Merge pull request #6 from PaddlePaddle/develop

update-2020-7-27

deploy/lite/readme_en.md

@@ -3,7 +3,7 @@
 
 This tutorial will introduce how to use paddle-lite to deploy paddleOCR ultra-lightweight Chinese and English detection models on mobile phones.
 
-addle Lite is a lightweight inference engine for PaddlePaddle.
+paddle-lite is a lightweight inference engine for PaddlePaddle.
 It provides efficient inference capabilities for mobile phones and IOTs,
 and extensively integrates cross-platform hardware to provide lightweight
 deployment solutions for end-side deployment issues.

deploy/pdserving/readme.md

@@ -9,9 +9,21 @@
 我们推荐用户使用GPU来做Paddle Serving的OCR服务部署 
 
 **CUDA版本：9.0**
+
 **CUDNN版本：7.0**
+
 **操作系统版本：CentOS 6以上**
 
+**Python3操作指南：**
+```
+#以下提供beta版本的paddle serving whl包，欢迎试用，正式版会在7月底正式上线
+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/others/paddle_serving_server_gpu-0.3.2-py3-none-any.whl
+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/others/paddle_serving_client-0.3.2-cp36-none-any.whl
+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/others/paddle_serving_app-0.1.2-py3-none-any.whl
+python -m pip install paddle_serving_app-0.1.2-py3-none-any.whl paddle_serving_server_gpu-0.3.2-py3-none-any.whl paddle_serving_client-0.3.2-cp36-none-any.whl
+```
+
+**Python2操作指南：**
 ```
 #以下提供beta版本的paddle serving whl包，欢迎试用，正式版会在7月底正式上线
 wget --no-check-certificate https://paddle-serving.bj.bcebos.com/others/paddle_serving_server_gpu-0.3.2-py2-none-any.whl

doc/doc_ch/serving.md

@@ -28,21 +28,38 @@ deploy/hubserving/ocr_system/
 # 安装paddlehub  
 pip3 install paddlehub --upgrade -i https://pypi.tuna.tsinghua.edu.cn/simple
 
-# 设置环境变量  
+# 在Linux下设置环境变量
 export PYTHONPATH=.
-```   
+# 在Windows下设置环境变量
+SET PYTHONPATH=.
+```
 
 ### 2. 安装服务模块
-PaddleOCR提供3种服务模块，根据需要安装所需模块。如： 
+PaddleOCR提供3种服务模块，根据需要安装所需模块。
 
-安装检测服务模块：  
-```hub install deploy/hubserving/ocr_det/```  
+* 在Linux环境下，安装示例如下：
+```shell
+# 安装检测服务模块：  
+hub install deploy/hubserving/ocr_det/
 
-或，安装识别服务模块：    
-```hub install deploy/hubserving/ocr_rec/```  
+# 或，安装识别服务模块：  
+hub install deploy/hubserving/ocr_rec/
 
-或，安装检测+识别串联服务模块：  
-```hub install deploy/hubserving/ocr_system/```  
+# 或，安装检测+识别串联服务模块：  
+hub install deploy/hubserving/ocr_system/
+```
+
+* 在Windows环境下(文件夹的分隔符为`\`)，安装示例如下：
+```shell
+# 安装检测服务模块：  
+hub install deploy\hubserving\ocr_det\
+
+# 或，安装识别服务模块：  
+hub install deploy\hubserving\ocr_rec\
+
+# 或，安装检测+识别串联服务模块：
+hub install deploy\hubserving\ocr_system\
+```
 
 ### 3. 启动服务
 #### 方式1. 命令行命令启动（仅支持CPU）
@@ -71,7 +88,7 @@ $ hub serving start --modules [Module1==Version1, Module2==Version2, ...] \
 **启动命令：**  
 ```hub serving start -c config.json```  
 
-其中，`config.json`格式如下： 
+其中，`config.json`格式如下：
 ```python
 {
     "modules_info": {
@@ -124,7 +141,7 @@ hub serving start -c deploy/hubserving/ocr_system/config.json
 ## 返回结果格式说明
 返回结果为列表（list），列表中的每一项为词典（dict），词典一共可能包含3种字段，信息如下：
 
-|字段名称|数据类型|意义| 
+|字段名称|数据类型|意义|
 |-|-|-|
 |text|str|文本内容|
 |confidence|float| 文本识别置信度|
@@ -134,9 +151,9 @@ hub serving start -c deploy/hubserving/ocr_system/config.json
 
 |字段名/模块名|ocr_det|ocr_rec|ocr_system|
 |-|-|-|-|  
-|text||✔|✔| 
-|confidence||✔|✔| 
-|text_region|✔||✔| 
+|text||✔|✔|
+|confidence||✔|✔|
+|text_region|✔||✔|
 
 **说明：** 如果需要增加、删除、修改返回字段，可在相应模块的`module.py`文件中进行修改，完整流程参考下一节自定义修改服务模块。
 
@@ -157,4 +174,3 @@ hub serving start -c deploy/hubserving/ocr_system/config.json
 
 - 5、重新启动服务  
 ```hub serving start -m ocr_system```  
-

doc/doc_en/serving_en.md

@@ -29,25 +29,38 @@ The following steps take the 2-stage series service as an example. If only the d
 # Install paddlehub  
 pip3 install paddlehub --upgrade -i https://pypi.tuna.tsinghua.edu.cn/simple
 
-# Set environment variables  
+# Set environment variables on Linux
 export PYTHONPATH=.
-```   
+# Set environment variables on Windows
+SET PYTHONPATH=.
+```
 
 ### 2. Install Service Module
-PaddleOCR provides 3 kinds of service modules, install the required modules according to your needs. Such as:  
+PaddleOCR provides 3 kinds of service modules, install the required modules according to your needs.
 
-Install the detection service module:  
+* On Linux platform, the examples are as follows.
 ```shell
+# Install the detection service module:
 hub install deploy/hubserving/ocr_det/
-```  
-Or, install the recognition service module:  
-```shell
+
+# Or, install the recognition service module:
 hub install deploy/hubserving/ocr_rec/
-```  
-Or, install the 2-stage series service module:  
-```shell
+
+# Or, install the 2-stage series service module:
 hub install deploy/hubserving/ocr_system/
-```  
+```
+
+* On Windows platform, the examples are as follows.
+```shell
+# Install the detection service module:
+hub install deploy\hubserving\ocr_det\
+
+# Or, install the recognition service module:
+hub install deploy\hubserving\ocr_rec\
+
+# Or, install the 2-stage series service module:
+hub install deploy\hubserving\ocr_system\
+```
 
 ### 3. Start service
 #### Way 1. Start with command line parameters (CPU only)
@@ -119,7 +132,7 @@ python tools/test_hubserving.py server_url image_path
 ```  
 
 Two parameters need to be passed to the script:
-- **server_url**：service address，format of which is 
+- **server_url**：service address，format of which is
 `http://[ip_address]:[port]/predict/[module_name]`  
 For example, if the detection, recognition and 2-stage serial services are started with provided configuration files, the respective `server_url` would be:  
 `http://127.0.0.1:8866/predict/ocr_det`  
@@ -135,7 +148,7 @@ python tools/test_hubserving.py http://127.0.0.1:8868/predict/ocr_system ./doc/i
 ## Returned result format
 The returned result is a list. Each item in the list is a dict. The dict may contain three fields. The information is as follows:
 
-|field name|data type|description| 
+|field name|data type|description|
 |-|-|-|
 |text|str|text content|
 |confidence|float|text recognition confidence|
@@ -145,9 +158,9 @@ The fields returned by different modules are different. For example, the results
 
 |field name/module name|ocr_det|ocr_rec|ocr_system|
 |-|-|-|-|  
-|text||✔|✔| 
-|confidence||✔|✔| 
-|text_region|✔||✔| 
+|text||✔|✔|
+|confidence||✔|✔|
+|text_region|✔||✔|
 
 **Note：** If you need to add, delete or modify the returned fields, you can modify the file `module.py` of the corresponding module. For the complete process, refer to the user-defined modification service module in the next section.
 

tools/infer/predict_det.py

@@ -135,6 +135,9 @@ def __call__(self, img):
     text_detector = TextDetector(args)
     count = 0
     total_time = 0
+    draw_img_save = "./inference_results"
+    if not os.path.exists(draw_img_save):
+        os.makedirs(draw_img_save)
     for image_file in image_file_list:
         img = cv2.imread(image_file)
         if img is None:
@@ -147,6 +150,7 @@ def __call__(self, img):
         print("Predict time of %s:" % image_file, elapse)
         src_im = utility.draw_text_det_res(dt_boxes, image_file)
         img_name_pure = image_file.split("/")[-1]
-        cv2.imwrite("./inference_results/det_res_%s" % img_name_pure, src_im)
+        cv2.imwrite(
+            os.path.join(draw_img_save, "det_res_%s" % img_name_pure), src_im)
     if count > 1:
         print("Avg Time:", total_time / (count - 1))