代码

解释都在注释里啦

import cv2 as cv
import numpy as nm

#调用转换函数实现图像色彩空间转换
def colorSpace(img):
    gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) # 将RGB转换为GRAY
    cv.imshow("gray", gray)
    hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV)  # 将RGB转换为HSV
    cv.imshow("hsv", hsv)
    yuv = cv.cvtColor(img, cv.COLOR_BGR2YUV)  # 将RGB转换为YUV
    cv.imshow("yuv", yuv)


def testColorSpace():
    src = cv.imread("me.jpg")
    cv.namedWindow("Before", cv.WINDOW_NORMAL)
    cv.imshow("Before", src)
    colorSpace(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，实现跟踪某一颜色
def traceColor():
    cap=cv.VideoCapture("you.mp4")
    while True:
        ret, frame = cap.read()  
        if ret==False:
            print("Wrong")
            break
        else:
            hsv=cv.cvtColor(frame,cv.COLOR_BGR2HSV)
            # 转换色彩空间为hsv
            hsvLow = nm.array([26, 43, 26])  
            # 设置过滤的颜色的低值
            hsvHigh = nm.array([34, 255, 255])
              # 设置过滤的颜色的高值 
            change = cv.inRange(hsv, hsvLow, hsvHigh)
            # 节图像颜色信息（H）、饱和度（S）、亮度（V）区间
            cv.imshow("Before",frame)
            cv.imshow("After",change)
            if cv.waitKey(50) & 0xFF==ord("r"):
                cv.destroyAllWindows()
                break


#通道分离、合并，修改某一通道
def operate(img):
    #通道分离
    b,g,r=cv.split(img)
    cv.imshow("blue",b)
    cv.imshow("green",g)
    cv.imshow("red",r)

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

    #修改通道值
    img[:,:,1]=100
    cv.imshow("single",img)

def testOperate():
    src = cv.imread("me.jpg")
    cv.namedWindow("Before", cv.WINDOW_NORMAL)
    cv.imshow("Before", src)
    operate(src)
    cv.waitKey(0)
    cv.destroyAllWindows()


testColorSpace()
testOperate()