简述

下面中cap的内容选的是0，表示启动摄像头0（如果只有一个摄像头的话，就直接找到对应的那个）。

注释部分，其实是背景提取后的效果，或者是提取之后的再做阈值的处理后的图片

代码

import cv2

cap = cv2.VideoCapture(0)
bs = cv2.createBackgroundSubtractorKNN(detectShadows=True)

while True:
    ret, frame = cap.read()
    fgmask = bs.apply(frame)
    th = cv2.threshold(fgmask.copy(), 244, 255, cv2.THRESH_BINARY)[1]
    dilated = cv2.dilate(th, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)), iterations=2)
    image, content, hier = cv2.findContours(dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    for c in content:
        if cv2.contourArea(c) > 1600:
            (x, y, w, h) = cv2.boundingRect(c)
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
    # cv2.imshow("mog", fgmask)
    # cv2.imshow("thresh", th)
    cv2.imshow("detection", frame)

    if cv2.waitKey(1) & 0xff == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()