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南宁网站设计图,淘宝优秀软文范例100字,seo谷歌,wordpress安全部署PPOCRLabel 使用PPOCRLabel对ocr预标注结果进行纠正由于PaddleOCR代码库十分混乱,路径经常乱调pip和代码库的代码（pip库和源码冲突）,经常报错，因此paddleocr和ppocrlabel都是使用pip包;PPOCRLabel中使用了cv2进行图片数据的读取，…

PPOCRLabel

使用PPOCRLabel对ocr预标注结果进行纠正
由于PaddleOCR代码库十分混乱,路径经常乱调pip和代码库的代码（pip库和源码冲突）,经常报错，因此paddleocr和ppocrlabel都是使用pip包;
PPOCRLabel中使用了cv2进行图片数据的读取，然cv2对中文路径读取有问题，经常会导致一些图片数据无法进行正常数据，在次基础上，把读取图片由cv2改为pilow，可以规避很多读取错误；

安装

pip install PPOCRLabel==2.1.3

启动

PPOCRLabel --lang ch

修改记录

修改1：

报错：AttributeError: ‘NoneType’ object has no attribute ‘shape’

'NoneType' object has no attribute 'shape'
Traceback (most recent call last):File "D:\ProgramData\Anaconda3\envs\paddle\lib\site-packages\PPOCRLabel\libs\autoDialog.py", line 41, in runh, w, _ = cv2.imdecode(np.fromfile(Imgpath, dtype=np.uint8), 1).shape
AttributeError: 'NoneType' object has no attribute 'shape'

原因：cv2不支持读取带有中文字符路径文件

  h, w, _ = cv2.imdecode(np.fromfile(Imgpath, dtype=np.uint8), 1).shape

解决：使用PIL替换cv2, 将上述代码替换为

# 修改文件："D:\ProgramData\Anaconda3\envs\paddle\lib\site-packages\PPOCRLabel\libs\autoDialog.py", line 41
# 增加PIL读取图片函数
from PIL import Image
def load_image(image_path: str, return_chw: bool = True, size: tuple = None):image = Image.open(image_path).convert("RGB")if size is not None:image = image.resize(size)  # resize imageimage = np.asarray(image)image = image[:, :, ::-1]  # flip color channels from RGB to BGRw, h = image.shape[1], image.shape[0]  # update size after resizeif return_chw:image = image.transpose(2, 0, 1)return image, (w, h)# 替换上面代码
try:image_data, (w, h) = load_image(Imgpath, return_chw=False)
except Exception as e:print(f"load file {Imgpath} fail!")continue

修改2

报错：AttributeError: ‘NoneType’ object has no attribute ‘shape’

Traceback (most recent call last):File "D:\ProgramData\Anaconda3\envs\paddle\lib\site-packages\PPOCRLabel\PPOCRLabel.py", line 1889, in saveFileself._saveFile(imgidx, mode=mode)File "D:\ProgramData\Anaconda3\envs\paddle\lib\site-packages\PPOCRLabel\PPOCRLabel.py", line 1934, in _saveFileself.openNextImg()File "D:\ProgramData\Anaconda3\envs\paddle\lib\site-packages\PPOCRLabel\PPOCRLabel.py", line 1880, in openNextImgself.loadFile(filename)File "D:\ProgramData\Anaconda3\envs\paddle\lib\site-packages\PPOCRLabel\PPOCRLabel.py", line 1550, in loadFileheight, width, depth = cvimg.shape
AttributeError: 'NoneType' object has no attribute 'shape'

原因还是cv2不能读取中文路径文件
解决：

# 修改: File "D:\ProgramData\Anaconda3\envs\paddle\lib\site-packages\PPOCRLabel\PPOCRLabel.py", line 1550, in loadFile
# cvimg = cv2.imdecode(np.fromfile(unicodeFilePath, dtype=np.uint8), 1)
cvimg, _ = load_image(unicodeFilePath, return_chw=False)

修改3

报错:error: (-215:Assertion failed) _src.total() > 0 in function ‘cv::warpPerspective’
- 报错描述：在对PPOCRLABEL的框进行重新识别是，发生如下报错：
```
  Can not recognise the detection box in xxxx,png. Please change manually'unicodeFilePath is J:\data\mllm-data\xxxxxxxxx\wKh2CWERPJOAY2x-AAE62o598k0620.pngOpenCV(4.2.0) C:\projects\opencv-python\opencv\modules\imgproc\src\imgwarp.cpp:3143: error: (-215:Assertion failed) _src.total() > 0 in function 'cv::warpPerspective'
```
- 原因是我们的ocr预标注数据Label.txt是使用PIL读取图片数据，调用ppocr进行生产的（并不是在PPOCRLabel工具内部生产的）, 当我们修改数据框后, PPOCRLabel尝试再次使用cv2进行读取原图,此时由于cv2对路径较为敏感,经常会读取文件失败,才会出现如上情况
解决：
依旧是修改PPOCRLabel源码, 把cv2读取改为PIL读取,就不惯着cv2的臭毛病…

# 修改如下代码def reRecognition(self):#img = cv2.imdecode(np.fromfile(self.filePath,dtype=np.uint8),1)img, _ = load_image(self.filePath, return_chw=False)

修改4

运行PPOCRLabel源码（paddleocr使用pip安装）,报错： AttributeError: ‘Namespace’ object has no attribute ‘return_word_box’

    - File "G:\dongyongfei786\paddle\PaddleOCR\ppstructure\predict_system.py", line 82, in __init__self.return_word_box = args.return_word_box
AttributeError: 'Namespace' object has no attribute 'return_word_box'

原因:
- paddleocr使用pip安装的源码中（paddleocr=2.7.0.3）, D:\ProgramData\Anaconda3\Lib\site-packages\paddleocr\tools\infer\utility.py, 缺少

  # extended functionparser.add_argument("--return_word_box", type=str2bool, default=False, help='Whether return the bbox of each word (split by space) or chinese character. Only used in ppstructure for layout recovery')