210_Python+OpenCV_010—色彩空间/二值化/split分离通道和merge合并

HSV

hue 色调
saturation 饱和度
value
OpenCV是0-180，主要是为了可以用Uint8，一个字节表示

做颜色物体跟踪的关键步骤

YCrCb

提取人的皮肤

最常见的HSV与RGB YUV与RGB转换

# -*- coding:utf-8 -*-
# Linda Li 2019/8/15 10:19 cv_01_色彩空间 PyCharm
import cv2 as cv


# RGB色彩空间 黑色(0,0,0) 白色 255,255,255
def color_space_demo(image):
    """BGR图像转换其他色彩空间"""

    # 转换为灰度图像
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    cv.imshow("gray", gray)

    # 转换为hsv图像
    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)


print("-----Hello Python----")
src = cv.imread("../cv_02/1.jpg")
cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
cv.imshow("input image", src)
color_space_demo(src)

# 如果设置waitKey(0),则表示程序会无限制的等待用户的按键事件
cv.waitKey(0)

cv.destroyAllWindows()

绿色二值化视频

# -*- coding:utf-8 -*-
# Linda Li 2019/8/15 15:04 cv_11_inchange PyCharm
import cv2 as cv
import numpy as np


def extract_object_demo():
    capture = cv.VideoCapture("../cv_02/cv_110.mp4")
    while True:
        ret, frame = capture.read()

        # ret为FALSE的时候说明播放完毕了，就退出视频, if ret == False
        if not ret:
            break
        hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)

        # 绿色的范围对应hsv表格找
        lower_hsv = np.array([35, 43, 46])
        upper_hsv = np.array([77, 255, 255])
        mask = cv.inRange(hsv, lower_hsv, upper_hsv)
        cv.imshow("video", frame)
        cv.imshow("hsv_mask", mask)
        #  在这个程序中,我们告诉OpenCv等待用户触发事件,等待时间为40ms，
        #  如果在这个时间段内, 用户按下ESC(ASCII码为27),则跳出循环,否则,则跳出循环
        c = cv.waitKey(40)
        if c == 27:
            break


print("-------hello python-------")

extract_object_demo()

cv.waitKey(0)
cv.destroyAllWindows()

split分离通道

# -*- coding:utf-8 -*-
# Linda Li 2019/8/15 10:19 cv_01_色彩空间 PyCharm
import cv2 as cv


print("-----Hello Python----")
src = cv.imread("../cv_02/1.jpg")
cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
cv.imshow("input image", src)

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

# 将最后一个通道red设置为0,相当于将红色的通道值没有了，blue和green的合并时发青色
src[:, :, 2] = 0
cv.imshow("changed image", src)
# 如果设置waitKey(0),则表示程序会无限制的等待用户的按键事件
cv.waitKey(0)

cv.destroyAllWindows()

merge 合并通道

# -*- coding:utf-8 -*-
# Linda Li 2019/8/15 10:19 cv_01_色彩空间 PyCharm
import cv2 as cv


print("-----Hello Python----")
src = cv.imread("../cv_02/1.jpg")
cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
cv.imshow("input image", src)

b, g, r = cv.split(src)


src1 = cv.merge([b, g, r])
cv.imshow("merge", src1)
# 如果设置waitKey(0),则表示程序会无限制的等待用户的按键事件
cv.waitKey(0)

cv.destroyAllWindows()

标签：src,210,Python,image,imshow,merge,hsv,cv,waitKey
来源： https://blog.csdn.net/weixin_44304362/article/details/99623341