python opencv 检测移动物体并截图保存实例

第pythonopencv检测移动物体并截图保存实例#camera=cv2.VideoCapture(0)#参数0表示第一个摄像头

camera=cv2.VideoCapture(file)

#参数设置，监测矩形区域

rectangleX=880#矩形最左点x坐标

rectangleXCols=0#矩形x轴上的长度

rectangleY=650#矩形最上点y坐标

rectangleYCols=100#矩形y轴上的长度

KeyFrame=17#取关键帧的间隔数，根据视频的帧率设置，我的视频是16FPS

counter=1#取帧计数器

pre_frame=None#总是取视频流前一帧做为背景相对下一帧进行比较

#判断视频是否打开

ifnotcamera.isOpened():

print(视频文件打开失败！)

width=int(camera.get(cv2.CAP_PROP_FRAME_WIDTH))

height=int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))

print(视频尺寸（高，宽）:,height,width)

ifrectangleXCols==0:

rectangleXCols=width-rectangleX

ifrectangleYCols==0:

rectangleYCols=height-rectangleY

start_time=datetime.now()

print({}开始处理文件：{}.format(start_time.strftime(%H:%M:%S),fname))

whileTrue:

grabbed,frame_lwpCV=camera.read()#读取视频流

ifgrabbed:

ifcounter%KeyFrame==0:

#ifnotgrabbed:

#print({}完成处理文件：{}。。。.format(datetime.now().strftime(%H:%M:%S),fname))

#break

gray_lwpCV=cv2.cvtColor(frame_lwpCV,cv2.COLOR_BGR2GRAY)#转灰度图

gray_lwpCV=gray_lwpCV[rectangleY:rectangleY+rectangleYCols,rectangleX:rectangleX+rectangleXCols]

lwpCV_box=cv2.rectangle(frame_lwpCV,(rectangleX,rectangleY),

(rectangleX+rectangleXCols,rectangleY+rectangleYCols),(0,255,0),

2)#用绿色矩形框显示监测区域

#cv2.imshow(lwpCVWindow,frame_lwpCV)#显示视频播放窗口，开启消耗时间大概是3倍

gray_lwpCV=cv2.GaussianBlur(gray_lwpCV,(21,21),0)

ifpre_frameisNone:

pre_frame=gray_lwpCV

else:

img_delta=cv2.absdiff(pre_frame,gray_lwpCV)

thresh=cv2.threshold(img_delta,25,255,cv2.THRESH_BINARY)[1]

thresh=cv2.dilate(thresh,None,iterations=2)

image,contours,hierarchy=cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL,

cv2.CHAIN_APPROX_SIMPLE)

forxincontours:

ifcv2.contourArea(x)1000:#设置敏感度

continue

else:

cv2.imwrite(

image/+fname+_+datetime.now().strftime(%H%M%S)+_+str(

random.randrange(0,9999))+.jpg,

frame_lwpCV)

#print(监测到移动物体。。。,datetime.now().strftime(%H:%M:%S))

break

pre_frame=gray_lwpCV

counter+=1

key=cv2.waitKey(1)0xFF

ifkey==ord(q):

break

else:

end_time=datetime.now()

print({}完成处理文件：{}耗时：{}.format(end_time.str