写一个测试YOLO算法帧率的python程序

要编写一个Python程序来测试YOLO（You Only Look Once）算法的帧率，首先需要安装必要的库如`yolov5`，`opencv-python`等。下面是一个简单的示例，这个程序将捕获视频流并计算YOLO模型处理每一帧的速度：

import cv2
from yolov5 import YOLO

# 加载预训练的YOLOv5模型
yolo = YOLO()

# 指定视频源，可以是文件路径或摄像头ID
video_capture = cv2.VideoCapture(0) # 使用摄像头作为输入

try:
    frame_rate = "FPS: ??"
    prev_time = cv2.getTickCount()
    
    while True:
        ret, frame = video_capture.read()  
        if not ret:
            break
        
        # 运行YOLO检测
        start_time = cv2.getTickCount()
        boxes = yolo.detect(frame)
        end_time = cv2.getTickCount()
        
        # 计算时间差
        time_diff = (end_time - start_time) / cv2.getTickFrequency()
        
        # 更新帧率
        current_time = cv2.getTickCount()
        fps = round(1 / time_diff)
        frame_rate = f"FPS: {fps}"
        
        # 在帧上显示帧率
        cv2.putText(frame, frame_rate, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)

        # 显示带有框的图像
        for box in boxes:
            x, y, w, h = box[:4]
            cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
        
        # 显示结果
        cv2.imshow("YOLO Detection", frame)
        key = cv2.waitKey(1)
        
        # 如果按下 'q' 键则退出循环
        if key == ord('q'):
            break
            
finally:
    # 释放资源
    video_capture.release()
    cv2.destroyAllWindows()