git：https://github.com/linyi0604/Computer-Vision
使用mog2算法进行背景分割
1 # coding:utf-8
2
3 import cv2
4
5 # 获取摄像头对象
6 cap = cv2.VideoCapture(0)
7 # 背景分割器对象
8 mog = cv2.createBackgroundSubtractorMOG2()
9
10 while True:
11 ret, frame = cap.read()
12 fgmask = mog.apply(frame)
13 cv2.imshow("frame", fgmask)
14 if cv2.waitKey(5) & 0xff == ord("q"):
15 break
16
17 cap.release()
18 cv2.destroyAllWindows()
使用knn进行背景分割 顺便检测运动物体
1 # coding:utf-8
2
3 import cv2
4
5 # 获取摄像头
6 camera = cv2.VideoCapture(0)
7 # 获取背景分割器对象
8 bs = cv2.createBackgroundSubtractorKNN(detectShadows=True)
9
10 while True:
11 # 读取帧
12 ret, frame = camera.read()
13 # 获取前景
14 fgmask = bs.apply(frame)
15 # 对前景二值化
16 th = cv2.threshold(fgmask.copy(), 244, 255, cv2.THRESH_BINARY)[1]
17 # 膨胀运算
18 dilated = cv2.dilate(th, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)), iterations=2)
19 # 检测轮廓
20 image, contours, hier = cv2.findContours(dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
21 # 将轮廓画在原图像上
22 for c in contours:
23 x, y, w, h = cv2.boundingRect(c)
24 cv2.rectangle(frame, (x, y), (x+w, y+h), (2555, 255, 0), 2)
25 # 显示前景
26 cv2.imshow("fgmask", fgmask)
27 # 显示二值化
28 cv2.imshow("thresh", th)
29 # 显示带有轮廓的原图
30 cv2.imshow("detection", frame)
31 if cv2.waitKey(5) & 0xff == ord("q"):
32 break
33
34 cv2.destroyAllWindows()
35 camera.release()
