Merge branch 'dygraph' of https://github.com/PaddlePaddle/PaddleOCR into update_readme_1215

README.md

@@ -27,8 +27,8 @@ PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools
 ## Visualization
 
 <div align="center">
-    <img src="doc/imgs_results/1101.jpg" width="800">
-    <img src="doc/imgs_results/1103.jpg" width="800">
+    <img src="doc/imgs_results/ch_ppocr_mobile_v2.0/test_add_91.jpg" width="800">
+    <img src="doc/imgs_results/ch_ppocr_mobile_v2.0/00018069.jpg" width="800">
 </div>
 
 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
 
 <a name="Supported-Chinese-model-list"></a>
 
+
 ## 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
 <div align="center">
-    <img src="./doc/imgs_results/1102.jpg" width="800">
-    <img src="./doc/imgs_results/1104.jpg" width="800">
-    <img src="./doc/imgs_results/1106.jpg" width="800">
-    <img src="./doc/imgs_results/1105.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/test_add_91.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/00015504.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/00056221.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/rotate_00052204.jpg" width="800">
 </div>
 
 - English OCR model
 <div align="center">
-    <img src="./doc/imgs_results/img_12.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/img_12.jpg" width="800">
 </div>
 
 - Multilingual OCR model
 <div align="center">
-    <img src="./doc/imgs_results/1110.jpg" width="800">
-    <img src="./doc/imgs_results/1112.jpg" width="800">
+    <img src="./doc/imgs_results/french_0.jpg" width="800">
+    <img src="./doc/imgs_results/korean.jpg" width="800">
 </div>
 
 

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
 
 <div align="center">
-    <img src="doc/imgs_results/1101.jpg" width="800">
-    <img src="doc/imgs_results/1103.jpg" width="800">
+    <img src="doc/imgs_results/ch_ppocr_mobile_v2.0/test_add_91.jpg" width="800">
+    <img src="doc/imgs_results/ch_ppocr_mobile_v2.0/00018069.jpg" width="800">
 </div>
 
 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
 <div align="center">
-    <img src="./doc/imgs_results/1102.jpg" width="800">
-    <img src="./doc/imgs_results/1104.jpg" width="800">
-    <img src="./doc/imgs_results/1106.jpg" width="800">
-    <img src="./doc/imgs_results/1105.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/test_add_91.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/00015504.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/00056221.jpg" width="800">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/rotate_00052204.jpg" width="800">
 </div>
 
 - 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
 <div align="center">
-    <img src="./doc/imgs_results/1110.jpg" width="800">
-    <img src="./doc/imgs_results/1112.jpg" width="800">
+    <img src="./doc/imgs_results/french_0.jpg" width="800">
+    <img src="./doc/imgs_results/korean.jpg" width="800">
 </div>
 
 <a name="欢迎加入PaddleOCR技术交流群"></a>

StyleTextRec/README_ch.md

 ## 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
 <div align="center">
     <img src="doc/images/3.png" width="800">
 </div>
 
-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。
-
 <div align="center">
-    <img src="doc/images/1.png" width="800">
-    <img src="doc/images/2.png" width="800">
+    <img src="doc/images/1.png" width="600">
 </div>
 
-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。
+
+<div align="center">
+    <img src="doc/images/2.png" width="1000">
+</div>
 
 ### 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
+```

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
 ```
 
 <a name="DB文本检测模型推理"></a>

doc/doc_ch/visualization.md

 # 效果展示
 
-<a name="通用ppocr_server_2.0效果展示"></a>
-## 通用ppocr_server_2.0效果展示
+<a name="超轻量ppocr_server_2.0效果展示"></a>
+## 通用ppocr_server_2.0 效果展示
 
 <div align="center">
-    <img src="../imgs_results/1101.jpg" width="800">
-    <img src="../imgs_results/1102.jpg" width="800">
-    <img src="../imgs_results/1103.jpg" width="800">
-    <img src="../imgs_results/1104.jpg" width="800">
-    <img src="../imgs_results/1105.jpg" width="800">
-    <img src="../imgs_results/1106.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00006737.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00009282.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00015504.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00018069.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00056221.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00057937.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00059985.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00111002.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00077949.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00207393.jpg" width="800">
 </div>
 
 
 <a name="英文识别模型效果展示"></a>
 ## 英文识别模型效果展示
 <div align="center">
-    <img src="../imgs_results/img_12.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/img_12.jpg" width="800">
 </div>
 
 
 <a name="多语言识别模型效果展示"></a>
 ## 多语言识别模型效果展示
 <div align="center">
-    <img src="../imgs_results/1110.jpg" width="800">
-    <img src="../imgs_results/1112.jpg" width="800">
-</div>
-
-
-<a name="超轻量ppocr_mobile_1.0效果展示"></a>
-## 超轻量ppocr_mobile_1.0效果展示
-
-<div align="center">
-    <img src="../imgs_results/1.jpg" width="800">
-    <img src="../imgs_results/7.jpg" width="800">
-    <img src="../imgs_results/6.jpg" width="800">
-    <img src="../imgs_results/16.png" width="800">
-</div>
-
-
-<a name="通用ppocr_server_1.0效果展示"></a>
-## 通用ppocr_server_1.0效果展示
-
-<div align="center">
-    <img src="../imgs_results/chinese_db_crnn_server/11.jpg" width="800">
-    <img src="../imgs_results/chinese_db_crnn_server/2.jpg" width="800">
-    <img src="../imgs_results/chinese_db_crnn_server/8.jpg" width="800">
+    <img src="../imgs_results/french_0.jpg" width="800">
+    <img src="../imgs_results/korean.jpg" width="800">
 </div>

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
 ```
 
 <a name="DB_DETECTION"></a>

doc/doc_en/visualization_en.md

 # Visualization
 
-<a name="ppocr_server_1.1"></a>
-## ch_ppocr_server_1.1
-
-<div align="center">
-    <img src="../imgs_results/1101.jpg" width="800">
-    <img src="../imgs_results/1102.jpg" width="800">
-    <img src="../imgs_results/1103.jpg" width="800">
-    <img src="../imgs_results/1104.jpg" width="800">
-    <img src="../imgs_results/1105.jpg" width="800">
-    <img src="../imgs_results/1106.jpg" width="800">
-</div>
-
-
-<a name="en_ppocr_mobile_1.1"></a>
-## en_ppocr_mobile_1.1
-<div align="center">
-    <img src="../imgs_results/img_12.jpg" width="800">
-</div>
 
+<a name="ppocr_server_2.0"></a>
+## ch_ppocr_server_2.0
 
-<a name="multilingual"></a>
-## (multilingual)_ppocr_mobile_1.1
 <div align="center">
-    <img src="../imgs_results/1110.jpg" width="800">
-    <img src="../imgs_results/1112.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00006737.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00009282.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00015504.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00018069.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00056221.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00057937.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00059985.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00111002.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00077949.jpg" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00207393.jpg" width="800">
 </div>
 
 
-<a name="ppocr_mobile_1.0"></a>
-## ppocr_mobile_1.0
 
+<a name="en_ppocr_mobile_2.0"></a>
+## en_ppocr_mobile_2.0
 <div align="center">
-    <img src="../imgs_results/1.jpg" width="800">
-    <img src="../imgs_results/7.jpg" width="800">
-    <img src="../imgs_results/6.jpg" width="800">
-    <img src="../imgs_results/16.png" width="800">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/img_12.jpg" width="800">
 </div>
 
 
-<a name="ppocr_server_1.0"></a>
-## ppocr_server_1.0
-
+<a name="multilingual"></a>
+## (multilingual)_ppocr_mobile_2.0
 <div align="center">
-    <img src="../imgs_results/chinese_db_crnn_server/11.jpg" width="800">
-    <img src="../imgs_results/chinese_db_crnn_server/2.jpg" width="800">
-    <img src="../imgs_results/chinese_db_crnn_server/8.jpg" width="800">
+    <img src="./doc/imgs_results/french_0.jpg" width="800">
+    <img src="./doc/imgs_results/korean.jpg" width="800">
 </div>