Create app.py

app.py

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+import gradio as gr
+import os
+from scenedetect import open_video, SceneManager
+from scenedetect.detectors import ContentDetector
+
+# 儲存 output 路徑
+OUTPUT_DIR = "outputs"
+os.makedirs(OUTPUT_DIR, exist_ok=True)
+
+def detect_scenes(video):
+    # 儲存上傳影片至暫存位置
+    input_path = video.name
+    # 初始化 scenedetect
+    video_stream = open_video(input_path)
+    scene_manager = SceneManager()
+    scene_manager.add_detector(ContentDetector())
+    scene_manager.detect_scenes(video_stream)
+
+    # 取得分鏡
+    scene_list = scene_manager.get_scene_list()
+    csv_rows = [["Scene Number", "Start Time", "End Time"]]
+    for i, (start, end) in enumerate(scene_list):
+        csv_rows.append([i+1, str(start.get_timecode()), str(end.get_timecode())])
+    
+    # 輸出 CSV
+    csv_path = os.path.join(OUTPUT_DIR, os.path.splitext(os.path.basename(input_path)) + "_scenes.csv")
+    with open(csv_path, "w") as f:
+        for row in csv_rows:
+            f.write(",".join(map(str, row)) + "\n")
+    
+    return f"偵測到 {len(scene_list)} 段分鏡，CSV 已儲存", csv_path
+
+iface = gr.Interface(
+    fn=detect_scenes,
+    inputs=gr.Video(label="上傳影片"),
+    outputs=[gr.Textbox(label="分鏡結果"), gr.File(label="分鏡 CSV")],
+    title="PySceneDetect 分鏡檢測 (CPU)",
+    description="自動分鏡檢測並可下載分鏡資訊表。"
+)
+
+iface.launch()