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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()
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