使用opencv3+python实现视频运动目标检测

本文主要实现了伯乐在线上的一个实践小项目,原文链接,用以巩固opencv视频操作知识内容。整个项目均有代码注释,通俗易懂,短短几十行就可以达到还算不错的实现效果,做起来成就感满满哒。打开编辑器,一起来感受下opencv+python在CV中的无穷魅力吧 ^_^

 1 import argparse
 2 import time
 3 import imutils
 4 import cv2
 5 
 6 # 创建参数解析器并解析参数
 7 ap = argparse.ArgumentParser()
 8 ap.add_argument("-v", "--video", help="path of the video")
 9 # 待检测目标的最小面积,该值需根据实际应用情况进行调整(原文为500)
10 ap.add_argument("-a", "--min-area", type=int, default=2000, help="minimum area size")
11 args = vars(ap.parse_args())    #@
12 
13 # 如果video参数为空,则从自带摄像头获取数据
14 if args.get("video") == None:
15     camera = cv2.VideoCapture(0)
16 # 否则读取指定的视频
17 else:
18     camera = cv2.VideoCapture(args["video"])
19 
20 
21 # 开始之前先暂停一下,以便跑路(离开本本摄像头拍摄区域^_^)
22 print("Ready?")
23 time.sleep(1)
24 print("Action!")
25 
26 # 初始化视频第一帧
27 firstRet, firstFrame = camera.read()
28 if not firstRet:
29     print("Load video error!")
30     exit(0)
31 
32 # 对第一帧进行预处理
33 firstFrame = imutils.resize(firstFrame, width=500)  # 尺寸缩放,width=500
34 gray_firstFrame = cv2.cvtColor(firstFrame, cv2.COLOR_BGR2GRAY) # 灰度化
35 firstFrame = cv2.GaussianBlur(gray_firstFrame, (21, 21), 0) #高斯模糊,用于去噪
36 
37 # 遍历视频的每一帧
38 while True:
39     (ret, frame) = camera.read()
40 
41     # 如果没有获取到数据,则结束循环
42     if not ret:
43         break
44 
45     # 对获取到的数据进行预处理
46     frame = imutils.resize(frame, width=500)
47     gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
48     gray_frame = cv2.GaussianBlur(gray_frame, (21, 21), 0)
49 
50     # cv2.imshow('video', firstFrame)
51     # 计算第一帧和其他帧的差别
52     frameDiff = cv2.absdiff(firstFrame, gray_frame)
53     # 忽略较小的差别
54     retVal, thresh = cv2.threshold(frameDiff, 25, 255, cv2.THRESH_BINARY)
55 
56     # 对阈值图像进行填充补洞
57     thresh = cv2.dilate(thresh, None, iterations=2)
58     image, contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
59 
60     text = "Unoccupied"
61     # 遍历轮廓
62     for contour in contours:
63         # if contour is too small, just ignore it
64         if cv2.contourArea(contour) < args["min_area"]:
65             continue
66 
67         # 计算最小外接矩形(非旋转)
68         (x, y, w, h) = cv2.boundingRect(contour)
69         cv2.rectangle(frame, (x, y), (x+w, y+h), (0,255,0), 2)
70         text = "Occupied!"
71 
72     cv2.putText(frame, "Room Status: {}".format(text), (10,20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,0,255), 2)
73 
74     cv2.imshow('frame', frame)
75     cv2.imshow('thresh', thresh)
76     cv2.imshow('frameDiff', frameDiff)
77 
78     # 处理按键效果
79     key = cv2.waitKey(60) & 0xff
80     if key == 27:   # 按下ESC时,退出
81         break
82     elif key == ord(' '):   # 按下空格键时,暂停
83         cv2.waitKey(0)
84 
85 # 释放资源并关闭所有窗口
86 camera.release()
87 cv2.destroyAllWindows()
View Code

 

附上原文实验结果:

Reference

posted @ 2017-05-03 16:44  朝研行歌  阅读(10561)  评论(0编辑  收藏  举报