fix: replace cv2.imread with toolbox.imread

cv2.imread will not raise error, even if the image is not existed

stagesepx/classifier/base.py

@@ -137,7 +137,7 @@ def read(self, *args, **kwargs):
 
     @staticmethod
     def read_from_path(data: typing.List[pathlib.Path], *_, **__):
-        return (cv2.imread(each.as_posix()) for each in data)
+        return (toolbox.imread(each.as_posix()) for each in data)
 
     def read_from_list(self, data: typing.List[int], video_cap: cv2.VideoCapture = None, *_, **__):
         cur_frame_id = toolbox.get_current_frame_id(video_cap)

stagesepx/classifier/svm.py

@@ -125,7 +125,7 @@ def predict(self, pic_path: str) -> str:
         :param pic_path:
         :return:
         """
-        pic_object = cv2.imread(pic_path)
+        pic_object = toolbox.imread(pic_path)
         return self.predict_with_object(pic_object)
 
     def predict_with_object(self, pic_object: np.ndarray) -> str:

stagesepx/cutter/cut_range.py

@@ -80,7 +80,7 @@ def contain_image(self,
         if image_path:
             logger.debug(f'found image path, use it first: {image_path}')
             assert os.path.isfile(image_path), f'image {image_path} not existed'
-            image_object = cv2.imread(image_path)
+            image_object = toolbox.imread(image_path)
         image_object = toolbox.turn_grey(image_object)
 
         # TODO use client or itself..?

stagesepx/toolbox.py

@@ -4,6 +4,7 @@
 import random
 import typing
 import math
+import os
 import numpy as np
 from loguru import logger
 from functools import wraps
@@ -60,6 +61,12 @@ def get_current_frame_time(video_cap: cv2.VideoCapture) -> float:
     return video_cap.get(cv2.CAP_PROP_POS_MSEC) / 1000
 
 
+def imread(img_path: str, *_, **__) -> np.ndarray:
+    """ wrapper of cv2.imread """
+    assert os.path.isfile(img_path), f'file {img_path} is not existed'
+    return cv2.imread(img_path, *_, **__)
+
+
 def get_frame_time(video_cap: cv2.VideoCapture, frame_id: int, recover: bool = None) -> float:
     cur = get_current_frame_id(video_cap)
     video_jump(video_cap, frame_id)
@@ -238,9 +245,3 @@ def _wrapper(*args, **kwargs):
         return func(*args, **kwargs)
 
     return _wrapper
-
-
-if __name__ == '__main__':
-    t = cv2.imread('../1.png', cv2.IMREAD_GRAYSCALE)
-    t = sharpen_frame(t)
-    cv2.imwrite('a.png', t)