Merge pull request #6138 from andyjpaddle/dygraph

update hubserving for PPOCRv3

deploy/hubserving/ocr_det/params.py

@@ -26,7 +26,7 @@ def read_params():
 
     #params for text detector
     cfg.det_algorithm = "DB"
-    cfg.det_model_dir = "./inference/ch_PP-OCRv2_det_infer/"
+    cfg.det_model_dir = "./inference/ch_PP-OCRv3_det_infer/"
     cfg.det_limit_side_len = 960
     cfg.det_limit_type = 'max'
 

deploy/hubserving/ocr_rec/params.py

@@ -26,9 +26,9 @@ def read_params():
 
     #params for text recognizer
     cfg.rec_algorithm = "CRNN"
-    cfg.rec_model_dir = "./inference/ch_PP-OCRv2_rec_infer/"
+    cfg.rec_model_dir = "./inference/ch_PP-OCRv3_rec_infer/"
 
-    cfg.rec_image_shape = "3, 32, 320"
+    cfg.rec_image_shape = "3, 48, 320"
     cfg.rec_batch_num = 6
     cfg.max_text_length = 25
 

deploy/hubserving/ocr_system/params.py

@@ -26,7 +26,7 @@ def read_params():
 
     #params for text detector
     cfg.det_algorithm = "DB"
-    cfg.det_model_dir = "./inference/ch_PP-OCRv2_det_infer/"
+    cfg.det_model_dir = "./inference/ch_PP-OCRv3_det_infer/"
     cfg.det_limit_side_len = 960
     cfg.det_limit_type = 'max'
 
@@ -44,9 +44,9 @@ def read_params():
 
     #params for text recognizer
     cfg.rec_algorithm = "CRNN"
-    cfg.rec_model_dir = "./inference/ch_PP-OCRv2_rec_infer/"
+    cfg.rec_model_dir = "./inference/ch_PP-OCRv3_rec_infer/"
 
-    cfg.rec_image_shape = "3, 32, 320"
+    cfg.rec_image_shape = "3, 48, 320"
     cfg.rec_batch_num = 6
     cfg.max_text_length = 25
 

deploy/hubserving/readme.md

@@ -41,6 +41,7 @@ deploy/hubserving/ocr_system/
 ```
 ## 1. 近期更新
 
+* 2022.05.05 新增PP-OCRv3检测和识别模型。
 * 2022.03.30 新增PP-Structure和表格识别两种服务。
 
 ## 2. 快速启动服务
@@ -53,10 +54,10 @@ pip3 install paddlehub==2.1.0 --upgrade -i https://mirror.baidu.com/pypi/simple
 ```
 
 ### 2.2 下载推理模型
-安装服务模块前，需要准备推理模型并放到正确路径。默认使用的是PP-OCRv2模型，默认模型路径为：
+安装服务模块前，需要准备推理模型并放到正确路径。默认使用的是PP-OCRv3模型，默认模型路径为：
 ```
-检测模型：./inference/ch_PP-OCRv2_det_infer/
-识别模型：./inference/ch_PP-OCRv2_rec_infer/
+检测模型：./inference/ch_PP-OCRv3_det_infer/
+识别模型：./inference/ch_PP-OCRv3_rec_infer/
 方向分类器：./inference/ch_ppocr_mobile_v2.0_cls_infer/
 表格结构识别模型：./inference/en_ppocr_mobile_v2.0_table_structure_infer/
 ```  
@@ -223,6 +224,7 @@ hub serving start -c deploy/hubserving/ocr_system/config.json
 
 - 2、 到相应的`module.py`和`params.py`等文件中根据实际需求修改代码。  
 例如，如果需要替换部署服务所用模型，则需要到`params.py`中修改模型路径参数`det_model_dir`和`rec_model_dir`，如果需要关闭文本方向分类器，则将参数`use_angle_cls`置为`False`，当然，同时可能还需要修改其他相关参数，请根据实际情况修改调试。 **强烈建议修改后先直接运行`module.py`调试，能正确运行预测后再启动服务测试。**
+**注意** PPOCR-v3识别模型使用的图片输入shape为`3,48,320`,因此需要修改`params.py`中的`cfg.rec_image_shape = "3, 48, 320"`，如果不使用PPOCR-v3识别模型，则无需修改该参数。
 
 - 3、 卸载旧服务包  
 ```hub uninstall ocr_system```  

deploy/hubserving/readme_en.md

@@ -41,6 +41,7 @@ deploy/hubserving/ocr_system/
 ```
 ## 1. Update
 
+* 2022.05.05 add PP-OCRv3 text detection and recognition models.
 * 2022.03.30 add PP-Structure and table recognition services。
 
 
@@ -55,10 +56,10 @@ pip3 install paddlehub==2.1.0 --upgrade -i https://pypi.tuna.tsinghua.edu.cn/sim
 ```
 
 ### 2.2 Download inference model
-Before installing the service module, you need to prepare the inference model and put it in the correct path. By default, the PP-OCRv2 models are used, and the default model path is:  
+Before installing the service module, you need to prepare the inference model and put it in the correct path. By default, the PP-OCRv3 models are used, and the default model path is:  
 ```
-text detection model: ./inference/ch_PP-OCRv2_det_infer/
-text recognition model: ./inference/ch_PP-OCRv2_rec_infer/
+text detection model: ./inference/ch_PP-OCRv3_det_infer/
+text recognition model: ./inference/ch_PP-OCRv3_rec_infer/
 text angle classifier: ./inference/ch_ppocr_mobile_v2.0_cls_infer/
 tanle recognition: ./inference/en_ppocr_mobile_v2.0_table_structure_infer/
 ```  
@@ -233,6 +234,7 @@ hub serving stop --port/-p XXXX
 ```
 - 2. Modify the code in the corresponding files, like `module.py` and `params.py`, according to the actual needs.  
 For example, if you need to replace the model used by the deployed service, you need to modify model path parameters `det_model_dir` and `rec_model_dir` in `params.py`. If you want to turn off the text direction classifier, set the parameter `use_angle_cls` to `False`. Of course, other related parameters may need to be modified at the same time. Please modify and debug according to the actual situation. It is suggested to run `module.py` directly for debugging after modification before starting the service test.  
+**Note** The image input shape used by the PPOCR-v3 recognition model is `3, 48, 320`, so you need to modify `cfg.rec_image_shape = "3, 48, 320"` in `params.py`, if you do not use the PPOCR-v3 recognition model, then there is no need to modify this parameter.
 - 3. Uninstall old service module
 ```shell
 hub uninstall ocr_system