parralel #2
@@ -11,11 +11,13 @@ class ParallelSharpnessLoader:
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return {
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"required": {
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"video_path": ("STRING", {"default": "C:\\path\\to\\video.mp4"}),
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"scan_limit": ("INT", {"default": 1440, "min": 0, "step": 1, "label": "Max Frames to Scan (0=All)"}),
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# scan_limit: 0 means ALL frames. Max set high to allow large user inputs.
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"scan_limit": ("INT", {"default": 1440, "min": 0, "max": 10000000, "step": 1, "label": "Max Frames to Scan (0=All)"}),
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"frame_scan_step": ("INT", {"default": 5, "min": 1, "step": 1, "label": "Analyze Every Nth Frame"}),
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"return_count": ("INT", {"default": 4, "min": 1, "step": 1, "label": "Best Frames Count"}),
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"min_distance": ("INT", {"default": 24, "min": 0, "step": 1, "label": "Min Distance (Frames)"}),
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"skip_start": ("INT", {"default": 0, "min": 0, "step": 1}),
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"return_count": ("INT", {"default": 4, "min": 1, "max": 1024, "step": 1, "label": "Best Frames Count"}),
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"min_distance": ("INT", {"default": 24, "min": 0, "max": 10000, "step": 1, "label": "Min Distance (Frames)"}),
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# FIXED: Max limit increased to 10 million to prevent slider locking at 2048
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"skip_start": ("INT", {"default": 0, "min": 0, "max": 10000000, "step": 1}),
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},
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}
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@@ -24,7 +26,6 @@ class ParallelSharpnessLoader:
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FUNCTION = "load_video"
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CATEGORY = "BetaHelper/Video"
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# Worker function for threading
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def calculate_sharpness(self, frame_data):
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gray = cv2.cvtColor(frame_data, cv2.COLOR_BGR2GRAY)
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return cv2.Laplacian(gray, cv2.CV_64F).var()
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@@ -32,7 +33,6 @@ class ParallelSharpnessLoader:
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def load_video(self, video_path, scan_limit, frame_scan_step, return_count, min_distance, skip_start):
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# 1. Validation
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if not os.path.exists(video_path):
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# Clean string to remove quotes if user pasted them
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video_path = video_path.strip('"')
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if not os.path.exists(video_path):
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raise FileNotFoundError(f"Video not found: {video_path}")
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@@ -46,11 +46,11 @@ class ParallelSharpnessLoader:
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current_frame = skip_start
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scanned_count = 0
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# Set start position
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# Seek to start
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if skip_start > 0:
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cap.set(cv2.CAP_PROP_POS_FRAMES, skip_start)
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# Thread Pool for high-speed calculation
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# Thread Pool
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with concurrent.futures.ThreadPoolExecutor(max_workers=16) as executor:
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futures = []
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@@ -61,12 +61,11 @@ class ParallelSharpnessLoader:
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ret, frame = cap.read()
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if not ret: break
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# Send to thread
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future = executor.submit(self.calculate_sharpness, frame)
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futures.append((current_frame, future))
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scanned_count += 1
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# Manual Stepping (Skip N frames without decoding if possible)
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# Manual Stepping
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if frame_scan_step > 1:
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for _ in range(frame_scan_step - 1):
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if not cap.grab(): break
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@@ -80,14 +79,13 @@ class ParallelSharpnessLoader:
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cap.release()
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# 3. Selection (Best N with spacing)
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# 3. Selection
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frame_scores.sort(key=lambda x: x[1], reverse=True)
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selected = []
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for idx, score in frame_scores:
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if len(selected) >= return_count: break
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# Distance check
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if all(abs(s[0] - idx) >= min_distance for s in selected):
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selected.append((idx, score))
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@@ -95,7 +93,7 @@ class ParallelSharpnessLoader:
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selected.sort(key=lambda x: x[0])
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print(f"xx- Selected Frames: {[f[0] for f in selected]}")
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# 4. Extraction (Pass 2 - Load Images)
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# 4. Extraction (Pass 2)
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cap = cv2.VideoCapture(video_path)
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output_tensors = []
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info_log = []
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@@ -116,8 +114,6 @@ class ParallelSharpnessLoader:
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return (torch.stack(output_tensors), ", ".join(info_log))
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# --- Registration ---
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# This part makes ComfyUI see the node
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NODE_CLASS_MAPPINGS = {
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"ParallelSharpnessLoader": ParallelSharpnessLoader
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}
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