如何在python opencv中获得hsv颜色的高低值

时间:2019-07-03 05:13:38

标签: python opencv hsv

我正在尝试在python opencv中检测几种颜色。为此,我需要定义高和低hsv值,以便代码可以读取它并检测颜色。现在,我面临的问题是如何获得高和低的hsv颜色。我指的是下图

enter image description here

我需要检测这件夹克,因此需要输入其高和低hsv。为此,我获得了对此code的引用,该引用允许选择图像的任何部分并为其输出高和低hsv值。但是据我所知,hsv值不能大于100,但是此代码和在线其他大多数代码给出的hsv值都大于100,这让我很困惑,这些值如何大于100。

任何人都可以解释一下如何获取hsv值的低值

2 个答案:

答案 0 :(得分:2)

尝试以下代码:

import cv2
import numpy as np

img = cv2.imread("jacket.jpg")

hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# mask of green (36,25,25) ~ (86, 255,255)
mask = cv2.inRange(hsv, (36, 25, 25), (70, 255,255))

green = cv2.bitwise_and(img,img, mask= mask)    

cv2.imshow('Image', green)
cv2.waitKey(0)
cv2.destroyAllWindowss()

输出:

enter image description here

查看this stackoverflow有关如何正确选择上下hsv值进行颜色检测的讨论。

答案 1 :(得分:1)

找不到资源,但是找到了类似的东西并制成了它 有用,谢谢作者

import cv2
import imutils  
import numpy as np  

image_hsv = None   # global
pixel = (20,60,80) # some stupid default

# mouse callback function
def pick_color(event,x,y,flags,param):
    if event == cv2.EVENT_LBUTTONDOWN:
        pixel = image_hsv[y,x]

        #you might want to adjust the ranges(+-10, etc):
        upper =  np.array([pixel[0] + 10, pixel[1] + 10, pixel[2] + 40])
        lower =  np.array([pixel[0] - 10, pixel[1] - 10, pixel[2] - 40])
        print(pixel, lower, upper)

        image_mask = cv2.inRange(image_hsv,lower,upper)
        cv2.imshow("mask",image_mask)

def main():
    import sys
    global image_hsv, pixel # so we can use it in mouse callback

    image_src = cv2.imread("myimage.jpeg")  # pick.py my.png
    image_src = imutils.resize(image_src, height=800)
    if image_src is None:
        print ("the image read is None............")
        return
    cv2.imshow("bgr",image_src)

    ## NEW ##
    cv2.namedWindow('hsv')
    cv2.setMouseCallback('hsv', pick_color)

    # now click into the hsv img , and look at values:
    image_hsv = cv2.cvtColor(image_src,cv2.COLOR_BGR2HSV)
    cv2.imshow("hsv",image_hsv)

    cv2.waitKey(0)
    cv2.destroyAllWindows()

if __name__=='__main__':
    main()

加载的图像如下所示:

enter image description here

点击球后,您将获得类似的图像

enter image description here

最后:终端将显示真实的BGR值,HSV上下边界,

enter image description here