gantt

requirements.txt

@@ -36,7 +36,7 @@ tqdm == 4.67.0; python_version>="3.9"
 xgboost == 0.90
 yellowbrick==0.9.1; python_version=="3.6"
 yellowbrick==1.5.0; python_version>="3.9"
-kaleido == 0.1.0.post1; python_version=="3.6"
+kaleido == 0.1.0; python_version=="3.6"
 kaleido; python_version>="3.9"
 psutil == 5.9.8; python_version=="3.6"
 psutil; python_version>="3.9"

simba/mixins/image_mixin.py

@@ -948,9 +948,8 @@ def img_sliding_mse(imgs: np.ndarray,
         return results.astype(int64)
 
     @staticmethod
-    def _read_img_batch_from_video_helper(
-        frm_idx: np.ndarray, video_path: Union[str, os.PathLike], verbose: bool,
-    ):
+    def _read_img_batch_from_video_helper(frm_idx: np.ndarray, video_path: Union[str, os.PathLike], greyscale: bool, verbose: bool):
+
         """Multiprocess helper used by read_img_batch_from_video to read in images from video file."""
         start_idx, end_frm, current_frm = frm_idx[0], frm_idx[-1] + 1, frm_idx[0]
         results = {}
@@ -959,18 +958,20 @@ def _read_img_batch_from_video_helper(
         while current_frm < end_frm:
             if verbose:
                 print(f'Reading frame idx {current_frm}...')
-            results[current_frm] = cap.read()[1]
+            img = cap.read()[1]
+            if greyscale:
+                img = ImageMixin.img_to_greyscale(img=img)
+            results[current_frm] = img
             current_frm += 1
         return results
 
     @staticmethod
-    def read_img_batch_from_video(
-        video_path: Union[str, os.PathLike],
-        start_frm: int,
-        end_frm: int,
-        core_cnt: Optional[int] = -1,
-        verbose: Optional[bool] = False,
-    ) -> Dict[int, np.ndarray]:
+    def read_img_batch_from_video(video_path: Union[str, os.PathLike],
+                                  start_frm: int,
+                                  end_frm: int,
+                                  greyscale: Optional[bool] = False,
+                                  core_cnt: Optional[int] = -1,
+                                  verbose: Optional[bool] = False) -> Dict[int, np.ndarray]:
         """
         Read a batch of frames from a video file. This method reads frames from a specified range of frames within a video file using multiprocessing.
 
@@ -981,7 +982,7 @@ def read_img_batch_from_video(
         :param int start_frm: Starting frame index.
         :param int end_frm: Ending frame index.
         :param Optionalint] core_cnt: Number of CPU cores to use for parallel processing. Default is -1, indicating using all available cores.
-        :param Optional[bool] greyscale: If True, reads the images as greyscale. If False, then as original color scale. Default: True.
+        :param Optional[bool] greyscale: If True, reads the images as greyscale. If False, then as original color scale. Default: False.
         :returns: A dictionary containing frame indices as keys and corresponding frame arrays as values.
         :rtype: Dict[int, np.ndarray]
 
@@ -990,34 +991,18 @@ def read_img_batch_from_video(
         """
         check_file_exist_and_readable(file_path=video_path)
         video_meta_data = get_video_meta_data(video_path=video_path)
-        check_int(
-            name=ImageMixin().__class__.__name__,
-            value=start_frm,
-            min_value=0,
-            max_value=video_meta_data["frame_count"],
-        )
-        check_int(
-            name=ImageMixin().__class__.__name__,
-            value=end_frm,
-            min_value=0,
-            max_value=video_meta_data["frame_count"],
-        )
+        check_int(name=ImageMixin().__class__.__name__,value=start_frm, min_value=0,max_value=video_meta_data["frame_count"])
+        check_int(name=ImageMixin().__class__.__name__, value=end_frm, min_value=start_frm+1, max_value=video_meta_data["frame_count"])
         check_int(name=ImageMixin().__class__.__name__, value=core_cnt, min_value=-1)
+        check_valid_boolean(value=[greyscale], source=f'{ImageMixin().__class__.__name__} greyscale')
         if core_cnt < 0:
             core_cnt = multiprocessing.cpu_count()
         if end_frm <= start_frm:
-            FrameRangeError(
-                msg=f"Start frame ({start_frm}) has to be before end frame ({end_frm})",
-                source=ImageMixin().__class__.__name__,
-            )
+            FrameRangeError(msg=f"Start frame ({start_frm}) has to be before end frame ({end_frm})", source=ImageMixin().__class__.__name__)
         frm_lst = np.array_split(np.arange(start_frm, end_frm + 1), core_cnt)
         results = {}
-        with multiprocessing.Pool(
-            core_cnt, maxtasksperchild=Defaults.LARGE_MAX_TASK_PER_CHILD.value
-        ) as pool:
-            constants = functools.partial(
-                ImageMixin()._read_img_batch_from_video_helper, video_path=video_path, verbose=verbose
-            )
+        with multiprocessing.Pool(core_cnt, maxtasksperchild=Defaults.LARGE_MAX_TASK_PER_CHILD.value) as pool:
+            constants = functools.partial(ImageMixin()._read_img_batch_from_video_helper, video_path=video_path, greyscale=greyscale, verbose=verbose)
             for cnt, result in enumerate(pool.imap(constants, frm_lst, chunksize=1)):
                 results.update(result)
 

simba/utils/enums.py

@@ -129,7 +129,7 @@ class Formats(Enum):
     MP4_CODEC = "mp4v"
     AVI_CODEC = "XVID"
     BATCH_CODEC = "libx264"
-    NUMERIC_DTYPES = (np.float32, np.float64, np.int64, np.int32, np.int8, int, float)
+    NUMERIC_DTYPES = (np.float32, np.float64, np.int64, np.int32, np.int8, np.uint8, int, float)
     LABELFRAME_HEADER_FORMAT = ("Helvetica", 12, "bold")
     LABELFRAME_HEADER_CLICKABLE_FORMAT = ("Helvetica", 12, "bold", "underline")
     LABELFRAME_HEADER_CLICKABLE_COLOR = f"#{5:02x}{99:02x}{193:02x}"