mirrors
/
PaddleOCR
mirror of https://github.com/PaddlePaddle/PaddleOCR.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Don't break overall processing on a bad image (#10216)

pull/10217/head
UserUnknownFactor 2023-07-19 10:46:29 +03:00 committed by GitHub
parent fac03876f3
commit 1dad0a980f
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 28 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

18
paddleocr.py
View File

@ -512,12 +512,12 @@ class PaddleOCR(predict_system.TextSystem):
def ocr(self, img, det=True, rec=True, cls=True):
"""
ocr with paddleocr
OCR with PaddleOCR
args：
img: img for ocr, support ndarray, img_path and list or ndarray
det: use text detection or not. If false, only rec will be exec. Default is True
rec: use text recognition or not. If false, only det will be exec. Default is True
cls: use angle classifier or not. Default is True. If true, the text with rotation of 180 degrees can be recognized. If no text is rotated by 180 degrees, use cls=False to get better performance. Text with rotation of 90 or 270 degrees can be recognized even if cls=False.
img: img for OCR, support ndarray, img_path and list or ndarray
det: use text detection or not. If False, only rec will be exec. Default is True
rec: use text recognition or not. If False, only det will be exec. Default is True
cls: use angle classifier or not. Default is True. If True, the text with rotation of 180 degrees can be recognized. If no text is rotated by 180 degrees, use cls=False to get better performance. Text with rotation of 90 or 270 degrees can be recognized even if cls=False.
"""
assert isinstance(img, (np.ndarray, list, str, bytes))
if isinstance(img, list) and det == True:
@ -525,7 +525,7 @@ class PaddleOCR(predict_system.TextSystem):
exit(0)
if cls == True and self.use_angle_cls == False:
logger.warning(
'Since the angle classifier is not initialized, the angle classifier will not be uesd during the forward process'
'Since the angle classifier is not initialized, it will not be used during the forward process'
)
img = check_img(img)
@ -541,6 +541,9 @@ class PaddleOCR(predict_system.TextSystem):
ocr_res = []
for idx, img in enumerate(imgs):
dt_boxes, rec_res, _ = self.__call__(img, cls)
if not dt_boxes and not rec_res:
ocr_res.append(None)
continue
tmp_res = [[box.tolist(), res]
for box, res in zip(dt_boxes, rec_res)]
ocr_res.append(tmp_res)
@ -549,6 +552,9 @@ class PaddleOCR(predict_system.TextSystem):
ocr_res = []
for idx, img in enumerate(imgs):
dt_boxes, elapse = self.text_detector(img)
if not dt_boxes:
ocr_res.append(None)
continue
tmp_res = [box.tolist() for box in dt_boxes]
ocr_res.append(tmp_res)
return ocr_res

22
tools/infer/predict_system.py
View File

@ -65,15 +65,25 @@ class TextSystem(object):
self.crop_image_res_index += bbox_num
def __call__(self, img, cls=True):
time_dict = {'det': 0, 'rec': 0, 'csl': 0, 'all': 0}
time_dict = {'det': 0, 'rec': 0, 'cls': 0, 'all': 0}
if img is None:
logger.debug("no valid image provided")
return None, None, time_dict
start = time.time()
ori_im = img.copy()
dt_boxes, elapse = self.text_detector(img)
time_dict['det'] = elapse
logger.debug("dt_boxes num : {}, elapse : {}".format(
len(dt_boxes), elapse))
if dt_boxes is None:
return None, None
logger.debug("no dt_boxes found, elapsed : {}".format(elapse))
end = time.time()
time_dict['all'] = end - start
return None, None, time_dict
else:
logger.debug("dt_boxes num : {}, elapsed : {}".format(
len(dt_boxes), elapse))
img_crop_list = []
dt_boxes = sorted_boxes(dt_boxes)
@ -89,12 +99,12 @@ class TextSystem(object):
img_crop_list, angle_list, elapse = self.text_classifier(
img_crop_list)
time_dict['cls'] = elapse
logger.debug("cls num : {}, elapse : {}".format(
logger.debug("cls num : {}, elapsed : {}".format(
len(img_crop_list), elapse))
rec_res, elapse = self.text_recognizer(img_crop_list)
time_dict['rec'] = elapse
logger.debug("rec_res num : {}, elapse : {}".format(
logger.debug("rec_res num : {}, elapsed : {}".format(
len(rec_res), elapse))
if self.args.save_crop_res:
self.draw_crop_rec_res(self.args.crop_res_save_dir, img_crop_list,