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import os |
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import subprocess |
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import tqdm |
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from multiprocessing import Pool |
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paths = [] |
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def gather_paths(input_dir, output_dir): |
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for video in sorted(os.listdir(input_dir)): |
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if video.endswith(".mp4"): |
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video_input = os.path.join(input_dir, video) |
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video_output = os.path.join(output_dir, video) |
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if os.path.isfile(video_output): |
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continue |
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paths.append([video_input, output_dir]) |
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elif os.path.isdir(os.path.join(input_dir, video)): |
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gather_paths(os.path.join(input_dir, video), os.path.join(output_dir, video)) |
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def detect_shot(video_input, output_dir): |
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os.makedirs(output_dir, exist_ok=True) |
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video = os.path.basename(video_input)[:-4] |
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command = f"scenedetect --quiet -i {video_input} detect-adaptive --threshold 2 split-video --filename '{video}_shot_$SCENE_NUMBER' --output {output_dir}" |
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subprocess.run(command, shell=True) |
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def multi_run_wrapper(args): |
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return detect_shot(*args) |
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def detect_shot_multiprocessing(input_dir, output_dir, num_workers): |
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print(f"Recursively gathering video paths of {input_dir} ...") |
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gather_paths(input_dir, output_dir) |
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print(f"Detecting shot of {input_dir} ...") |
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with Pool(num_workers) as pool: |
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for _ in tqdm.tqdm(pool.imap_unordered(multi_run_wrapper, paths), total=len(paths)): |
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pass |
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if __name__ == "__main__": |
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input_dir = "/mnt/bn/maliva-gen-ai-v2/chunyu.li/ads/high-resolution" |
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output_dir = "/mnt/bn/maliva-gen-ai-v2/chunyu.li/ads/shot" |
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num_workers = 50 |
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detect_shot_multiprocessing(input_dir, output_dir, num_workers) |
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