使用python-opencv进行背景子跟踪的质心跟踪

import cv2
import numpy as np

cap = cv2.VideoCapture('video.mp4')  # 从视频文件读取
# cap = cv2.VideoCapture(0)  # 从摄像头读取

fgbg = cv2.createBackgroundSubtractorMOG2()

while True:
    ret, frame = cap.read()
    if not ret:
        break
    
    # 背景提取
    fgmask = fgbg.apply(frame)
    
    # 进行形态学操作，去除噪声
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
    fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
    
    # 寻找轮廓
    contours, hierarchy = cv2.findContours(fgmask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    
    # 寻找最大轮廓
    max_contour = max(contours, key=cv2.contourArea)
    
    # 计算质心
    M = cv2.moments(max_contour)
    if M["m00"] != 0:
        cx = int(M["m10"] / M["m00"])
        cy = int(M["m01"] / M["m00"])
        cv2.circle(frame, (cx, cy), 5, (0, 255, 0), -1)
    
    # 显示结果
    cv2.imshow('Frame', frame)
    cv2.imshow('FG Mask', fgmask)
    
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()