修改完成:划分det与rec数据集脚本，以及对应的中英文文档指令及其数据集存放树状结构。已提交过release2.4分支

PPOCRLabel/README.md

@@ -198,21 +198,31 @@ For some data that are difficult to recognize, the recognition results will not
 
 - Enter the following command in the terminal to execute the dataset division script:
 
-  ```
+    ```
   cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
-  python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --labelRootPath ../train_data/label --detRootPath ../train_data/det --recRootPath ../train_data/rec
+  python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ../train_data 
   ```
 
   Parameter Description:
 
   - `trainValTestRatio` is the division ratio of the number of images in the training set, validation set, and test set, set according to your actual situation, the default is `6:2:2`
 
-  - `labelRootPath` is the storage path of the dataset labeled by PPOCRLabel, the default is `../train_data/label`
-
-  - `detRootPath` is the path where the text detection dataset is divided according to the dataset marked by PPOCRLabel. The default is `../train_data/det`
-
-  - `recRootPath` is the path where the character recognition dataset is divided according to the dataset marked by PPOCRLabel. The default is `../train_data/rec`
-
+  - `datasetRootPath` is the storage path of the complete dataset labeled by PPOCRLabel. The default path is `PaddleOCR/train_data` .
+  ```
+  |-train_data
+    |-crop_img
+      |- word_001_crop_0.png
+      |- word_002_crop_0.jpg
+      |- word_003_crop_0.jpg
+      | ...
+    | Label.txt
+    | rec_gt.txt
+    |- word_001.png
+    |- word_002.jpg
+    |- word_003.jpg
+    | ...
+  ```
+  
 ### 3.6 Error message
 
 - If paddleocr is installed with whl, it has a higher priority than calling PaddleOCR class with paddleocr.py, which may cause an exception if whl package is not updated.

PPOCRLabel/README_ch.md

@@ -185,19 +185,29 @@ PPOCRLabel支持三种导出方式：
 
 ```
 cd ./PPOCRLabel # 将目录切换到PPOCRLabel文件夹下
-python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --labelRootPath ../train_data/label --detRootPath ../train_data/det --recRootPath ../train_data/rec
+python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ../train_data 
 ```
 
 参数说明：
 
 - `trainValTestRatio` 是训练集、验证集、测试集的图像数量划分比例，根据实际情况设定，默认是`6:2:2`
 
-- `labelRootPath` 是PPOCRLabel标注的数据集存放路径，默认是`../train_data/label`
-
-- `detRootPath` 是根据PPOCRLabel标注的数据集划分后的文本检测数据集存放的路径，默认是`../train_data/det `
-
-- `recRootPath` 是根据PPOCRLabel标注的数据集划分后的字符识别数据集存放的路径，默认是`../train_data/rec`
-
+- `datasetRootPath` 是PPOCRLabel标注的完整数据集存放路径。默认路径是 `PaddleOCR/train_data` 分割数据集前应有如下结构：
+  ```
+  |-train_data
+    |-crop_img
+      |- word_001_crop_0.png
+      |- word_002_crop_0.jpg
+      |- word_003_crop_0.jpg
+      | ...
+    | Label.txt
+    | rec_gt.txt
+    |- word_001.png
+    |- word_002.jpg
+    |- word_003.jpg
+    | ...
+  ```
+  
 ### 3.6 错误提示
 
 - 如果同时使用whl包安装了paddleocr，其优先级大于通过paddleocr.py调用PaddleOCR类，whl包未更新时会导致程序异常。

PPOCRLabel/gen_ocr_train_val_test.py

@@ -17,15 +17,14 @@ def isCreateOrDeleteFolder(path, flag):
     return flagAbsPath
 
 
-def splitTrainVal(root, dir, absTrainRootPath, absValRootPath, absTestRootPath, trainTxt, valTxt, testTxt, flag):
+def splitTrainVal(root, absTrainRootPath, absValRootPath, absTestRootPath, trainTxt, valTxt, testTxt, flag):
     # 按照指定的比例划分训练集、验证集、测试集
-    labelPath = os.path.join(root, dir)
-    labelAbsPath = os.path.abspath(labelPath)
+    dataAbsPath = os.path.abspath(root)
 
     if flag == "det":
-        labelFilePath = os.path.join(labelAbsPath, args.detLabelFileName)
+        labelFilePath = os.path.join(dataAbsPath, args.detLabelFileName)
     elif flag == "rec":
-        labelFilePath = os.path.join(labelAbsPath, args.recLabelFileName)
+        labelFilePath = os.path.join(dataAbsPath, args.recLabelFileName)
 
     labelFileRead = open(labelFilePath, "r", encoding="UTF-8")
     labelFileContent = labelFileRead.readlines()
@@ -38,9 +37,9 @@ def splitTrainVal(root, dir, absTrainRootPath, absValRootPath, absTestRootPath,
         imageName = os.path.basename(imageRelativePath)
 
         if flag == "det":
-            imagePath = os.path.join(labelAbsPath, imageName)
+            imagePath = os.path.join(dataAbsPath, imageName)
         elif flag == "rec":
-            imagePath = os.path.join(labelAbsPath, "{}\\{}".format(args.recImageDirName, imageName))
+            imagePath = os.path.join(dataAbsPath, "{}\\{}".format(args.recImageDirName, imageName))
 
         # 按预设的比例划分训练集、验证集、测试集
         trainValTestRatio = args.trainValTestRatio.split(":")
@@ -90,15 +89,20 @@ def genDetRecTrainVal(args):
     recValTxt = open(os.path.join(args.recRootPath, "val.txt"), "a", encoding="UTF-8")
     recTestTxt = open(os.path.join(args.recRootPath, "test.txt"), "a", encoding="UTF-8")
 
-    for root, dirs, files in os.walk(args.labelRootPath):
+    splitTrainVal(args.datasetRootPath, detAbsTrainRootPath, detAbsValRootPath, detAbsTestRootPath, detTrainTxt, detValTxt,
+                  detTestTxt, "det")
+
+    for root, dirs, files in os.walk(args.datasetRootPath):
         for dir in dirs:
-            splitTrainVal(root, dir, detAbsTrainRootPath, detAbsValRootPath, detAbsTestRootPath, detTrainTxt, detValTxt,
-                          detTestTxt, "det")
-            splitTrainVal(root, dir, recAbsTrainRootPath, recAbsValRootPath, recAbsTestRootPath, recTrainTxt, recValTxt,
-                          recTestTxt, "rec")
+            if dir == 'crop_img':
+                splitTrainVal(root, recAbsTrainRootPath, recAbsValRootPath, recAbsTestRootPath, recTrainTxt, recValTxt,
+                              recTestTxt, "rec")
+            else:
+                continue
         break
 
 
+
 if __name__ == "__main__":
     # 功能描述：分别划分检测和识别的训练集、验证集、测试集
     # 说明：可以根据自己的路径和需求调整参数，图像数据往往多人合作分批标注，每一批图像数据放在一个文件夹内用PPOCRLabel进行标注，
@@ -110,9 +114,9 @@ if __name__ == "__main__":
         default="6:2:2",
         help="ratio of trainset:valset:testset")
     parser.add_argument(
-        "--labelRootPath",
+        "--datasetRootPath",
         type=str,
-        default="../train_data/label",
+        default="../train_data/",
         help="path to the dataset marked by ppocrlabel, E.g, dataset folder named 1,2,3..."
     )
     parser.add_argument(