## v0.9.20260325_144654 ### Features - API Key Authentication System - Job Worker System - V2 Backup Versioning ### Bug Fixes - get_processor_results_by_job column mapping Co-authored-by: OpenCode
107 lines
3.2 KiB
Python
Executable File
107 lines
3.2 KiB
Python
Executable File
#!/opt/homebrew/bin/python3.11
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"""
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CUT Processor - Scene Detection
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Uses PySceneDetect for scene detection (local)
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"""
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import sys
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import json
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import argparse
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import os
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from redis_publisher import RedisPublisher
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def process_cut(video_path: str, output_path: str, uuid: str = ""):
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"""Process video for scene detection"""
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publisher = RedisPublisher(uuid) if uuid else None
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if publisher:
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publisher.info("cut", "CUT_START")
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try:
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from scenedetect import VideoManager, SceneManager
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from scenedetect.detectors import ContentDetector
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except ImportError:
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if publisher:
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publisher.error("cut", "scenedetect not installed")
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result = {"frame_count": 0, "fps": 0.0, "scenes": []}
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if publisher:
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publisher.complete("cut", "0 scenes")
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with open(output_path, "w") as f:
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json.dump(result, f, indent=2)
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return result
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if publisher:
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publisher.info("cut", "CUT_LOADING_VIDEO")
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# Create video manager and scene manager
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video_manager = VideoManager([video_path])
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scene_manager = SceneManager()
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# Add content detector (detects scene cuts based on frame differences)
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# threshold: sensitivity (lower = more sensitive, default 30)
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# min_scene_len: minimum frames per scene (default 15)
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scene_manager.add_detector(ContentDetector(threshold=30.0, min_scene_len=15))
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# Set downscale factor for faster processing
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video_manager.set_downscale_factor()
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if publisher:
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publisher.info("cut", "CUT_DETECTING")
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# Start video manager
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video_manager.start()
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# Detect scenes
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scene_manager.detect_scenes(frame_source=video_manager)
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# Get scene list
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scene_list = scene_manager.get_scene_list()
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# Get frame rate
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fps = video_manager.get_framerate()
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if publisher:
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publisher.info("cut", f"fps={fps}")
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# Get total frame count
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frame_count = 0
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if scene_list:
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frame_count = scene_list[-1][1].get_frames()
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# Convert scenes to result format
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scenes = []
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for i, (start, end) in enumerate(scene_list):
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scene = {
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"scene_number": i + 1,
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"start_frame": start.get_frames(),
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"end_frame": end.get_frames() - 1, # end is exclusive
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"start_time": start.get_seconds(),
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"end_time": end.get_seconds() - (1.0 / fps) if fps > 0 else 0,
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}
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scenes.append(scene)
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if publisher:
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publisher.progress("cut", i + 1, len(scene_list), f"Scene {i + 1}")
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result = {"frame_count": frame_count, "fps": fps, "scenes": scenes}
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with open(output_path, "w") as f:
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json.dump(result, f, indent=2)
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if publisher:
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publisher.complete("cut", f"{len(scenes)} scenes")
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return result
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Scene Detection")
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parser.add_argument("video_path", help="Path to video file")
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parser.add_argument("output_path", help="Output JSON path")
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parser.add_argument("--uuid", "-u", help="UUID for Redis progress", default="")
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args = parser.parse_args()
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process_cut(args.video_path, args.output_path, args.uuid)
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