2018-03-0421:22:46
(1)cv.InRange函数
void cvInRange(//提取图像中在阈值中间的部分 const CvArr* src,//目标图像const CvArr* lower,//阈值下限 const CvArr* upper,//阈值上限 CvArr* dst//结果图像 )
历程:# 取出摄像头中,绿色的区域
import cv2 as cv import numpy as np def video_demo(): capture = cv.VideoCapture(0) while(True): # 打开摄像头 ret,frame = capture.read() if ret == False: break # 转换为hsv图像 hsv = cv.cvtColor(frame,cv.COLOR_BGR2HSV) # 下阈值 lower_hsv = np.array([37,43,46]) # 上阈值 upper_hsv = np.array([77,255,255]) mask = cv.inRange(hsv,lowerb=lower_hsv,upperb = upper_hsv) # cv.inRange(目标图像,阈值下,阈值上,输出图像) cv.imshow ("video",frame) cv.imshow ( "mask",mask) c = cv.waitKey (50) if c == 27: # 相当于人为退出 break video_demo()
原文地址:https://www.cnblogs.com/pengwenzheng/p/8506254.html
时间: 2024-11-06 09:38:00