OpenCV之色彩空间的使用

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计算机视觉，这是第二天的学习笔记（颜色空间的类型，主要是hsv（h:色调 s:饱和度 v:明度）；色彩空间的转换，颜色的过滤，颜色通道的合并）

色彩空间的转换

cv.cvtColor(src,cv.COLOR_BGR2HSV)

色彩通道的分离

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

通道的合并

src=cv.merge([b,g,r])

追踪或者过滤某一种颜色

①先将每一帧视频转化成hsv
②设置最小值与最大值 通过hsv实例表进行查找
lower=np.array([h_low,s_low,v_low])
higher=np.array([h_high,s_high,v_high])
通过inRange接口进行实现 cv.inRange(hsv,lowerb=lower,upperb=higher)

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#色彩空间的使用
# rgb hsv his ycrcb yuv (常见的色彩空间)
import cv2 as cv
import numpy as np
class Color_space():
    def init_image(self,path):
        self.src=cv.imread(path)
    def close_cv(self):
        cv.waitKey(0)
        cv.destoryAllWindow()
    #色彩空间的相互转换
    def color_space_demo(self):
        gray=cv.cvtColor(self.src,cv.COLOR_BGR2GRAY)
        cv.imshow("gray",gray)
        hsv=cv.cvtColor(self.src,cv.COLOR_BGR2HSV)
        cv.imshow("hsv",hsv)
        # yuv = cv.cvtColor(self, cv.COLOR_BGR2YUV)
        # cv.imshow("yuv", yuv)
        ycrcb = cv.cvtColor(self.src, cv.COLOR_BGR2YCrCb)
        cv.imshow("ycrcb", ycrcb)
        cv.waitKey(0)
        cv.destroyAllWindows()
    #颜色的过滤,追踪某个颜色
    def extrace_object_demo(self):
        capture=cv.VideoCapture("D:/download/5.mp4")
        while(True):
            ret,frame=capture.read()
            if ret==False:
                break
            hsv=cv.cvtColor(frame,cv.COLOR_BGR2HSV)
            lower=np.array([156,43,46])
            higer=np.array([180,255,255])
            mck=cv.inRange(hsv,lowerb=lower,upperb=higer)
            cv.imshow("video",frame)
            cv.imshow("mck", mck)
            c=cv.waitKey(40)
            if c==27:
                break
    #通道的合并
    def image_merge(self):
        b,g,r=cv.split(self.src)
        cv.imshow("blue",b)
        cv.imshow("green",g)
        cv.imshow("red",r)
        self.src=cv.merge([b,g,r])
        cv.imshow("change image",self.src)
        cv.waitKey(0)
        cv.destroyAllWindows()
if __name__=="__main__":
    colo=Color_space()
    colo.extrace_object_demo()
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