diff --git a/README.md b/README.md index 81a9ddaa36d7dceba3071fca48cb2f649e6b239c..c72395d2f85f9f2844b895a12bb51a783a679f63 100644 --- a/README.md +++ b/README.md @@ -27,8 +27,8 @@ PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools ## Visualization
- - + +
The above pictures are the visualizations of the general ppocr_server model. For more effect pictures, please see [More visualizations](./doc/doc_en/visualization_en.md). @@ -58,6 +58,7 @@ Mobile DEMO experience (based on EasyEdge and Paddle-Lite, supports iOS and Andr + ## PP-OCR 2.0 series model list（Update on Dec 15） | Model introduction | Model name | Recommended scene | Detection model | Direction classifier | Recognition model | @@ -129,21 +130,21 @@ PP-OCR is a practical ultra-lightweight OCR system. It is mainly composed of thr ## Visualization [more](./doc/doc_en/visualization_en.md) - Chinese OCR model
- - - - + + + +
- English OCR model
- +
- Multilingual OCR model
- - + +
diff --git a/README_ch.md b/README_ch.md index 1bad66a182bd8833685d58dc8438663412a9feea..929fca50a709ec486cacf16e493f220fd0dbb83d 100644 --- a/README_ch.md +++ b/README_ch.md @@ -36,8 +36,8 @@ PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库，助力 ## 效果展示
- - + +
上图是通用ppocr_server模型效果展示，更多效果图请见[效果展示页面](./doc/doc_ch/visualization.md)。 @@ -120,10 +120,10 @@ PP-OCR是一个实用的超轻量OCR系统。主要由DB文本检测、检测框 ## 效果展示 [more](./doc/doc_ch/visualization.md) - 中文模型
- - - - + + + +
- 英文模型 @@ -133,8 +133,8 @@ PP-OCR是一个实用的超轻量OCR系统。主要由DB文本检测、检测框 - 其他语言模型
- - + +
diff --git a/StyleTextRec/README_ch.md b/StyleTextRec/README_ch.md index 60edf343d753e6baf141798a4e88ca60bf4be132..b85615309f9a27187cd5378cc4b61fe2e4d6c50e 100644 --- a/StyleTextRec/README_ch.md +++ b/StyleTextRec/README_ch.md @@ -1,29 +1,31 @@ ## Style Text Rec ### 目录 -[工具简介](#工具简介) -[环境配置](#环境配置) -[快速上手](#快速上手) -[高级使用](#高级使用) -[应用示例](#应用示例) +- [工具简介](#工具简介) +- [环境配置](#环境配置) +- [快速上手](#快速上手) +- [高级使用](#高级使用) +- [应用示例](#应用示例) ### 工具简介
-Style-Text是对百度自研文本编辑算法《Editing Text in the Wild》中提出的SRNet网络的改进，不同于常用的GAN的方法只选择一个分支，该工具将文本合成任务分解为三个子模块，文本风格迁移模块、背景抽取模块和前背景融合模块，来提升合成数据的效果。下图显示了一些示例结果。 -
- - +
-此外，在实际铭牌文本识别场景和韩语文本识别场景，验证了该合成工具的有效性。 +Style-Text数据合成工具是基于百度自研的文本编辑算法《Editing Text in the Wild》https://arxiv.org/abs/1908.03047 +不同于常用的基于GAN的数据合成工具，Style-Text主要框架包括：1.文本前景风格迁移模块 2.背景抽取模块 3.融合模块。经过这样三步，就可以迅速实现图片文字风格迁移。下图是一些该数据合成工具效果图。 + +
+ +
### 环境配置 -1. 参考[快速安装](../doc/doc_ch/installation.md)，安装PaddleOCR。强烈建议您使用python3环境。 +1. 参考[快速安装](../doc/doc_ch/installation.md)，安装PaddleOCR。 2. 进入`style_text_rec`目录，下载模型，并解压： ```bash @@ -159,4 +161,4 @@ style_text_rec |-- logging.py |-- math_functions.py `-- sys_funcs.py -``` \ No newline at end of file +``` diff --git a/doc/doc_ch/inference.md b/doc/doc_ch/inference.md index f9437d0772c0612d78938781b265da35253e21cd..962b4ae748922ce6067a7ee4e609366ba1f3e01d 100644 --- a/doc/doc_ch/inference.md +++ b/doc/doc_ch/inference.md @@ -128,24 +128,32 @@ python3 tools/export_model.py -c configs/cls/cls_mv3.yml -o Global.pretrained_mo 超轻量中文检测模型推理，可以执行如下命令： ``` -python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" +# 下载超轻量中文检测模型： +wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar +tar xf ch_ppocr_mobile_v2.0_det_infer.tar +python3 tools/infer/predict_det.py --image_dir="./doc/imgs/22.jpg" --det_model_dir="./ch_ppocr_mobile_v2.0_det_infer/" ``` 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'det_res'。结果示例如下： -![](../imgs_results/det_res_2.jpg) +![](../imgs_results/det_res_22.jpg) -通过参数`limit_type`和`det_limit_side_len`来对图片的尺寸进行限制限，`limit_type=max`为限制长边长度<`det_limit_side_len`，`limit_type=min`为限制短边长度>`det_limit_side_len`, -图片不满足限制条件时(`limit_type=max`时长边长度>`det_limit_side_len`或`limit_type=min`时短边长度<`det_limit_side_len`)，将对图片进行等比例缩放。 -该参数默认设置为`limit_type='max',det_max_side_len=960`。 如果输入图片的分辨率比较大，而且想使用更大的分辨率预测，可以执行如下命令： +通过参数`limit_type`和`det_limit_side_len`来对图片的尺寸进行限制， +`litmit_type`可选参数为[`max`, `min`]， +`det_limit_size_len` 为正整数，一般设置为32 的倍数，比如960。 +参数默认设置为`limit_type='max', det_limit_side_len=960`。表示网络输入图像的最长边不能超过960， +如果超过这个值，会对图像做等宽比的resize操作，确保最长边为`det_limit_side_len`。 +设置为`limit_type='min', det_limit_side_len=960` 则表示限制图像的最短边为960。 + +如果输入图片的分辨率比较大，而且想使用更大的分辨率预测，可以设置det_limit_side_len 为想要的值，比如1216： ``` -python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --det_limit_type=max --det_limit_side_len=1200 +python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --det_limit_type=max --det_limit_side_len=1216 ``` 如果想使用CPU进行预测，执行命令如下 ``` -python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --use_gpu=False +python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --use_gpu=False ``` diff --git a/doc/doc_ch/visualization.md b/doc/doc_ch/visualization.md index 4cd3264b802299d53c71bfdc02d197419048b03a..f2ea2b09d9431ebd710f2d7ccac0bd73c50b558e 100644 --- a/doc/doc_ch/visualization.md +++ b/doc/doc_ch/visualization.md @@ -1,49 +1,32 @@ # 效果展示 - -## 通用ppocr_server_2.0效果展示 + +## 通用ppocr_server_2.0 效果展示
- - - - - - + + + + + + + + + +
## 英文识别模型效果展示
- +
## 多语言识别模型效果展示
- - -
- - - -## 超轻量ppocr_mobile_1.0效果展示 - -
- - - - -
- - - -## 通用ppocr_server_1.0效果展示 - -
- - - + +
diff --git a/doc/doc_en/inference_en.md b/doc/doc_en/inference_en.md index 826aad692a31567708609b142c5f3c9337a36dd3..85dc261c89098b7579336b429d7663cb1c0864f5 100644 --- a/doc/doc_en/inference_en.md +++ b/doc/doc_en/inference_en.md @@ -134,24 +134,33 @@ Because EAST and DB algorithms are very different, when inference, it is necessa For lightweight Chinese detection model inference, you can execute the following commands: ``` -python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" +# download DB text detection inference model +wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar +tar xf ch_ppocr_mobile_v2.0_det_infer.tar +# predict +python3 tools/infer/predict_det.py --image_dir="./doc/imgs/22.jpg" --det_model_dir="./inference/det_db/" ``` The visual text detection results are saved to the ./inference_results folder by default, and the name of the result file is prefixed with'det_res'. Examples of results are as follows: -![](../imgs_results/det_res_2.jpg) +![](../imgs_results/det_res_22.jpg) -The size of the image is limited by the parameters `limit_type` and `det_limit_side_len`, `limit_type=max` is to limit the length of the long side <`det_limit_side_len`, and `limit_type=min` is to limit the length of the short side>`det_limit_side_len`, -When the picture does not meet the restriction conditions (for `limit_type=max`and long side >`det_limit_side_len` or for `min` and short side <`det_limit_side_len`), the image will be scaled proportionally. -This parameter is set to `limit_type='max', det_max_side_len=960` by default. If the resolution of the input picture is relatively large, and you want to use a larger resolution prediction, you can execute the following command: +You can use the parameters `limit_type` and `det_limit_side_len` to limit the size of the input image, +The optional parameters of `litmit_type` are [`max`, `min`], and +`det_limit_size_len` is a positive integer, generally set to a multiple of 32, such as 960. +The default setting of the parameters is `limit_type='max', det_limit_side_len=960`. Indicates that the longest side of the network input image cannot exceed 960, +If this value is exceeded, the image will be resized with the same width ratio to ensure that the longest side is `det_limit_side_len`. +Set as `limit_type='min', det_limit_side_len=960`, it means that the shortest side of the image is limited to 960. + +If the resolution of the input picture is relatively large and you want to use a larger resolution prediction, you can set det_limit_side_len to the desired value, such as 1216: ``` -python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --det_limit_type=max --det_limit_side_len=1200 +python3 tools/infer/predict_det.py --image_dir="./doc/imgs/22.jpg" --det_model_dir="./inference/det_db/" --det_limit_type=max --det_limit_side_len=1216 ``` If you want to use the CPU for prediction, execute the command as follows ``` -python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --use_gpu=False +python3 tools/infer/predict_det.py --image_dir="./doc/imgs/22.jpg" --det_model_dir="./inference/det_db/" --use_gpu=False ``` diff --git a/doc/doc_en/visualization_en.md b/doc/doc_en/visualization_en.md index 2b88b1de6042b6f63cefb85134f58d83d4c625f8..732ca9ea6240f3b00d6c902b24296c53fe6af245 100644 --- a/doc/doc_en/visualization_en.md +++ b/doc/doc_en/visualization_en.md @@ -1,49 +1,34 @@ # Visualization - -## ch_ppocr_server_1.1 - -
- - - - - - -
- - - -## en_ppocr_mobile_1.1 -
- -
+ +## ch_ppocr_server_2.0 - -## (multilingual)_ppocr_mobile_1.1
- - + + + + + + + + + +
- -## ppocr_mobile_1.0 + +## en_ppocr_mobile_2.0
- - - - +
- -## ppocr_server_1.0 - + +## (multilingual)_ppocr_mobile_2.0
- - - + +
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