_serving/ --op GeneralDetectionOp GeneralInferOp --port 9293 --gpu_id=0" - elif [ ${model_name} = "ocr_det_v3" ] || [ ${model_name} = "ocr_rec_v3" ]; then - web_service_cpp_cmd="${python_list[0]} -m paddle_serving_server.serve --model ppocr_det_v3_serving/ ppocr_rec_v3_serving/ --op GeneralDetectionOp GeneralInferOp --port 9293 --gpu_id=0" - fi - eval $web_service_cpp_cmd - sleep 2s - _save_log_path="${LOG_PATH}/server_infer_cpp_cpu_pipeline_usemkldnn_False_threads_4_batchsize_1.log" - if [ ${model_name} = "ocr_det_mobile" ]; then - pipeline_cmd="${python_list[0]} ocr_cpp_client.py ppocr_det_mobile_2.0_client/ ppocr_rec_mobile_2.0_client/" - elif [ ${model_name} = "ocr_det_v3" ] || [ ${model_name} = "ocr_rec_v3" ]; then - pipeline_cmd="${python_list[0]} ocr_cpp_client.py ppocr_det_v3_client/ ppocr_rec_v3_client/" - fi - eval $pipeline_cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${pipeline_cmd}" "${status_log}" - sleep 2s - ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9 - fi - done - else - # python serving - for use_gpu in ${web_use_gpu_list[*]}; do - if [ ${use_gpu} = "null" ]; then - for use_mkldnn in ${web_use_mkldnn_list[*]}; do - for threads in ${web_cpu_threads_list[*]}; do - set_cpu_threads=$(func_set_params "${web_cpu_threads_key}" "${threads}") - web_service_cmd="${python} ${web_service_py} ${web_use_gpu_key}="" ${web_use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} &" - eval $web_service_cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${web_service_cmd}" "${status_log}" - sleep 2s - for pipeline in ${pipeline_py[*]}; do - _save_log_path="${LOG_PATH}/server_infer_cpu_${pipeline%_client*}_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_1.log" - pipeline_cmd="${python} ${pipeline} ${set_image_dir} > ${_save_log_path} 2>&1 " - eval $pipeline_cmd - last_status=${PIPESTATUS[0]} - eval "cat ${_save_log_path}" - status_check $last_status "${pipeline_cmd}" "${status_log}" - sleep 2s - done - ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9 - done - done - elif [ ${use_gpu} = "gpu" ]; then - for use_trt in ${web_use_trt_list[*]}; do - for precision in ${web_precision_list[*]}; do - if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then - continue - fi - if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then - continue - fi - if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [[ ${_flag_quant} = "True" ]]; then - continue - fi - set_tensorrt=$(func_set_params "${web_use_trt_key}" "${use_trt}") - if [ ${use_trt} = True ]; then - device_type=2 - fi - set_precision=$(func_set_params "${web_precision_key}" "${precision}") - web_service_cmd="${python} ${web_service_py} ${set_tensorrt} ${set_precision} & " - eval $web_service_cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${web_service_cmd}" "${status_log}" - - sleep 2s - for pipeline in ${pipeline_py[*]}; do - _save_log_path="${LOG_PATH}/server_infer_gpu_${pipeline%_client*}_usetrt_${use_trt}_precision_${precision}_batchsize_1.log" - pipeline_cmd="${python} ${pipeline} ${set_image_dir}> ${_save_log_path} 2>&1" - eval $pipeline_cmd - last_status=${PIPESTATUS[0]} - eval "cat ${_save_log_path}" - status_check $last_status "${pipeline_cmd}" "${status_log}" - sleep 2s - done - ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9 - done - done - else - echo "Does not support hardware other than CPU and GPU Currently!" - fi - done - fi - done -} - - -#set cuda device -GPUID=$2 -if [ ${#GPUID} -le 0 ];then - env="export CUDA_VISIBLE_DEVICES=0" -else - env="export CUDA_VISIBLE_DEVICES=${GPUID}" -fi -eval $env -echo $env - - -echo "################### run test ###################" - -export Count=0 -IFS="|" -func_serving "${web_service_cmd}" diff --git a/test_tipc/test_serving_infer_cpp.sh b/test_tipc/test_serving_infer_cpp.sh new file mode 100644 index 0000000000000000000000000000000000000000..f9f7ac1aa554312052ca22876558e58629342549 --- /dev/null +++ b/test_tipc/test_serving_infer_cpp.sh @@ -0,0 +1,133 @@ +#!/bin/bash +source test_tipc/common_func.sh + +function func_parser_model_config(){ + strs=$1 + IFS="/" + array=(${strs}) + tmp=${array[-1]} + echo ${tmp} +} + +FILENAME=$1 +dataline=$(awk 'NR==1, NR==19{print}' $FILENAME) +MODE=$2 + +# parser params +IFS=$'\n' +lines=(${dataline}) + +# parser serving +model_name=$(func_parser_value "${lines[1]}") +python_list=$(func_parser_value "${lines[2]}") +trans_model_py=$(func_parser_value "${lines[3]}") +det_infer_model_dir_key=$(func_parser_key "${lines[4]}") +det_infer_model_dir_value=$(func_parser_value "${lines[4]}") +model_filename_key=$(func_parser_key "${lines[5]}") +model_filename_value=$(func_parser_value "${lines[5]}") +params_filename_key=$(func_parser_key "${lines[6]}") +params_filename_value=$(func_parser_value "${lines[6]}") +det_serving_server_key=$(func_parser_key "${lines[7]}") +det_serving_server_value=$(func_parser_value "${lines[7]}") +det_serving_client_key=$(func_parser_key "${lines[8]}") +det_serving_client_value=$(func_parser_value "${lines[8]}") +rec_infer_model_dir_key=$(func_parser_key "${lines[9]}") +rec_infer_model_dir_value=$(func_parser_value "${lines[9]}") +rec_serving_server_key=$(func_parser_key "${lines[10]}") +rec_serving_server_value=$(func_parser_value "${lines[10]}") +rec_serving_client_key=$(func_parser_key "${lines[11]}") +rec_serving_client_value=$(func_parser_value "${lines[11]}") +det_server_value=$(func_parser_model_config "${lines[7]}") +det_client_value=$(func_parser_model_config "${lines[8]}") +rec_server_value=$(func_parser_model_config "${lines[10]}") +rec_client_value=$(func_parser_model_config "${lines[11]}") +serving_dir_value=$(func_parser_value "${lines[12]}") +web_service_py=$(func_parser_value "${lines[13]}") +op_key=$(func_parser_key "${lines[14]}") +op_value=$(func_parser_value "${lines[14]}") +port_key=$(func_parser_key "${lines[15]}") +port_value=$(func_parser_value "${lines[15]}") +gpu_key=$(func_parser_key "${lines[16]}") +gpu_value=$(func_parser_value "${lines[16]}") +cpp_client_py=$(func_parser_value "${lines[17]}") +image_dir_key=$(func_parser_key "${lines[18]}") +image_dir_value=$(func_parser_value "${lines[18]}") + +LOG_PATH="$(pwd)/test_tipc/output/${model_name}/${MODE}/cpp" +mkdir -p ${LOG_PATH} +status_log="${LOG_PATH}/results_cpp_serving.log" + +function func_serving(){ + IFS='|' + _python=$1 + _script=$2 + _model_dir=$3 + # pdserving + set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") + set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") + # trans det + set_dirname=$(func_set_params "--dirname" "${det_infer_model_dir_value}") + set_serving_server=$(func_set_params "--serving_server" "${det_serving_server_value}") + set_serving_client=$(func_set_params "--serving_client" "${det_serving_client_value}") + python_list=(${python_list}) + trans_model_cmd="${python_list[0]} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}" + eval $trans_model_cmd + cp "deploy/pdserving/serving_client_conf.prototxt" ${det_serving_client_value} + # trans rec + set_dirname=$(func_set_params "--dirname" "${rec_infer_model_dir_value}") + set_serving_server=$(func_set_params "--serving_server" "${rec_serving_server_value}") + set_serving_client=$(func_set_params "--serving_client" "${rec_serving_client_value}") + python_list=(${python_list}) + trans_model_cmd="${python_list[0]} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}" + eval $trans_model_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${trans_model_cmd}" "${status_log}" "${model_name}" + set_image_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}") + python_list=(${python_list}) + cd ${serving_dir_value} + # cpp serving + for gpu_id in ${gpu_value[*]}; do + if [ ${gpu_id} = "null" ]; then + web_service_cpp_cmd="${python_list[0]} ${web_service_py} --model ${det_server_value} ${rec_server_value} ${op_key} ${op_value} ${port_key} ${port_value} > serving_log_cpu.log &" + eval $web_service_cpp_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${web_service_cpp_cmd}" "${status_log}" "${model_name}" + sleep 5s + _save_log_path="${LOG_PATH}/server_infer_cpp_cpu.log" + cpp_client_cmd="${python_list[0]} ${cpp_client_py} ${det_client_value} ${rec_client_value} > ${_save_log_path} 2>&1" + eval $cpp_client_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${cpp_client_cmd}" "${status_log}" "${model_name}" + ps ux | grep -i ${port_value} | awk '{print $2}' | xargs kill -s 9 + else + web_service_cpp_cmd="${python_list[0]} ${web_service_py} --model ${det_server_value} ${rec_server_value} ${op_key} ${op_value} ${port_key} ${port_value} ${gpu_key} ${gpu_id} > serving_log_gpu.log &" + eval $web_service_cpp_cmd + sleep 5s + _save_log_path="${LOG_PATH}/server_infer_cpp_gpu.log" + cpp_client_cmd="${python_list[0]} ${cpp_client_py} ${det_client_value} ${rec_client_value} > ${_save_log_path} 2>&1" + eval $cpp_client_cmd + last_status=${PIPESTATUS[0]} + eval "cat ${_save_log_path}" + status_check $last_status "${cpp_client_cmd}" "${status_log}" "${model_name}" + ps ux | grep -i ${port_value} | awk '{print $2}' | xargs kill -s 9 + fi + done +} + + +#set cuda device +GPUID=$3 +if [ ${#GPUID} -le 0 ];then + env="export CUDA_VISIBLE_DEVICES=0" +else + env="export CUDA_VISIBLE_DEVICES=${GPUID}" +fi +eval $env +echo $env + + +echo "################### run test ###################" + +export Count=0 +IFS="|" +func_serving "${web_service_cpp_cmd}" diff --git a/test_tipc/test_serving_infer_python.sh b/test_tipc/test_serving_infer_python.sh new file mode 100644 index 0000000000000000000000000000000000000000..c76d6f5d19e00c729953dc0df95cbfc20b6494a8 --- /dev/null +++ b/test_tipc/test_serving_infer_python.sh @@ -0,0 +1,223 @@ +#!/bin/bash +source test_tipc/common_func.sh + +function func_parser_model_config(){ + strs=$1 + IFS="/" + array=(${strs}) + tmp=${array[-1]} + echo ${tmp} +} + +FILENAME=$1 +dataline=$(awk 'NR==1, NR==23{print}' $FILENAME) +MODE=$2 + +# parser params +IFS=$'\n' +lines=(${dataline}) + +# parser serving +model_name=$(func_parser_value "${lines[1]}") +python_list=$(func_parser_value "${lines[2]}") +trans_model_py=$(func_parser_value "${lines[3]}") +det_infer_model_dir_key=$(func_parser_key "${lines[4]}") +det_infer_model_dir_value=$(func_parser_value "${lines[4]}") +model_filename_key=$(func_parser_key "${lines[5]}") +model_filename_value=$(func_parser_value "${lines[5]}") +params_filename_key=$(func_parser_key "${lines[6]}") +params_filename_value=$(func_parser_value "${lines[6]}") +det_serving_server_key=$(func_parser_key "${lines[7]}") +det_serving_server_value=$(func_parser_value "${lines[7]}") +det_serving_client_key=$(func_parser_key "${lines[8]}") +det_serving_client_value=$(func_parser_value "${lines[8]}") +rec_infer_model_dir_key=$(func_parser_key "${lines[9]}") +rec_infer_model_dir_value=$(func_parser_value "${lines[9]}") +rec_serving_server_key=$(func_parser_key "${lines[10]}") +rec_serving_server_value=$(func_parser_value "${lines[10]}") +rec_serving_client_key=$(func_parser_key "${lines[11]}") +rec_serving_client_value=$(func_parser_value "${lines[11]}") +serving_dir_value=$(func_parser_value "${lines[12]}") +web_service_py=$(func_parser_value "${lines[13]}") +web_use_gpu_key=$(func_parser_key "${lines[14]}") +web_use_gpu_list=$(func_parser_value "${lines[14]}") +web_use_mkldnn_key=$(func_parser_key "${lines[15]}") +web_use_mkldnn_list=$(func_parser_value "${lines[15]}") +web_cpu_threads_key=$(func_parser_key "${lines[16]}") +web_cpu_threads_list=$(func_parser_value "${lines[16]}") +web_use_trt_key=$(func_parser_key "${lines[17]}") +web_use_trt_list=$(func_parser_value "${lines[17]}") +web_precision_key=$(func_parser_key "${lines[18]}") +web_precision_list=$(func_parser_value "${lines[18]}") +det_server_key=$(func_parser_key "${lines[19]}") +det_server_value=$(func_parser_model_config "${lines[7]}") +det_client_value=$(func_parser_model_config "${lines[8]}") +rec_server_key=$(func_parser_key "${lines[20]}") +rec_server_value=$(func_parser_model_config "${lines[10]}") +rec_client_value=$(func_parser_model_config "${lines[11]}") +pipeline_py=$(func_parser_value "${lines[21]}") +image_dir_key=$(func_parser_key "${lines[22]}") +image_dir_value=$(func_parser_value "${lines[22]}") + +LOG_PATH="$(pwd)/test_tipc/output/${model_name}/${MODE}/python" +mkdir -p ${LOG_PATH} +status_log="${LOG_PATH}/results_python_serving.log" + +function func_serving(){ + IFS='|' + _python=$1 + _script=$2 + _model_dir=$3 + # pdserving + set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") + set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") + if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then + # trans det + set_dirname=$(func_set_params "--dirname" "${det_infer_model_dir_value}") + set_serving_server=$(func_set_params "--serving_server" "${det_serving_server_value}") + set_serving_client=$(func_set_params "--serving_client" "${det_serving_client_value}") + python_list=(${python_list}) + trans_model_cmd="${python_list[0]} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}" + eval $trans_model_cmd + # trans rec + set_dirname=$(func_set_params "--dirname" "${rec_infer_model_dir_value}") + set_serving_server=$(func_set_params "--serving_server" "${rec_serving_server_value}") + set_serving_client=$(func_set_params "--serving_client" "${rec_serving_client_value}") + python_list=(${python_list}) + trans_model_cmd="${python_list[0]} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}" + eval $trans_model_cmd + elif [[ ${model_name} =~ "det" ]]; then + # trans det + set_dirname=$(func_set_params "--dirname" "${det_infer_model_dir_value}") + set_serving_server=$(func_set_params "--serving_server" "${det_serving_server_value}") + set_serving_client=$(func_set_params "--serving_client" "${det_serving_client_value}") + python_list=(${python_list}) + trans_model_cmd="${python_list[0]} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}" + eval $trans_model_cmd + elif [[ ${model_name} =~ "rec" ]]; then + # trans rec + set_dirname=$(func_set_params "--dirname" "${rec_infer_model_dir_value}") + set_serving_server=$(func_set_params "--serving_server" "${rec_serving_server_value}") + set_serving_client=$(func_set_params "--serving_client" "${rec_serving_client_value}") + python_list=(${python_list}) + trans_model_cmd="${python_list[0]} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}" + eval $trans_model_cmd + fi + set_image_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}") + python_list=(${python_list}) + + cd ${serving_dir_value} + python=${python_list[0]} + + # python serving + for use_gpu in ${web_use_gpu_list[*]}; do + if [ ${use_gpu} = "null" ]; then + for use_mkldnn in ${web_use_mkldnn_list[*]}; do + for threads in ${web_cpu_threads_list[*]}; do + set_cpu_threads=$(func_set_params "${web_cpu_threads_key}" "${threads}") + if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then + set_det_model_config=$(func_set_params "${det_server_key}" "${det_server_value}") + set_rec_model_config=$(func_set_params "${rec_server_key}" "${rec_server_value}") + web_service_cmd="${python} ${web_service_py} ${web_use_gpu_key}="" ${web_use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_det_model_config} ${set_rec_model_config} &" + eval $web_service_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}" + elif [[ ${model_name} =~ "det" ]]; then + set_det_model_config=$(func_set_params "${det_server_key}" "${det_server_value}") + web_service_cmd="${python} ${web_service_py} ${web_use_gpu_key}="" ${web_use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_det_model_config} &" + eval $web_service_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}" + elif [[ ${model_name} =~ "rec" ]]; then + set_rec_model_config=$(func_set_params "${rec_server_key}" "${rec_server_value}") + web_service_cmd="${python} ${web_service_py} ${web_use_gpu_key}="" ${web_use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_rec_model_config} &" + eval $web_service_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}" + fi + sleep 2s + for pipeline in ${pipeline_py[*]}; do + _save_log_path="${LOG_PATH}/server_infer_cpu_${pipeline%_client*}_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_1.log" + pipeline_cmd="${python} ${pipeline} ${set_image_dir} > ${_save_log_path} 2>&1 " + eval $pipeline_cmd + last_status=${PIPESTATUS[0]} + eval "cat ${_save_log_path}" + status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}" + sleep 2s + done + ps ux | grep -E 'web_service' | awk '{print $2}' | xargs kill -s 9 + done + done + elif [ ${use_gpu} = "gpu" ]; then + for use_trt in ${web_use_trt_list[*]}; do + for precision in ${web_precision_list[*]}; do + if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then + continue + fi + if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then + continue + fi + if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [[ ${_flag_quant} = "True" ]]; then + continue + fi + set_tensorrt=$(func_set_params "${web_use_trt_key}" "${use_trt}") + if [ ${use_trt} = True ]; then + device_type=2 + fi + set_precision=$(func_set_params "${web_precision_key}" "${precision}") + if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then + set_det_model_config=$(func_set_params "${det_server_key}" "${det_server_value}") + set_rec_model_config=$(func_set_params "${rec_server_key}" "${rec_server_value}") + web_service_cmd="${python} ${web_service_py} ${set_tensorrt} ${set_precision} ${set_det_model_config} ${set_rec_model_config} &" + eval $web_service_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}" + elif [[ ${model_name} =~ "det" ]]; then + set_det_model_config=$(func_set_params "${det_server_key}" "${det_server_value}") + web_service_cmd="${python} ${web_service_py} ${set_tensorrt} ${set_precision} ${set_det_model_config} &" + eval $web_service_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}" + elif [[ ${model_name} =~ "rec" ]]; then + set_rec_model_config=$(func_set_params "${rec_server_key}" "${rec_server_value}") + web_service_cmd="${python} ${web_service_py} ${set_tensorrt} ${set_precision} ${set_rec_model_config} &" + eval $web_service_cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}" + fi + sleep 2s + for pipeline in ${pipeline_py[*]}; do + _save_log_path="${LOG_PATH}/server_infer_gpu_${pipeline%_client*}_usetrt_${use_trt}_precision_${precision}_batchsize_1.log" + pipeline_cmd="${python} ${pipeline} ${set_image_dir}> ${_save_log_path} 2>&1" + eval $pipeline_cmd + last_status=${PIPESTATUS[0]} + eval "cat ${_save_log_path}" + status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}" + sleep 2s + done + ps ux | grep -E 'web_service' | awk '{print $2}' | xargs kill -s 9 + done + done + else + echo "Does not support hardware other than CPU and GPU Currently!" + fi + done +} + + +#set cuda device +GPUID=$3 +if [ ${#GPUID} -le 0 ];then + env="export CUDA_VISIBLE_DEVICES=0" +else + env="export CUDA_VISIBLE_DEVICES=${GPUID}" +fi +eval $env +echo $env + + +echo "################### run test ###################" + +export Count=0 +IFS="|" +func_serving "${web_service_cmd}" diff --git a/test_tipc/test_train_inference_python.sh b/test_tipc/test_train_inference_python.sh index 81d1bf8eef51b130782f0059b80e89b33b7d2657..62a56a32ceb15e387f568f1b9857bced95166be3 100644 --- a/test_tipc/test_train_inference_python.sh +++ b/test_tipc/test_train_inference_python.sh @@ -142,9 +142,9 @@ function func_inference(){ for use_gpu in ${use_gpu_list[*]}; do if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then for use_mkldnn in ${use_mkldnn_list[*]}; do - if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then - continue - fi + # if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then + # continue + # fi for threads in ${cpu_threads_list[*]}; do for batch_size in ${batch_size_list[*]}; do for precision in ${precision_list[*]}; do @@ -169,7 +169,7 @@ function func_inference(){ eval $command last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" - status_check $last_status "${command}" "${status_log}" + status_check $last_status "${command}" "${status_log}" "${model_name}" done done done @@ -200,7 +200,7 @@ function func_inference(){ eval $command last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" - status_check $last_status "${command}" "${status_log}" + status_check $last_status "${command}" "${status_log}" "${model_name}" done done @@ -240,7 +240,7 @@ if [ ${MODE} = "whole_infer" ] || [ ${MODE} = "klquant_whole_infer" ]; then echo $export_cmd eval $export_cmd status_export=$? - status_check $status_export "${export_cmd}" "${status_log}" + status_check $status_export "${export_cmd}" "${status_log}" "${model_name}" else save_infer_dir=${infer_model} fi @@ -315,7 +315,9 @@ else set_batchsize=$(func_set_params "${train_batch_key}" "${train_batch_value}") set_train_params1=$(func_set_params "${train_param_key1}" "${train_param_value1}") set_use_gpu=$(func_set_params "${train_use_gpu_key}" "${train_use_gpu}") - if [ ${#ips} -le 26 ];then + # if length of ips >= 15, then it is seen as multi-machine + # 15 is the min length of ips info for multi-machine: 0.0.0.0,0.0.0.0 + if [ ${#ips} -le 15 ];then save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}" nodes=1 else @@ -330,14 +332,14 @@ else set_save_model=$(func_set_params "${save_model_key}" "${save_log}") if [ ${#gpu} -le 2 ];then # train with cpu or single gpu cmd="${python} ${run_train} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config} " - elif [ ${#ips} -le 26 ];then # train with multi-gpu + elif [ ${#ips} -le 15 ];then # train with multi-gpu cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config}" else # train with multi-machine cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_pretrain} ${set_epoch} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config}" fi # run train eval $cmd - status_check $? "${cmd}" "${status_log}" + status_check $? "${cmd}" "${status_log}" "${model_name}" set_eval_pretrain=$(func_set_params "${pretrain_model_key}" "${save_log}/${train_model_name}") @@ -347,7 +349,7 @@ else set_eval_params1=$(func_set_params "${eval_key1}" "${eval_value1}") eval_cmd="${python} ${eval_py} ${set_eval_pretrain} ${set_use_gpu} ${set_eval_params1}" eval $eval_cmd - status_check $? "${eval_cmd}" "${status_log}" + status_check $? "${eval_cmd}" "${status_log}" "${model_name}" fi # run export model if [ ${run_export} != "null" ]; then @@ -357,7 +359,7 @@ else set_save_infer_key=$(func_set_params "${save_infer_key}" "${save_infer_path}") export_cmd="${python} ${run_export} ${set_export_weight} ${set_save_infer_key}" eval $export_cmd - status_check $? "${export_cmd}" "${status_log}" + status_check $? "${export_cmd}" "${status_log}" "${model_name}" #run inference eval $env diff --git a/tools/end2end/convert_ppocr_label.py b/tools/end2end/convert_ppocr_label.py index 8084cac785125f23885399931f98531326b6fb20..c64b9ed168113879182262b609bea692fcb73165 100644 --- a/tools/end2end/convert_ppocr_label.py +++ b/tools/end2end/convert_ppocr_label.py @@ -85,10 +85,16 @@ def convert_label(label_dir, mode="gt", save_dir="./save_results/"): print("The convert label saved in {}".format(save_dir)) -if __name__ == "__main__": +def parse_args(): + import argparse + parser = argparse.ArgumentParser(description="args") + parser.add_argument("--label_path", type=str, required=True) + parser.add_argument("--save_folder", type=str, required=True) + parser.add_argument("--mode", type=str, default=False) + args = parser.parse_args() + return args - ppocr_label_gt = "/paddle/Datasets/chinese/test_set/Label_refine_310_V2.txt" - convert_label(ppocr_label_gt, "gt", "./save_gt_310_V2/") - ppocr_label_gt = "./infer_results/ch_PPOCRV2_infer.txt" - convert_label(ppocr_label_gt_en, "pred", "./save_PPOCRV2_infer/") +if __name__ == "__main__": + args = parse_args() + convert_label(args.label_path, args.mode, args.save_folder) diff --git a/tools/end2end/readme.md b/tools/end2end/readme.md index 69da06dcdabc92c0b6f1831341e592e674ea7473..636ee764aef35a551f729cce20c16357ddf4f495 100644 --- a/tools/end2end/readme.md +++ b/tools/end2end/readme.md @@ -23,19 +23,13 @@ all-sum-510/00224225.jpg [{"transcription": "超赞", "points": [[8.0, 48 **步骤二:** 将步骤一保存的数据转换为端对端评测需要的数据格式: -修改 `tools/convert_ppocr_label.py`中的代码,convert_label函数中设置输入标签路径,Mode,保存标签路径等,对预测数据的GTlabel和预测结果的label格式进行转换。 -``` -ppocr_label_gt = "gt_label.txt" -convert_label(ppocr_label_gt, "gt", "./save_gt_label/") +修改 `tools/end2end/convert_ppocr_label.py`中的代码,convert_label函数中设置输入标签路径,Mode,保存标签路径等,对预测数据的GTlabel和预测结果的label格式进行转换。 -ppocr_label_gt = "./ch_PP-OCRv2_results/system_results.txt" -convert_label(ppocr_label_gt_en, "pred", "./save_PPOCRV2_infer/") ``` +python3 tools/end2end/convert_ppocr_label.py --mode=gt --label_path=path/to/label_txt --save_folder=save_gt_label -运行`convert_ppocr_label.py`: -``` -python3 tools/convert_ppocr_label.py +python3 tools/end2end/convert_ppocr_label.py --mode=pred --label_path=path/to/pred_txt --save_folder=save_PPOCRV2_infer ``` 得到如下结果: diff --git a/tools/export_model.py b/tools/export_model.py index c0cbcd361cec31c51616a7154836c234f076a86e..3ea0228f857a2fadb36678ecd3b91bc865e56e46 100755 --- a/tools/export_model.py +++ b/tools/export_model.py @@ -76,7 +76,7 @@ def export_single_model(model, arch_config, save_path, logger, quanter=None): else: infer_shape = [3, -1, -1] if arch_config["model_type"] == "rec": - infer_shape = [3, 32, -1] # for rec model, H must be 32 + infer_shape = [3, 48, -1] # for rec model, H must be 32 if "Transform" in arch_config and arch_config[ "Transform"] is not None and arch_config["Transform"][ "name"] == "TPS": diff --git a/tools/infer/utility.py b/tools/infer/utility.py index 48b16db4a0f2c2c901509d691088d3dc4381fabd..366212f228eec33f11c825bfaf1e360258af9b2e 100644 --- a/tools/infer/utility.py +++ b/tools/infer/utility.py @@ -34,6 +34,7 @@ def init_args(): parser = argparse.ArgumentParser() # params for prediction engine parser.add_argument("--use_gpu", type=str2bool, default=True) + parser.add_argument("--use_xpu", type=str2bool, default=False) parser.add_argument("--ir_optim", type=str2bool, default=True) parser.add_argument("--use_tensorrt", type=str2bool, default=False) parser.add_argument("--min_subgraph_size", type=int, default=15) @@ -201,7 +202,8 @@ def create_predictor(args, mode, logger): workspace_size=1 << 30, precision_mode=precision, max_batch_size=args.max_batch_size, - min_subgraph_size=args.min_subgraph_size) + min_subgraph_size=args.min_subgraph_size, + use_calib_mode=False) # skip the minmum trt subgraph use_dynamic_shape = True if mode == "det": @@ -286,6 +288,8 @@ def create_predictor(args, mode, logger): config.set_trt_dynamic_shape_info( min_input_shape, max_input_shape, opt_input_shape) + elif args.use_xpu: + config.enable_xpu(10 * 1024 * 1024) else: config.disable_gpu() if hasattr(args, "cpu_threads"): diff --git a/tools/program.py b/tools/program.py index 7c02dc0149f36085ef05ca378b79d27e92d6dd57..aa0d2698cf66c928f87217996c31c042e1c8aa02 100755 --- a/tools/program.py +++ b/tools/program.py @@ -112,20 +112,25 @@ def merge_config(config, opts): return config -def check_gpu(use_gpu): +def check_device(use_gpu, use_xpu=False): """ Log error and exit when set use_gpu=true in paddlepaddle cpu version. """ - err = "Config use_gpu cannot be set as true while you are " \ - "using paddlepaddle cpu version ! \nPlease try: \n" \ - "\t1. Install paddlepaddle-gpu to run model on GPU \n" \ - "\t2. Set use_gpu as false in config file to run " \ + err = "Config {} cannot be set as true while your paddle " \ + "is not compiled with {} ! \nPlease try: \n" \ + "\t1. Install paddlepaddle to run model on {} \n" \ + "\t2. Set {} as false in config file to run " \ "model on CPU" try: + if use_gpu and use_xpu: + print("use_xpu and use_gpu can not both be ture.") if use_gpu and not paddle.is_compiled_with_cuda(): - print(err) + print(err.format("use_gpu", "cuda", "gpu", "use_gpu")) + sys.exit(1) + if use_xpu and not paddle.device.is_compiled_with_xpu(): + print(err.format("use_xpu", "xpu", "xpu", "use_xpu")) sys.exit(1) except Exception as e: pass @@ -547,7 +552,7 @@ def preprocess(is_train=False): # check if set use_gpu=True in paddlepaddle cpu version use_gpu = config['Global']['use_gpu'] - check_gpu(use_gpu) + use_xpu = config['Global'].get('use_xpu', False) # check if set use_xpu=True in paddlepaddle cpu/gpu version use_xpu = False @@ -562,11 +567,13 @@ def preprocess(is_train=False): 'SEED', 'SDMGR', 'LayoutXLM', 'LayoutLM', 'PREN', 'FCE', 'SVTR' ] - device = 'cpu' - if use_gpu: - device = 'gpu:{}'.format(dist.ParallelEnv().dev_id) if use_xpu: - device = 'xpu' + device = 'xpu:{0}'.format(os.getenv('FLAGS_selected_xpus', 0)) + else: + device = 'gpu:{}'.format(dist.ParallelEnv() + .dev_id) if use_gpu else 'cpu' + check_device(use_gpu, use_xpu) + device = paddle.set_device(device) config['Global']['distributed'] = dist.get_world_size() != 1