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wf.setframerate(RATE)
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wf.writeframes(b''.join(frames))
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# 视频录制线程
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def record_video(stop_event):
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# time.sleep(5)
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cap = cv2.VideoCapture(0)
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cap.set(cv2.CAP_PROP_FRAME_WIDTH, FRAME_WIDTH)
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cap.set(cv2.CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT)
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cap.set(cv2.CAP_PROP_FPS, FRAME_RATE)
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fourcc = cv2.VideoWriter_fourcc(*'XVID')
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out = cv2.VideoWriter(TEMP_VIDEO_FILE, fourcc, FRAME_RATE, (FRAME_WIDTH, FRAME_HEIGHT))
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print("开始录像...")
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while not stop_event.is_set():
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ret, frame = cap.read()
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if ret:
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out.write(frame)
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cv2.imshow('Recording Video', frame)
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if cv2.waitKey(1) & 0xFF == ord('q'): # 按 Q 退出摄像头窗口
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stop_event.set()
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else:
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break
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print("录像结束。")
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cap.release()
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out.release()
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cv2.destroyAllWindows()
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# 合并音视频
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def merge_audio_video(audio_file, video_file, output_file):
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print("正在合并音频和视频...")
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ffmpeg.input(video_file).output(audio_file, output_file, vcodec='copy', acodec='aac', strict='experimental').run(overwrite_output=True)
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print(f"合并完成，文件保存为: {output_file}")
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# 主函数
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def main():
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stop_event = threading.Event()
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# 启动音频和视频录制线程
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audio_thread = threading.Thread(target=record_audio, args=(stop_event,))
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video_thread = threading.Thread(target=record_video, args=(stop_event,))
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print("按 Enter 键开始录制...")
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input() # 等待用户按下 Enter 键
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print("录制中... 再次按 Enter 键停止录制。")
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audio_thread.start()
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video_thread.start()
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input() # 等待用户再次按下 Enter 键
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stop_event.set()
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audio_thread.join()
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video_thread.join()
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# # 合并音频和视频
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# merge_audio_video(TEMP_AUDIO_FILE, TEMP_VIDEO_FILE, OUTPUT_FILE)
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# # 清理临时文件
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# os.remove(TEMP_AUDIO_FILE)
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# os.remove(TEMP_VIDEO_FILE)
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print("录制完成！")
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# -------------- Load QWen2-VL Model ------------
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# default: Load the model on the available device(s)
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model = Qwen2VLForConditionalGeneration.from_pretrained(
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"Qwen/Qwen2-VL-2B-Instruct", torch_dtype="auto", device_map="auto"
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)
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# ------- 设置分辨率，降低现存占用 -------
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min_pixels = 256*28*28
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max_pixels = 512*28*28
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processor = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-2B-Instruct", min_pixels=min_pixels, max_pixels=max_pixels)
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# --------------------------------------
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# -------- SenceVoice 语音识别 --模型加载-----
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model_dir = r"E:\2_PYTHON\Project\GPT\QWen\pretrained_models\SenseVoiceSmall"
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model_senceVoice = AutoModel( model=model_dir, trust_remote_code=True, )
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if __name__ == "__main__":
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while 1:
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main()
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folder_path = "./Test_QWen2_VL/"
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os.makedirs(folder_path, exist_ok=True)
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file_path = os.path.join(folder_path, "captured_image.jpg") # 设置保存路径
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cap = cv2.VideoCapture(TEMP_VIDEO_FILE)
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total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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frame_index = int(total_frames // 2)
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# 设置视频帧位置
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cap.set(cv2.CAP_PROP_POS_FRAMES, frame_index)
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ret, frame = cap.read()
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if not ret:
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print(f"无法读取帧索引 {frame_index}")
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else:
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# 显示帧
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cv2.imwrite(file_path, frame)
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