def _find_voids(
clip: VideoClip, diff_threshold: float, repetition_threshold: int
) -> List[Tuple[float, float]]:
cuts: List[Tuple[float, float]] = []
last_used_frame = None
last_used_frame_t = 0
num_similar = 0
with ui.ProgressBar(f"{clip.filename} - Processing frames", 1) as progress:
for frame_t, frame in clip.iter_frames(with_times=True, logger=progress):
if last_used_frame is None:
last_used_frame = frame
last_used_frame_t = frame_t
continue
diff = np.mean((frame - last_used_frame) ** 2)
if diff < diff_threshold:
# there are no signficant differences between this frame and the
# last used frame
num_similar += (
1 # Count the number of frames in a row which are similar
)
else:
# there was a significant difference between the frames
if num_similar > repetition_threshold:
# there were enough differences in a row
cuts.append((last_used_frame_t, frame_t))
# take note of this frame, and use it as reference for comparison
last_used_frame = frame
last_used_frame_t = frame_t
num_similar = 0
return cuts
