如何使用 OpenCV 和蒙版从图像中选择好的颜色？

Question

我正在尝试使用 OpenCV 选择图像中的绿色（这样做的方法来自这个网站。我正在处理的图像是：

import cv2
import matplotlib.pyplot as plt
import numpy as np

greenhsv = (60, 255, 255)
green2hsv=(70,100,170)
g_square = np.full((10, 10, 3), greenhsv, dtype=np.uint8)/255.0
plt.imshow(hsv_to_rgb(g_square))
plt.show()
g1_square = np.full((10, 10, 3), green2hsv, dtype=np.uint8)/255.0
plt.imshow(hsv_to_rgb(g1_square))
plt.show()

nucl = cv2.imread('./Pictures/image_nucleation_essai0.png')
nucl = cv2.cvtColor(nucl, cv2.COLOR_BGR2RGB)
plt.imshow(nucl)
plt.show()

hsv_nucl = cv2.cvtColor(nucl, cv2.COLOR_RGB2HSV)

mask = cv2.inRange(hsv_nucl, greenhsv,green2hsv)
result = cv2.bitwise_and(nucl, nucl, mask=mask)
plt.imshow(mask, cmap="gray")
plt.show()
plt.imshow(result)
plt.show()

结果是：

所以口罩没用。

Answer 1

您的颜色范围还不太正确。此外 inRange() 函数中的变量顺序错误。是from-to，所以颜色深的一定要先。将您的代码更改为cv2.inRange(hsv_nucl, green2hsv,greenhsv) 您可以使用/调整下面代码中的值，这是可行的。
结果：

白色背景：

import numpy as np 
import cv2

# load image
img = cv2.imread("Eding.png")
# convert to HSV
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) 
# set lower and upper color limits
lower_val = np.array([50,100,170])
upper_val = np.array([70,255,255])
# Threshold the HSV image to get only green colors
mask = cv2.inRange(hsv, lower_val, upper_val)
# apply mask to original image - this shows the green with black blackground
only_green = cv2.bitwise_and(img,img, mask= mask)

# create a black image with the dimensions of the input image
background = np.zeros(img.shape, img.dtype)
# invert to create a white image
background = cv2.bitwise_not(background)
# invert the mask that blocks everything except green -
# so now it only blocks the green area's
mask_inv = cv2.bitwise_not(mask)
# apply the inverted mask to the white image,
# so it now has black where the original image had green
masked_bg = cv2.bitwise_and(background,background, mask= mask_inv)
# add the 2 images together. It adds all the pixel values, 
# so the result is white background and the the green from the first image
final = cv2.add(only_green, masked_bg)

#show image
cv2.imshow("img", final)
cv2.waitKey(0)
cv2.destroyAllWindows()