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import gradio as gr |
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import os |
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from scenedetect import open_video, SceneManager |
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from scenedetect.detectors import ContentDetector |
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OUTPUT_DIR = "outputs" |
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os.makedirs(OUTPUT_DIR, exist_ok=True) |
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def detect_scenes(video_path): |
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if not video_path or not os.path.exists(video_path): |
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return "未找到影片檔案，請確認上傳檔案無誤", None |
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try: |
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video = open_video(video_path) |
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manager = SceneManager() |
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manager.add_detector(ContentDetector()) |
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manager.detect_scenes(video) |
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scene_list = manager.get_scene_list() |
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rows = [["Scene Number", "Start Time", "End Time"]] |
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for i, (start, end) in enumerate(scene_list): |
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rows.append([str(i + 1), str(start.get_timecode()), str(end.get_timecode())]) |
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fname, _ = os.path.splitext(os.path.basename(video_path)) |
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csv_path = os.path.join(OUTPUT_DIR, fname + "_scenes.csv") |
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with open(csv_path, "w", encoding='utf-8') as f: |
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for row in rows: |
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f.write(",".join(row) + "\n") |
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return f"偵測到 {len(scene_list)} 組分鏡，CSV 可下載", csv_path |
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except Exception as e: |
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return f"解析失敗：{e}", None |
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iface = gr.Interface( |
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fn=detect_scenes, |
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inputs=gr.Video(label="上傳影片"), |
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outputs=[gr.Textbox(label="分鏡結果"), gr.File(label="下載分鏡 CSV")], |
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title="PySceneDetect 分鏡偵測（可儲存 CSV）", |
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description="上傳影片，自動產生分鏡資訊，並可下載 CSV。支援 CPU 部署。" |
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) |
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if __name__ == "__main__": |
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iface.launch() |
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