如何从健康地区掩蔽感染区域？

Question

import cv2
import numpy as np

img =  cv2.imread('AFTER_5746.png')
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# find the green color 
mask_green = cv2.inRange(hsv, (36,0,0), (86,255,255))
# find the brown color
mask_brown = cv2.inRange(hsv, (90, 60, 20), (30, 255, 200))
# find the yellow color in the leaf
mask_yellow = cv2.inRange(hsv, (14, 39, 64), (40, 255, 255))

# find any of the three colors(green or brown or yellow) in the image
mask = cv2.bitwise_or(mask_green, mask_brown)
mask = cv2.bitwise_or(mask, mask_yellow)

# Bitwise-AND mask and original image
res = cv2.bitwise_and(img,img, mask= mask)

cv2.imshow("original", img)
cv2.imshow("final image", res)
cv2.waitKey(0)
cv2.destroyAllWindows()

我使用HSV颜色图对图像进行分割，但是提取的叶子图像中的棕色区域总是会丢失，如下所示：

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如何使mask_brown可见？

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Answer 1

你的棕色面罩是空的(没有白色)。你是怎么得到布朗的价值的？它们在OpenCV HSV中不包括棕色。您的棕色是在色调=0/180环绕过渡。OpenCV inRange()似乎不喜欢将160到20分别指定为较低的和较高的(没有分成两种褐变，一种是从160到180，另一种从0到20)。所以我只给了0到180来覆盖范围。不要走得太高(V)，否则你会开始包括天空。

下面是在Python/OpenCV中适用于我的棕色颜色的选择。

输入：

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import cv2
import numpy as np

img =  cv2.imread('AFTER_5746.png')
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# find the green color 
mask_green = cv2.inRange(hsv, (36,0,0), (86,255,255))
# find the brown color
mask_brown = cv2.inRange(hsv, (0, 0, 0), (180, 255, 160))
# find the yellow color in the leaf
mask_yellow = cv2.inRange(hsv, (14, 39, 64), (40, 255, 255))

# find any of the three colors(green or brown or yellow) in the image
mask = cv2.bitwise_or(mask_green, mask_brown)
mask = cv2.bitwise_or(mask, mask_yellow)

# Bitwise-AND mask and original image
res = cv2.bitwise_and(img,img, mask= mask)

cv2.imshow("original", img)
cv2.imshow("mask_green", mask_green)
cv2.imshow("mask_brown", mask_brown)
cv2.imshow("mask_yellow", mask_yellow)
cv2.imshow("mask", mask)
cv2.imshow("final image", res)
cv2.waitKey(0)
cv2.destroyAllWindows()

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我想这就是你想要的。