Merge pull request #471 from LDOUBLEV/fixocr

fix typo and opt doc

doc/doc_ch/detection.md

@@ -26,7 +26,7 @@ wget -P ./train_data/  https://paddleocr.bj.bcebos.com/dataset/test_icdar2015_la
 提供的标注文件格式为，其中中间是"\t"分隔：
 ```
 " 图像文件名                    json.dumps编码的图像标注信息"
-ch4_test_images/img_61.jpg    [{"transcription": "MASA", "points": [[310, 104], [416, 141], [418, 216], [312, 179]], ...}]
+ch4_test_images/img_61.jpg    [{"transcription": "MASA", "points": [[310, 104], [416, 141], [418, 216], [312, 179]]}, {...}]
 ```
 json.dumps编码前的图像标注信息是包含多个字典的list，字典中的 `points` 表示文本框的四个点的坐标(x, y)，从左上角的点开始顺时针排列。
 `transcription` 表示当前文本框的文字，在文本检测任务中并不需要这个信息。

doc/doc_ch/installation.md

@@ -21,10 +21,10 @@ cd /home/Projects
 如果您希望在CPU环境下使用docker，使用docker而不是nvidia-docker创建docker
 sudo docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda9.0-cudnn7-dev /bin/bash
 
-如果您的机器安装的是CUDA9，请运行以下命令创建容器
+如果使用CUDA9，请运行以下命令创建容器
 sudo nvidia-docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda9.0-cudnn7-dev /bin/bash
 
-如果您的机器安装的是CUDA10，请运行以下命令创建容器
+如果使用CUDA10，请运行以下命令创建容器
 sudo nvidia-docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda10.0-cudnn7-dev /bin/bash
 
 您也可以访问[DockerHub](https://hub.docker.com/r/paddlepaddle/paddle/tags/)获取与您机器适配的镜像。

doc/doc_en/detection_en.md

@@ -25,7 +25,7 @@ After decompressing the data set and downloading the annotation file, PaddleOCR/
 The provided annotation file format is as follow, seperated by "\t":
 ```
 " Image file name             Image annotation information encoded by json.dumps"
-ch4_test_images/img_61.jpg    [{"transcription": "MASA", "points": [[310, 104], [416, 141], [418, 216], [312, 179]], ...}]
+ch4_test_images/img_61.jpg    [{"transcription": "MASA", "points": [[310, 104], [416, 141], [418, 216], [312, 179]]}, {...}]
 ```
 The image annotation after json.dumps() encoding is a list containing multiple dictionaries. The `points` in the dictionary represent the coordinates (x, y) of the four points of the text box, arranged clockwise from the point at the upper left corner.
 

doc/doc_en/installation_en.md

@@ -18,14 +18,14 @@ cd /home/Projects
 # You need to create a docker container for the first run, and do not need to run the current command when you run it again
 # Create a docker container named ppocr and map the current directory to the /paddle directory of the container
 
-#If you want to use docker in a CPU environment, use docker instead of nvidia-docker to create docker
+#If using CPU, use docker instead of nvidia-docker to create docker
 sudo docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda9.0-cudnn7-dev /bin/bash
 ```
-If you have cuda9 installed on your machine, please run the following command to create a container:
+If using CUDA9, please run the following command to create a container:
 ```
 sudo nvidia-docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda9.0-cudnn7-dev /bin/bash
 ```
-If you have cuda10 installed on your machine, please run the following command to create a container:
+If using CUDA10, please run the following command to create a container:
 ```
 sudo nvidia-docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda10.0-cudnn7-dev /bin/bash
 ```

tools/infer/predict_rec.py

@@ -122,9 +122,9 @@ class TextRecognizer(object):
                     ind = np.argmax(probs, axis=1)
                     blank = probs.shape[1]
                     valid_ind = np.where(ind != (blank - 1))[0]
-                    score = np.mean(probs[valid_ind, ind[valid_ind]])
                     if len(valid_ind) == 0:
                         continue
+                    score = np.mean(probs[valid_ind, ind[valid_ind]])
                     # rec_res.append([preds_text, score])
                     rec_res[indices[beg_img_no + rno]] = [preds_text, score]
             else:

tools/infer/utility.py

@@ -95,7 +95,7 @@ def create_predictor(args, mode):
         config.set_cpu_math_library_num_threads(6)
         if args.enable_mkldnn:
             config.enable_mkldnn()
-            
+
     #config.enable_memory_optim()
     config.disable_glog_info()
 
@@ -169,7 +169,7 @@ def draw_ocr_box_txt(image, boxes, txts):
     img_right = Image.new('RGB', (w, h), (255, 255, 255))
 
     import random
-    # 每次使用相同的随机种子 ，可以保证两次颜色一致
+
     random.seed(0)
     draw_left = ImageDraw.Draw(img_left)
     draw_right = ImageDraw.Draw(img_right)