一、填充轮廓
#_*_ encoding=utf-8 _*_ import numpy as np import cv2 img=cv2.imread('leilei.jpg') imggray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) #二值化图片,将灰度图片中>127的像素修改为255(白色) ret,thresh=cv2.threshold(imggray,127,255,0) # cv2.imshow('thresh',thresh) #在二值化图像中找轮廓,参数(输入图像,轮廓检索模式,轮廓近似方法),返回值(原图像,轮廓,轮廓的层析结构——轮廓之间的关系) #具体返回值含义见https://blog.csdn.net/jjddss/article/details/73527990 image,contours,hierarchy=cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) # cv2.imshow("image",image) # print("轮廓的数量:",np.size(contours)) # print("第一个轮廓的所有点的坐标:",contours[0]) # print("hierarchy",hierarchy) contourlist=[] #绘制轮廓 for contour in contours: if cv2.contourArea(contour)>200: contourlist.append(contour) #根据最后的参数不同,可以选择填充轮廓,还是 img=cv2.drawContours(image,contourlist,3,(0,255,0),3) cv2.imshow("img",img) cv2.waitKey(0)
在这里只将轮廓大于200的进行填充,但效果不咋明显。
这里用到的opencv工具有:
cv2.threshold()
cv2.findContours()
#在二值化图像中找轮廓,参数(输入图像,轮廓检索模式,轮廓近似方法),返回值(原图像,轮廓,轮廓的层析结构——轮廓之间的关系) #具体返回值含义见https://blog.csdn.net/jjddss/article/details/73527990
cv2.contourArea()
cv2.drawContours()
二、帧间差分法
python代码实现:
#_*_ encoding=utf-8 _*_ import cv2 import numpy as np vedioFile=r"Fueling.mp4" frame_x=720 frame_y=964 cap=cv2.VideoCapture(vedioFile) frontFrame=np.zeros((frame_x,frame_y),np.uint8) targetImage=np.zeros((frame_x,frame_y),np.uint8) kernel=cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5)) while cap.isOpened(): ret,frame=cap.read() frameGray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY) # (x,y,w,h)=cv2.boundingRect(frameGray) # print('x:{},y:{},w:{},h:{}'.format(x,y,w,h)) if frontFrame.sum()==0: frontFrame=frameGray else: #使用opencv的方法计算两帧相减并取绝对值 targetImage=cv2.absdiff(frameGray,frontFrame) ret,targetImage=cv2.threshold(targetImage,127,255,cv2.THRESH_BINARY) targetImage=cv2.morphologyEx(targetImage,cv2.MORPH_OPEN,kernel) targetImage=cv2.morphologyEx(targetImage,cv2.MORPH_CLOSE,kernel) frontFrame=frameGray cv2.imshow("targetImage",targetImage) k=cv2.waitKey(35)&0xFF if k==ord("q"): break