色彩空间（OpenCV + Python）

import cv2 as cv
import numpy as np

def extrace_object_demo():
    capture = cv.VideoCapture(0)
    while(True):
        ret,frame = capture.read()
        if ret == False:
            break
        hsv = cv.cvtColor(frame,cv.COLOR_BGR2HSV)
 #       lower_hsv = np.array([37,43,46])
#        upper_hsv = np.array([77,255,255])
        lower_hsv = np.array([0, 0, 46]) # 灰色这个颜色分别在三个通道范围的最低值
        upper_hsv = np.array([180, 43, 220]) # 灰色这个颜色在三个通道范围的最高值
        mask = cv.inRange(hsv,lowerb = lower_hsv,upperb = upper_hsv)
        cv.imshow("video",frame)
        cv.imshow("mask",mask)
        c = cv.waitKey(40)
        if c == 27:
            break


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("yuv",yuv)
    Ycrcb = cv.cvtColor(image,cv.COLOR_BGR2YCrCb)
    cv.imshow("ycrcb",Ycrcb)

src = cv.imread(r"C:\pics\beay.png")
cv.namedWindow("input image",cv.WINDOW_AUTOSIZE)
cv.imshow("input image",src)

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

src[:, :, 2] = 0        #通道合并
src = cv.merge([b,g,r])
cv.imshow("changed image",src)

#extrace_object_demo()
#color_space_demo(src)
cv.waitKey(0)

cv.destoryAllWindows()

cv.split()函数与src[:, :, 0] = 0有区别，前者是分离通道并转换为了一个灰度图像（即像素只由一个数值表达），而后者仍然是三通道RGB图像，只不过表示像素值的三个数某个数被改变（因此仍然是彩色图像）。

HSV 色彩空间分布