未验证 提交 ad8b450a 编写于 作者: D Double_V 提交者: GitHub

Merge pull request #7441 from vivien8261/dygraph

update bytes support
......@@ -414,6 +414,33 @@ def get_model_config(type, version, model_type, lang):
return model_urls[version][model_type][lang]
def img_decode(content: bytes):
np_arr = np.frombuffer(content, dtype=np.uint8)
return cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
def check_img(img):
if isinstance(img, bytes):
img = img_decode(img)
if isinstance(img, str):
# download net image
if is_link(img):
download_with_progressbar(img, 'tmp.jpg')
img = 'tmp.jpg'
image_file = img
img, flag, _ = check_and_read(image_file)
if not flag:
with open(image_file, 'rb') as f:
img = img_decode(f.read())
if img is None:
logger.error("error in loading image:{}".format(image_file))
return None
if isinstance(img, np.ndarray) and len(img.shape) == 2:
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
return img
class PaddleOCR(predict_system.TextSystem):
def __init__(self, **kwargs):
"""
......@@ -482,7 +509,7 @@ class PaddleOCR(predict_system.TextSystem):
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))
assert isinstance(img, (np.ndarray, list, str, bytes))
if isinstance(img, list) and det == True:
logger.error('When input a list of images, det must be false')
exit(0)
......@@ -491,22 +518,8 @@ class PaddleOCR(predict_system.TextSystem):
'Since the angle classifier is not initialized, the angle classifier will not be uesd during the forward process'
)
if isinstance(img, str):
# download net image
if img.startswith('http'):
download_with_progressbar(img, 'tmp.jpg')
img = 'tmp.jpg'
image_file = img
img, flag, _ = check_and_read(image_file)
if not flag:
with open(image_file, 'rb') as f:
np_arr = np.frombuffer(f.read(), dtype=np.uint8)
img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
if img is None:
logger.error("error in loading image:{}".format(image_file))
return None
if isinstance(img, np.ndarray) and len(img.shape) == 2:
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
img = check_img(img)
if det and rec:
dt_boxes, rec_res, _ = self.__call__(img, cls)
return [[box.tolist(), res] for box, res in zip(dt_boxes, rec_res)]
......@@ -585,23 +598,7 @@ class PPStructure(StructureSystem):
super().__init__(params)
def __call__(self, img, return_ocr_result_in_table=False, img_idx=0):
if isinstance(img, str):
# download net image
if img.startswith('http'):
download_with_progressbar(img, 'tmp.jpg')
img = 'tmp.jpg'
image_file = img
img, flag, _ = check_and_read(image_file)
if not flag:
with open(image_file, 'rb') as f:
np_arr = np.frombuffer(f.read(), dtype=np.uint8)
img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
if img is None:
logger.error("error in loading image:{}".format(image_file))
return None
if isinstance(img, np.ndarray) and len(img.shape) == 2:
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
img = check_img(img)
res, _ = super().__call__(
img, return_ocr_result_in_table, img_idx=img_idx)
return res
......@@ -644,7 +641,7 @@ def main():
if not flag_pdf:
if img is None:
logger.error("error in loading image:{}".format(image_file))
logger.error("error in loading image:{}".format(img_path))
continue
img_paths = [[img_path, img]]
else:
......
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