YOLOV8& OpenCV + usb 相机 实时识别

1 OpenCV 读相机

import cv2

cap = cv2.VideoCapture(0)
while (1):
    # get a frame
    ret, frame = cap.read()
    # show a frame
    cv2.imshow("capture", frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
       # cv2.imwrite("/opt/code/image/fangjian2.jpeg", frame)
       #pass
       break
cap.release()
cv2.destroyAllWindows()

2 yolov8推理

from ultralytics import  YOLO
model =YOLO('yolov8n.pt')

result = model.predict('dog.jpg',imgsz = 640,show = True)

3 yolov8 实时推理相机图片

 
from ultralytics import  YOLO

import cv2


def get_img(cap):
    while (1):
        # get a frame
        ret, frame = cap.read()
        # show a frame
        # cv2.imshow("capture", frame)
        # if cv2.waitKey(1) & 0xFF == ord('q'):
        #    # cv2.imwrite("/opt/code/image/fangjian2.jpeg", frame)
        #    #pass
        #    break
        return frame
m_cap = cv2.VideoCapture(0)
model =YOLO('yolov8n.pt')
# 输出检测结果和坐标
while True:
    img = get_img(m_cap)
    cv2.imshow("capture", img)
    cv2.waitKey(1)
    #results = model.predict(img)
    results = model.predict(img)
    annotated_frame = results[0].plot()
    cv2.imshow("YOLOv8 Tracking", annotated_frame)
    cv2.waitKey(1)

4 result

5 PS

总结，在一台老旧的电脑上

跑yolov8 n 感觉速度可以

识别精度也还凑合

原文地址：https://blog.csdn.net/qq_36784503/article/details/142415412

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