答案 0 :(得分:0)
使用cv2.bitwise_and
用二进制遮罩遮罩图像。将保留遮罩上的所有白色像素(值为1),而黑色像素(值为0)将被忽略。这是一个例子:
输入图像(左),遮罩(右)
遮罩后的结果
代码
import cv2
import numpy as np
# Load image, create mask, and draw white circle on mask
image = cv2.imread('1.jpeg')
mask = np.zeros(image.shape, dtype=np.uint8)
mask = cv2.circle(mask, (260, 300), 225, (255,255,255), -1)
# Mask input image with binary mask
result = cv2.bitwise_and(image, mask)
# Color background white
result[mask==0] = 255 # Optional
cv2.imshow('image', image)
cv2.imshow('mask', mask)
cv2.imshow('result', result)
cv2.waitKey()
答案 1 :(得分:0)
还有另外两种使用Python Opencv的方式。第一个类似于@nathancy。第二种使用乘法来做掩蔽。 我使用@nathancy提供的图像:
import cv2
import numpy as np
# read image
img = cv2.imread('pink_flower.png')
#mask it - method 1:
# read mask as grayscale in range 0 to 255
mask1 = cv2.imread('pink_flower_mask.png',0)
result1 = img.copy()
result1[mask1 == 0] = 0
result1[mask1 != 0] = img[mask1 != 0]
# mask it - method 2:
# read mask normally, but divide by 255.0, so range is 0 to 1 as float
mask2 = cv2.imread('pink_flower_mask.png') / 255.0
# mask by multiplication, clip to range 0 to 255 and make integer
result2 = (img * mask2).clip(0, 255).astype(np.uint8)
cv2.imshow('image', img)
cv2.imshow('mask1', mask1)
cv2.imshow('masked image1', result1)
cv2.imshow('masked image2', result2)
cv2.waitKey(0)
cv2.destroyAllWindows()
# save results
cv2.imwrite('pink_flower_masked1.png', result1)
cv2.imwrite('pink_flower_masked2.png', result2)
两种方法的结果相同:
答案 2 :(得分:0)
其他答案对我不起作用。那时,我花了很多时间来找到良好的遮罩功能。这是仅用numpy的两个简单答案。
import numpy as np
arr = np.arange(27).reshape(3,3,3) #3 channel image
mask = np.zeros(shape=(3,3))
mask[1,1] = 1 # binary mask
mask_3d = np.stack((mask,mask,mask),axis=0) #3 channel mask
## Answer 1
# Simply multiply the image array with the mask
masked_arr = arr*mask_3d
## Answer 2
# Use the where function in numpy
masked_arr = np.where(mask_3d==1,arr,mask_3d)
#Both answer gives
print(masked_arr)
array([[[ 0., 0., 0.],
[ 0., 4., 0.],
[ 0., 0., 0.]],
[[ 0., 0., 0.],
[ 0., 13., 0.],
[ 0., 0., 0.]],
[[ 0., 0., 0.],
[ 0., 22., 0.],
[ 0., 0., 0.]]])