#-*- coding:utf-8 -*-
import cv2
import numpy as np
# 1.常见一个BackgroundSubtractorKNN接口
bs = cv2.createBackgroundSubtractorKNN(detectShadows=True)
#2.读取视频
camera = cv2.VideoCapture(r"aaa.mp4")
#定义卷积核圆形
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))
while True:
ret,frame = camera.read()
#3. apply()函数计算了前景掩码
fgmask = bs.apply(frame)
#4. 获得前景掩码（含有白色值以及阴影的灰色值），通过设定阈值将非白色（244~255）的所有像素都设为0，而不是1；
th = cv2.threshold(fgmask.copy(),244,255,cv2.THRESH_BINARY)[1] #二值化操作
dilated = cv2.dilate(th,kernel,iterations =2) #5.膨胀操作
#cv2.getStructuringElement 构建一个椭圆形的核
#3x3卷积核中有2个1那就设置为1
#6. findContours函数参数说明cv2.RETR_EXTERNAL只检测外轮廓，
# cv2.CHAIN_APPROX_SIMPLE只存储水平，垂直，对角直线的起始点。
contours,hier = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) #查找轮廓
for c in contours: #从list列表取出每个轮廓
if cv2.contourArea(c) < 1500: #进行轮廓筛选 轮廓面积小于1500
continue
(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(100) & 0xff == ord("q"):
break
camera.release()
cv2.destroyAllWindows()
