Ethanfel/ComfyUI-Sharp-Selector
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Update parallel_loader.py

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Ethanfel
2026-01-19 13:24:52 +01:00
parent 6eccb258ee
commit 6d5c773bea
1 changed files with 7 additions and 8 deletions
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15
parallel_loader.py
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@@ -23,7 +23,6 @@ class ParallelSharpnessLoader:
},
}
# Added a 4th output: STRING (The status sentence)
RETURN_TYPES = ("IMAGE", "STRING", "INT", "STRING")
RETURN_NAMES = ("images", "scores_info", "batch_int", "batch_status")
FUNCTION = "load_video"
@@ -45,17 +44,17 @@ class ParallelSharpnessLoader:
current_skip = (batch_index * scan_limit) + manual_skip_start
range_end = current_skip + scan_limit
# Create the Status String
status_msg = f"Batch {batch_index}: Skipped {current_skip} frames. Scanning range {current_skip} -> {range_end}."
print(f"xx- Parallel Loader | {status_msg}")
cap = cv2.VideoCapture(video_path)
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
# --- STOP CONDITION 1: REACHED END OF VIDEO ---
# This stops the queue immediately if we try to read past the end.
if current_skip >= total_frames:
print("xx- End of video reached.")
empty_img = torch.zeros((1, 64, 64, 3))
return (empty_img, "End of Video", batch_index, "End of Video Reached")
cap.release()
raise ValueError(f"Processing Complete. Batch {batch_index} starts at frame {current_skip}, but video only has {total_frames} frames.")
# 3. Scanning (Pass 1)
if current_skip > 0:
@@ -93,8 +92,9 @@ class ParallelSharpnessLoader:
cap.release()
# 4. Selection
# --- STOP CONDITION 2: NO FRAMES FOUND ---
if not frame_scores:
return (torch.zeros((1, 64, 64, 3)), "No frames in batch", batch_index, status_msg + " (No frames found)")
raise ValueError(f"No frames found in batch {batch_index} (Range {current_skip}-{range_end}). The video might be corrupted or blank.")
frame_scores.sort(key=lambda x: x[1], reverse=True)
selected = []
@@ -123,7 +123,6 @@ class ParallelSharpnessLoader:
cap.release()
if not output_tensors:
return (torch.zeros((1, 64, 64, 3)), "Extraction Failed", batch_index, status_msg)
raise ValueError("Frames were selected but could not be loaded. This indicates a file read error.")
# Return all 4 outputs
return (torch.stack(output_tensors), ", ".join(info_log), batch_index, status_msg)