图片的色彩空间转换、简单色彩跟踪与通道分离、合并(三)

import cv2 as cv

#色彩空间的转换
def color_space_demo(image):
    gray=cv.cvtColor(image,cv.COLOR_BGR2GRAY)
    cv.imshow(‘gray‘,gray)
    hsv=cv.cvtColor(image,cv.COLOR_BGR2HSV)
    cv.imshow(‘hsv‘,hsv)
    yuv=cv.cvtColor(image,cv.COLOR_BGR2YUV)
    cv.imshow(‘hsv‘,yuv)

src=cv.imread(‘./yiner.jpg‘)
cv.namedWindow(‘before‘,cv.WINDOW_NORMAL)
cv.imshow(‘before‘,src)

color_space_demo(src)
cv.waitKey(0)
cv.destroyAllWindows()

#色彩空间转换,利用inrange函数过滤视频中的颜色,实现跟踪颜色
import cv2 as cv
import numpy as np

def catch_pen():
    capture=cv.VideoCapture(‘./1.mp4‘)#导入文件

    while True:
        ret,frame=capture.read()
        if ret==False:
            break
        #色彩空间转换到HSV
        hsv=cv.cvtColor(frame,cv.COLOR_BGR2HSV)
        # 设置黑色的范围，跟踪视频中的黑色
        lower_hsv=np.array([0,0,0]) #设置过滤的颜色的低值
        upper_hsv=np.array([180,255,46])#设置过滤的颜色的高值
        # 调节图像颜色信息（H）、饱和度（S）、亮度（V）区间，选择黑色区域
        mask=cv.inRange(hsv,lower_hsv,upper_hsv)
        cv.imshow(‘video‘,frame)
        cv.imshow(‘mask‘,mask)
        if cv.waitKey(50)&0xFF==ord(‘q‘):
            break

catch_pen()
cv.waitKey()
cv.destroyAllWindows()

import cv2 as cv
import numpy as np

src=cv.imread(‘hua.jpg‘)
cv.namedWindow(‘before‘,cv.WINDOW_NORMAL)
cv.imshow(‘before‘,src)

#通道分离
b,g,r=cv.split(src)
cv.imshow(‘blue‘,b)
cv.imshow(‘green‘,g)
cv.imshow(‘red‘,r)

#通道合并
src=cv.merge([b,g,r])
cv.imshow(‘merge‘,src)

# 修改某个通道
src[:,:,2]=100
cv.imshow(‘single‘,src)

cv.waitKey(0)
cv.destroyAllWindows()