yolov8测试fps代码

当然，这是一个使用YOLOv4模型测试FPS的示例代码：

import cv2
import time

# 加载YOLOv4模型
net = cv2.dnn.readNet("yolov4.weights", "yolov4.cfg")

# 设置图像输入尺寸和归一化系数
inputWidth = 416
inputHeight = 416
scale = 1 / 255

# 获取输入层和输出层信息
layerNames = net.getLayerNames()
outputLayers = [layerNames[i[0] - 1] for i in net.getUnconnectedOutLayers()]

# 打开摄像头
cap = cv2.VideoCapture(0)

# 用于计算帧率的变量
start_time = time.time()
frame_count = 0

while True:
    # 读取帧
    ret, frame = cap.read()

    if not ret:
        break

    # 构建一个blob，将帧传递给模型进行预测
    blob = cv2.dnn.blobFromImage(frame, scale, (inputWidth, inputHeight), (0, 0, 0), True, crop=False)
    net.setInput(blob)
    outs = net.forward(outputLayers)

    # 处理预测结果
    # ...

    # 绘制FPS信息
    frame_count += 1
    if (time.time() - start_time) > 1:
        fps = frame_count / (time.time() - start_time)
        start_time = time.time()
        frame_count = 0
        cv2.putText(frame, "FPS: {:.2f}".format(fps), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)

    # 显示帧
    cv2.imshow("YOLOv4", frame)

    if cv2.waitKey(1) == ord('q'):
        break

# 释放资源
cap.release()
cv2.destroyAllWindows()

请确保已经下载了YOLOv4的权重文件（`yolov4.weights`）和配置文件（`yolov4.cfg`），并将它们与上述代码放在同一目录下。你可以根据自己的需要进行修改和调整。