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
Alchemist_W
parent
efc0908277
commit
f58d8d0372
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@ -200,18 +200,28 @@ For some data that are difficult to recognize, the recognition results will not
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```
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cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
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python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --labelRootPath ../train_data/label --detRootPath ../train_data/det --recRootPath ../train_data/rec
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python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ../train_data
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```
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Parameter Description:
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- `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`
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- `labelRootPath` is the storage path of the dataset labeled by PPOCRLabel, the default is `../train_data/label`
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- `detRootPath` is the path where the text detection dataset is divided according to the dataset marked by PPOCRLabel. The default is `../train_data/det`
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- `recRootPath` is the path where the character recognition dataset is divided according to the dataset marked by PPOCRLabel. The default is `../train_data/rec`
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- `datasetRootPath` is the storage path of the complete dataset labeled by PPOCRLabel. The default path is `PaddleOCR/train_data` .
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```
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|-train_data
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|-crop_img
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|- word_001_crop_0.png
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|- word_002_crop_0.jpg
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|- word_003_crop_0.jpg
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| ...
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| Label.txt
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| rec_gt.txt
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|- word_001.png
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|- word_002.jpg
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|- word_003.jpg
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| ...
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```
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### 3.6 Error message
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@ -185,18 +185,28 @@ PPOCRLabel支持三种导出方式：
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```
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cd ./PPOCRLabel # 将目录切换到PPOCRLabel文件夹下
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python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --labelRootPath ../train_data/label --detRootPath ../train_data/det --recRootPath ../train_data/rec
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python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ../train_data
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```
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参数说明：
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- `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`
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- `labelRootPath` 是PPOCRLabel标注的数据集存放路径，默认是`../train_data/label`
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- `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 `
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- `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`
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- `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：
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```
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|-train_data
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|-crop_img
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|- word_001_crop_0.png
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|- word_002_crop_0.jpg
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|- word_003_crop_0.jpg
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| ...
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| Label.txt
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| rec_gt.txt
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|- word_001.png
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|- word_002.jpg
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|- word_003.jpg
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| ...
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```
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### 3.6 错误提示
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@ -17,15 +17,14 @@ def isCreateOrDeleteFolder(path, flag):
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return flagAbsPath
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def splitTrainVal(root, dir, absTrainRootPath, absValRootPath, absTestRootPath, trainTxt, valTxt, testTxt, flag):
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def splitTrainVal(root, absTrainRootPath, absValRootPath, absTestRootPath, trainTxt, valTxt, testTxt, flag):
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# 按照指定的比例划分训练集、验证集、测试集
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labelPath = os.path.join(root, dir)
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labelAbsPath = os.path.abspath(labelPath)
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dataAbsPath = os.path.abspath(root)
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if flag == "det":
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labelFilePath = os.path.join(labelAbsPath, args.detLabelFileName)
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labelFilePath = os.path.join(dataAbsPath, args.detLabelFileName)
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elif flag == "rec":
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labelFilePath = os.path.join(labelAbsPath, args.recLabelFileName)
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labelFilePath = os.path.join(dataAbsPath, args.recLabelFileName)
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labelFileRead = open(labelFilePath, "r", encoding="UTF-8")
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labelFileContent = labelFileRead.readlines()
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@ -38,9 +37,9 @@ def splitTrainVal(root, dir, absTrainRootPath, absValRootPath, absTestRootPath,
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imageName = os.path.basename(imageRelativePath)
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if flag == "det":
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imagePath = os.path.join(labelAbsPath, imageName)
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imagePath = os.path.join(dataAbsPath, imageName)
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elif flag == "rec":
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imagePath = os.path.join(labelAbsPath, "{}\\{}".format(args.recImageDirName, imageName))
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imagePath = os.path.join(dataAbsPath, "{}\\{}".format(args.recImageDirName, imageName))
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# 按预设的比例划分训练集、验证集、测试集
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trainValTestRatio = args.trainValTestRatio.split(":")
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@ -90,15 +89,20 @@ def genDetRecTrainVal(args):
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recValTxt = open(os.path.join(args.recRootPath, "val.txt"), "a", encoding="UTF-8")
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recTestTxt = open(os.path.join(args.recRootPath, "test.txt"), "a", encoding="UTF-8")
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for root, dirs, files in os.walk(args.labelRootPath):
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for dir in dirs:
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splitTrainVal(root, dir, detAbsTrainRootPath, detAbsValRootPath, detAbsTestRootPath, detTrainTxt, detValTxt,
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splitTrainVal(args.datasetRootPath, detAbsTrainRootPath, detAbsValRootPath, detAbsTestRootPath, detTrainTxt, detValTxt,
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detTestTxt, "det")
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splitTrainVal(root, dir, recAbsTrainRootPath, recAbsValRootPath, recAbsTestRootPath, recTrainTxt, recValTxt,
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for root, dirs, files in os.walk(args.datasetRootPath):
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for dir in dirs:
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if dir == 'crop_img':
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splitTrainVal(root, recAbsTrainRootPath, recAbsValRootPath, recAbsTestRootPath, recTrainTxt, recValTxt,
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recTestTxt, "rec")
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else:
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continue
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break
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if __name__ == "__main__":
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# 功能描述：分别划分检测和识别的训练集、验证集、测试集
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# 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，
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@ -110,9 +114,9 @@ if __name__ == "__main__":
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default="6:2:2",
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help="ratio of trainset:valset:testset")
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parser.add_argument(
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"--labelRootPath",
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"--datasetRootPath",
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type=str,
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default="../train_data/label",
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default="../train_data/",
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help="path to the dataset marked by ppocrlabel, E.g, dataset folder named 1,2,3..."
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)
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parser.add_argument(
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