From 5488aaedb3830bb458ca55557f2994ec8a8ab263 Mon Sep 17 00:00:00 2001 From: MissPenguin Date: Thu, 14 Apr 2022 11:21:03 +0000 Subject: [PATCH] update doc --- README_ch.md | 21 ++++++--- doc/doc_ch/algorithm_det_db.md | 75 ++++++++++++--------------------- doc/doc_ch/application.md | 1 + doc/doc_ch/quickstart.md | 1 - doc/features.png | Bin 1023229 -> 1209567 bytes 5 files changed, 44 insertions(+), 54 deletions(-) create mode 100644 doc/doc_ch/application.md diff --git a/README_ch.md b/README_ch.md index e3d8176d..6a43040a 100755 --- a/README_ch.md +++ b/README_ch.md @@ -35,19 +35,19 @@ PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库,助力 > 上述内容的使用方法建议从文档教程中的快速开始体验 -## 零代码体验 +## 快速开始 - 在线网站体验:超轻量PP-OCR mobile模型体验地址:https://www.paddlepaddle.org.cn/hub/scene/ocr -- 移动端:[安装包DEMO下载地址](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite)(基于EasyEdge和Paddle-Lite, 支持iOS和Android系统) - +- 移动端demo体验:[安装包DEMO下载地址](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite)(基于EasyEdge和Paddle-Lite, 支持iOS和Android系统) +- [快速开始(中英文/多语言/文档分析)](./doc/doc_ch/quickstart.md) + ## 《动手学OCR》电子书 - [《动手学OCR》电子书📚](./doc/doc_ch/ocr_book.md) - - -## 社区、社区贡献与社区常规赛 + +## 开源社区 - **加入社区**👬:微信扫描下方二维码加入官方交流群,与各行各业开发者充分交流,期待您的加入。 - **社区贡献**🏅️:[社区贡献](./doc/doc_ch/thirdparty.md)文档中包含了社区用户**使用PaddleOCR开发的各种工具、应用**以及**为PaddleOCR贡献的功能、优化的文档与代码**等,是官方为社区开发者打造的荣誉墙,也是帮助优质项目宣传的广播站。 @@ -74,6 +74,12 @@ PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库,助力 - [运行环境准备](./doc/doc_ch/environment.md) - [快速开始(中英文/多语言/文档分析)](./doc/doc_ch/quickstart.md) - [PP-OCR文本检测识别🔥](./doc/doc_ch/ppocr_introduction.md) + +|[模型库](./doc/doc_ch/models_list.md)|[模型训练](./doc/doc_ch/training.md)|模型压缩|[推理部署](./deploy/readme_ch.md)| +| :-------: | :----------: | :---------: | :---------: | +|[模型库](./doc/doc_ch/models_list.md)|[文本检测](./doc/doc_ch/detection.md)
[文本识别](./doc/doc_ch/recognition.md)
[文本方向分类器](./doc/doc_ch/angle_class.md)|[模型量化](./deploy/slim/quantization/README.md)
[模型裁剪](./deploy/slim/prune/README.md)
[知识蒸馏](./doc/doc_ch/knowledge_distillation.md)|[基于Python预测引擎推理](./doc/doc_ch/inference_ppocr.md)
[基于C++预测引擎推理](./deploy/cpp_infer/readme.md)
[服务化部署](./deploy/pdserving/README_CN.md)
[端侧部署](./deploy/lite/readme.md)
[Paddle2ONNX模型转化与预测](./deploy/paddle2onnx/readme.md)
[Benchmark](./doc/doc_ch/benchmark.md)| + +- - [模型库](./doc/doc_ch/models_list.md) - [模型训练](./doc/doc_ch/training.md) - [文本检测](./doc/doc_ch/detection.md) @@ -105,6 +111,7 @@ PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库,助力 - [文本识别算法](./doc/doc_ch/algorithm_overview.md#12-%E6%96%87%E6%9C%AC%E8%AF%86%E5%88%AB%E7%AE%97%E6%B3%95) - [端到端算法](./doc/doc_ch/algorithm_overview.md#2-%E6%96%87%E6%9C%AC%E8%AF%86%E5%88%AB%E7%AE%97%E6%B3%95) - [使用PaddleOCR架构添加新算法](./doc/doc_ch/add_new_algorithm.md) +- [场景应用](./doc/doc_ch/application.md) - 数据标注与合成 - [半自动标注工具PPOCRLabel](./PPOCRLabel/README_ch.md) - [数据合成工具Style-Text](./StyleText/README_ch.md) @@ -119,6 +126,8 @@ PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库,助力 - [DocVQA数据集](./doc/doc_ch/docvqa_datasets.md) - [代码组织结构](./doc/doc_ch/tree.md) - [效果展示](#效果展示) +- [《动手学OCR》电子书📚](#电子书) +- [开源社区](#开源社区) - FAQ - [通用问题](./doc/doc_ch/FAQ.md) - [PaddleOCR实战问题](./doc/doc_ch/FAQ.md) diff --git a/doc/doc_ch/algorithm_det_db.md b/doc/doc_ch/algorithm_det_db.md index 6c92b699..9b52dd74 100644 --- a/doc/doc_ch/algorithm_det_db.md +++ b/doc/doc_ch/algorithm_det_db.md @@ -2,10 +2,16 @@ - [1. 算法简介](#1) - [2. 环境配置](#2) -- [3. 快速使用](#3) -- [4. 模型训练、评估、预测](#4) -- [5. 推理部署](#5) -- [6. FAQ](#6) +- [3. 模型训练、评估、预测](#3) + - [3.1 训练](#3-1) + - [3.2 评估](#3-2) + - [3.3 预测](#3-3) +- [4. 推理部署](#4) + - [4.1 Python推理](#4-1) + - [4.2 C++推理](#4-2) + - [4.3 Serving服务化部署](#4-3) + - [4.4 更多推理部署](#4-4) +- [5. FAQ](#5) ## 1. 算法简介 @@ -29,50 +35,22 @@ -## 3. 快速使用 -参考本节,可以直接下载训好的模型,进行基于训练引擎的模型预测。 - -### 训练模型下载 -根据第1节给出的模型列表,选择下载训练模型: -```bash -mkdir trained_models && cd trained_models -wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar && tar xf det_mv3_db_v2.0_train.tar -cd .. -``` -* windows 环境下如果没有安装wget,下载模型时可将链接复制到浏览器中下载,并解压放置在相应目录下 +## 3. 模型训练、评估、预测 -解压完毕后应有如下文件结构: -``` -├── det_mv3_db_v2.0_train -│ ├── best_accuracy.states -│ ├── best_accuracy.pdparams -│ ├── best_accuracy.pdopt -│ └── train.log -``` -### 单张图像或者图像集合预测 -```bash -# 预测image_dir指定的单张图像 -python3 tools/infer/predict_e2e.py --e2e_algorithm="PGNet" --image_dir="./doc/imgs_en/img623.jpg" --e2e_model_dir="./inference/e2e_server_pgnetA_infer/" --e2e_pgnet_valid_set="totaltext" + +### 3.1 训练 -# 预测image_dir指定的图像集合 -python3 tools/infer/predict_e2e.py --e2e_algorithm="PGNet" --image_dir="./doc/imgs_en/" --e2e_model_dir="./inference/e2e_server_pgnetA_infer/" --e2e_pgnet_valid_set="totaltext" + +### 3.2 评估 -# 如果想使用CPU进行预测,需设置use_gpu参数为False -python3 tools/infer/predict_e2e.py --e2e_algorithm="PGNet" --image_dir="./doc/imgs_en/img623.jpg" --e2e_model_dir="./inference/e2e_server_pgnetA_infer/" --e2e_pgnet_valid_set="totaltext" --use_gpu=False -``` -### 可视化结果 -可视化文本检测结果默认保存到./inference_results文件夹里面,结果文件的名称前缀为'e2e_res'。结果示例如下: -![](../imgs_results/e2e_res_img623_pgnet.jpg) + +### 3.3 预测 -## 4. 模型训练、评估、预测 -### 4.1 训练 -### 4.2 评估 -### 4.3 预测 +## 4. 推理部署 - -## 5. 推理部署 -### 5.1 Python推理 + +### 4.1 Python推理 首先将DB文本检测训练过程中保存的模型,转换成inference model。以基于Resnet50_vd骨干网络,在ICDAR2015英文数据集训练的模型为例( [模型下载地址](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar) ),可以使用如下命令进行转换: ``` @@ -91,17 +69,20 @@ python3 tools/infer/predict_det.py --image_dir="./doc/imgs_en/img_10.jpg" --det_ **注意**:由于ICDAR2015数据集只有1000张训练图像,且主要针对英文场景,所以上述模型对中文文本图像检测效果会比较差。 -### 5.2 C++推理 + +### 4.2 C++推理 敬请期待 -### 5.3 Serving服务化部署 + +### 4.3 Serving服务化部署 敬请期待 -### 5.4 Paddle2ONNX推理 + +### 4.4 更多推理部署 敬请期待 - -## 6. FAQ + +## 5. 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