def _split_normal_img_by_size(self,
path: str,
row_len,
column_len: int,
sub_path_func: typing.Callable[[str, int],
str],
replace_exist=True):
"""图片分割"""
img = cvutil.load_img(path)
total_height, total_width = img.shape[:2]
width, height = total_width // column_len, total_height // row_len
num = 1
station_str = Path(path).stem.split('_')[0]
for i in range(0, row_len):
left_top_height = i * height
right_bottom_height = (i + 1) * height
for j in range(0, column_len):
sub_path = sub_path_func(path=path,
num=num * self.thumbnailDuration)
if Path(sub_path).exists() and replace_exist:
continue
left_top_width = j * width
right_bottom_width = (j + 1) * width
roi = img[left_top_height:right_bottom_height,
left_top_width:right_bottom_width]
roi = cvutil.resize(roi, self.resize_width, self.resize_height)
cvutil.save_img(sub_path, roi)
if os.path.getsize(sub_path) < 1024:
self.log.info(
f'[{self.user_id}:{station_str}] invalid img size DEL {sub_path}'
)
os.remove(sub_path)
num += 1
return width, height
def test_shape():
path = 'img/0:0:3_0.jpg'
img = cvutil.load_img(path)
img = cvutil.gray(img)
img = img.flatten() / 255
print(img.shape)
p = Path(path)
print(p.stem.split('_')[-1])
print()
def cv_load(path: str):
img = cvutil.load_img(path)
total_height, total_width = img.shape[:2]
return img, total_width, total_height
def _prepare_img_by_path(path: str) -> np.array:
img = cvutil.load_img(path)
img = cvutil.gray(img)
# flatten 转为一维
img = img.flatten() / 255
return img