yolov8使用opencv 调用摄像头，实时目标检测，左上角显示帧率_opencv显示yolov8识别结果

import cv2
from ultralytics import YOLO
from cv2 import getTickCount, getTickFrequency
# 加载 YOLOv8 模型
model = YOLO("weights/yolov8s.pt")

# 获取摄像头内容，参数 0 表示使用默认的摄像头
cap = cv2.VideoCapture(0)

while cap.isOpened():
    loop_start = getTickCount()
    success, frame = cap.read()  # 读取摄像头的一帧图像

    if success:
        results = model.predict(source=frame) # 对当前帧进行目标检测并显示结果
    annotated_frame = results[0].plot()

    # 中间放自己的显示程序
    loop_time = getTickCount() - loop_start
    total_time = loop_time / (getTickFrequency())
    FPS = int(1 / total_time)
    # 在图像左上角添加FPS文本
    fps_text = f"FPS: {FPS:.2f}"
    font = cv2.FONT_HERSHEY_SIMPLEX
    font_scale = 1
    font_thickness = 2
    text_color = (0, 0, 255)  # 红色
    text_position = (10, 30)  # 左上角位置

    cv2.putText(annotated_frame, fps_text, text_position, font, font_scale, text_color, font_thickness)
    cv2.imshow('img', annotated_frame)
    # 通过按下 'q' 键退出循环
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()  # 释放摄像头资源
cv2.destroyAllWindows()  # 关闭OpenCV窗口


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