Merge remote-tracking branch 'origin/master'

sgoldenlab · Mar 7, 2024 · 07302b8 · 07302b8
2 parents f3e95b7 + e056fb1
commit 07302b8
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Showing 3 changed files with 60 additions and 15 deletions.
diff --git a/simba/mixins/geometry_mixin.py b/simba/mixins/geometry_mixin.py
@@ -2698,7 +2698,9 @@ def rank_shapes(
         return [shapes[idx] for idx in ranked]
 
     @staticmethod
-    def contours_to_geometries(contours: List[np.ndarray], force_rectangles: Optional[bool] = True) -> List[Polygon]:
+    def contours_to_geometries(
+        contours: List[np.ndarray], force_rectangles: Optional[bool] = True
+    ) -> List[Polygon]:
         """
         Convert a list of contours to a list of geometries.
 
@@ -2715,9 +2717,17 @@ def contours_to_geometries(contours: List[np.ndarray], force_rectangles: Optiona
         >>> GeometryMixin.contours_to_geometries(contours=contours)
         """
 
-        check_instance(source=GeometryMixin.contours_to_geometries.__name__, instance=contours, accepted_types=(list,))
-        for i in contours: check_instance(source=f'{GeometryMixin.contours_to_geometries.__name__} {i}', instance=i,
-                                          accepted_types=(np.ndarray,))
+        check_instance(
+            source=GeometryMixin.contours_to_geometries.__name__,
+            instance=contours,
+            accepted_types=(list,),
+        )
+        for i in contours:
+            check_instance(
+                source=f"{GeometryMixin.contours_to_geometries.__name__} {i}",
+                instance=i,
+                accepted_types=(np.ndarray,),
+            )
         results = []
         for contour in contours:
             if contour.ndim == 3:

diff --git a/simba/mixins/image_mixin.py b/simba/mixins/image_mixin.py
@@ -89,19 +89,40 @@ def brightness_intensity(
     @staticmethod
     def gaussian_blur(img: np.ndarray, kernel_size: Optional[Tuple] = (9, 9)):
         check_if_valid_img(data=img, source=ImageMixin.gaussian_blur.__name__)
-        check_instance(source=ImageMixin.gaussian_blur.__name__, instance=kernel_size, accepted_types=(tuple,))
-        check_valid_lst(data=list(kernel_size), source=ImageMixin.gaussian_blur.__name__, valid_dtypes=(int,), exact_len=2)
+        check_instance(
+            source=ImageMixin.gaussian_blur.__name__,
+            instance=kernel_size,
+            accepted_types=(tuple,),
+        )
+        check_valid_lst(
+            data=list(kernel_size),
+            source=ImageMixin.gaussian_blur.__name__,
+            valid_dtypes=(int,),
+            exact_len=2,
+        )
         return cv2.GaussianBlur(img, kernel_size, 0)
 
     @staticmethod
-    def erode(img: np.ndarray, kernel_size: Optional[Tuple] = (3, 3), iterations: Optional[int] = 3):
+    def erode(
+        img: np.ndarray,
+        kernel_size: Optional[Tuple] = (3, 3),
+        iterations: Optional[int] = 3,
+    ):
         check_if_valid_img(data=img, source=ImageMixin.gaussian_blur.__name__)
-        check_instance(source=ImageMixin.gaussian_blur.__name__, instance=kernel_size, accepted_types=(tuple,))
-        check_valid_lst(data=list(kernel_size), source=ImageMixin.gaussian_blur.__name__, valid_dtypes=(int,), exact_len=2)
+        check_instance(
+            source=ImageMixin.gaussian_blur.__name__,
+            instance=kernel_size,
+            accepted_types=(tuple,),
+        )
+        check_valid_lst(
+            data=list(kernel_size),
+            source=ImageMixin.gaussian_blur.__name__,
+            valid_dtypes=(int,),
+            exact_len=2,
+        )
         check_int(name=ImageMixin.erode.__name__, value=iterations, min_value=1)
         return cv2.erode(img, np.ones((3, 3), np.uint8), iterations=3)
 
-
     @staticmethod
     def get_histocomparison(
         img_1: np.ndarray,

diff --git a/simba/utils/read_write.py b/simba/utils/read_write.py
@@ -415,7 +415,9 @@ def read_config_file(config_path: Union[str, os.PathLike]) -> configparser.Confi
     return config
 
 
-def get_video_meta_data(video_path: Union[str, os.PathLike], fps_as_int: bool = True) -> dict:
+def get_video_meta_data(
+    video_path: Union[str, os.PathLike], fps_as_int: bool = True
+) -> dict:
     """
     Read video metadata (fps, resolution, frame cnt etc.) from video file (e.g., mp4).
 
@@ -648,7 +650,14 @@ def find_all_videos_in_directory(
     return video_lst
 
 
-def read_frm_of_video(video_path: Union[str, os.PathLike, cv2.VideoCapture], frame_index: int = 0, opacity: Optional[float] = None, size: Optional[Tuple[int, int]] = None, greyscale: Optional[bool] = False, clahe: Optional[bool] = False) -> np.ndarray:
+def read_frm_of_video(
+    video_path: Union[str, os.PathLike, cv2.VideoCapture],
+    frame_index: int = 0,
+    opacity: Optional[float] = None,
+    size: Optional[Tuple[int, int]] = None,
+    greyscale: Optional[bool] = False,
+    clahe: Optional[bool] = False,
+) -> np.ndarray:
     """
     Reads single image from video file.
 
@@ -710,14 +719,19 @@ def read_frm_of_video(video_path: Union[str, os.PathLike, cv2.VideoCapture], fra
         if size:
             img = cv2.resize(img, size, interpolation=cv2.INTER_LINEAR)
         if greyscale:
-            if len(img.shape) > 2: img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+            if len(img.shape) > 2:
+                img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
         if clahe:
-            if len(img.shape) > 2: img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+            if len(img.shape) > 2:
+                img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
             img = cv2.createCLAHE(clipLimit=2, tileGridSize=(16, 16)).apply(img)
     else:
-        NoDataFoundWarning(msg=f"Frame {frame_index} for video {video_path} could not be read.")
+        NoDataFoundWarning(
+            msg=f"Frame {frame_index} for video {video_path} could not be read."
+        )
     return img
 
+
 def find_video_of_file(
     video_dir: Union[str, os.PathLike], filename: str, raise_error: bool = False
 ) -> Union[str, os.PathLike]: