python opencv3 背景分割 mog2 knn

git：https://github.com/linyi0604/Computer-Vision

使用mog2算法进行背景分割

 # coding:utf-8

 import cv2

 # 获取摄像头对象

 cap = cv2.VideoCapture(0)

 # 背景分割器对象

 mog = cv2.createBackgroundSubtractorMOG2()

 while True:

     ret, frame = cap.read()

     fgmask = mog.apply(frame)

     cv2.imshow("frame", fgmask)

     if cv2.waitKey(5) & 0xff == ord("q"):

         break

 cap.release()

 cv2.destroyAllWindows()

使用knn进行背景分割 顺便检测运动物体

 # coding:utf-8

 import cv2

 # 获取摄像头

 camera = cv2.VideoCapture(0)

 # 获取背景分割器对象

 bs = cv2.createBackgroundSubtractorKNN(detectShadows=True)

 while True:

     # 读取帧

     ret, frame = camera.read()

     # 获取前景

     fgmask = bs.apply(frame)

     # 对前景二值化

     th = cv2.threshold(fgmask.copy(), 244, 255, cv2.THRESH_BINARY)[1]

     # 膨胀运算

     dilated = cv2.dilate(th, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)), iterations=2)

     # 检测轮廓

     image, contours, hier = cv2.findContours(dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

     # 将轮廓画在原图像上

     for c in contours:

         x, y, w, h = cv2.boundingRect(c)

         cv2.rectangle(frame, (x, y), (x+w, y+h), (2555, 255, 0), 2)

     # 显示前景

     cv2.imshow("fgmask", fgmask)

     # 显示二值化

     cv2.imshow("thresh", th)

     # 显示带有轮廓的原图

     cv2.imshow("detection", frame)

     if cv2.waitKey(5) & 0xff == ord("q"):

         break

 cv2.destroyAllWindows()

 camera.release()