#色彩空间转换
import cv2 as cv
def color_space_demo(img):
  gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) #RGB转换为GRAY 这里的GRAY是单通道的
  cv.imshow("gray", gray)
  hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV)   #RGB转换为HSV
  cv.imshow("hsv", hsv)
  yuv = cv.cvtColor(img, cv.COLOR_RGB2YUV)   #RGB转换为YUV
  cv.imshow("yuv",yuv)
  Ycrcb = cv.cvtColor(img, cv.COLOR_RGB2YCrCb) #RGB转换为YCrCb
  cv.imshow("Ycrcb", Ycrcb)
src = cv.imread('D:\imageload\example.png')
cv.namedWindow('first_image', cv.WINDOW_AUTOSIZE)
cv.imshow('first_image', src)
color_space_demo(src)
cv.waitKey(0)
cv.destroyAllWindows()

#视频特定颜色追踪
import cv2 as cv
import numpy as np
def extrace_object_demo():
  capture=cv.VideoCapture("E:/imageload/video_example.mp4")
  while True:
    ret, frame = capture.read()
    if ret == False:
      break
    hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)   #色彩空间由RGB转换为HSV
    lower_hsv = np.array([100, 43, 46])       #设置要过滤颜色的最小值
    upper_hsv = np.array([124, 255, 255])      #设置要过滤颜色的最大值
    mask = cv.inRange(hsv, lower_hsv, upper_hsv)  #调节图像颜色信息（H）、饱和度（S）、亮度（V）区间，选择蓝色区域
    cv.imshow("video",frame)
    cv.imshow("mask", mask)
    c = cv.waitKey(40)
    if c == 27:   #按键Esc的ASCII码为27
      break
extrace_object_demo()
cv.destroyAllWindows()

#通道的分离与合并以及某个通道值的修改
import cv2 as cv
src=cv.imread('E:\imageload\example.png')
cv.namedWindow('first_image', cv.WINDOW_AUTOSIZE)
cv.imshow('first_image', src)

#三通道分离形成单通道图片
b, g, r =cv.split(src)
cv.imshow("second_blue", b)
cv.imshow("second_green", g)
cv.imshow("second_red", r)
# 其中cv.imshow("second_red", r)可表示为r = cv2.split(src)[2]

#三个单通道合成一个三通道图片
src = cv.merge([b, g, r])
cv.imshow('changed_image', src)

#修改多通道里的某个通道的值
src[:, :, 2] = 0
cv.imshow('modify_image', src)

cv.waitKey(0)
cv.destroyAllWindows()