import gradio as gr from moviepy.editor import VideoFileClip import cv2 import base64 from openai import OpenAI import os # 參考: https://cookbook.openai.com/examples/gpt4o/introduction_to_gpt4o def process_video(video_path, seconds_per_frame=2): base64Frames = [] base_video_path, _ = os.path.splitext(video_path) video = cv2.VideoCapture(video_path) total_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT)) fps = video.get(cv2.CAP_PROP_FPS) frames_to_skip = int(fps * seconds_per_frame) curr_frame = 0 while curr_frame < total_frames - 1: video.set(cv2.CAP_PROP_POS_FRAMES, curr_frame) success, frame = video.read() if not success: break _, buffer = cv2.imencode(".jpg", frame) base64Frames.append(base64.b64encode(buffer).decode("utf-8")) curr_frame += frames_to_skip video.release() audio_path = f"{base_video_path}.mp3" clip = VideoFileClip(video_path) clip.audio.write_audiofile(audio_path, bitrate="32k") clip.audio.close() clip.close() return base64Frames, audio_path def summarize_video(file_path): api_key = os.getenv("OPENAI_API_KEY") client = OpenAI(api_key=api_key) # 抽取幀和音頻(每0.5秒一幀) base64Frames, audio_path = process_video(file_path, seconds_per_frame=0.5) # 使用Whisper進行音頻轉錄 transcription = client.audio.transcriptions.create( model="whisper-1", file=open(audio_path, "rb") ) # 使用GPT-4o生成摘要 response = client.chat.completions.create( model="gpt-4o", messages=[ { "role": "system", "content": """您是一名優秀的摘要專家,請根據提供的影片和其轉錄內容生成Markdown格式的摘要。""", }, { "role": "user", "content": [ "以下是從影片中提取的幀畫面", *map( lambda x: { "type": "image_url", "image_url": { "url": f"data:image/jpg;base64,{x}", "detail": "low", }, }, base64Frames, ), { "type": "text", "text": f"這是影片的轉錄內容: {transcription.text}", }, ], }, ], temperature=0, ) return response.choices[0].message.content demo = gr.Interface( fn=summarize_video, inputs=[gr.File(label="上傳影片 (mp4)")], outputs="markdown", title="影片摘要生成器", description="上傳影片,將生成影片的摘要。", ) if __name__ == "__main__": demo.launch()