1 OpenCV 读相机

import cv2cap = cv2.VideoCapture(0)
while (1):# get a frameret, frame = cap.read()# show a framecv2.imshow("capture", frame)if cv2.waitKey(1) & 0xFF == ord('q'):# cv2.imwrite("/opt/code/image/fangjian2.jpeg", frame)#passbreak
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  YOLOimport cv2def get_img(cap):while (1):# get a frameret, 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#    breakreturn 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