python OpenCV - 添加 alpha 通道到 RGB 图像

Question

What is the best way to convert RGB image to RGBA in python using opencv?

Let's say I have one array with shape

(185, 198, 3) - it is RGB

and the other is alpha mask with shape (185, 198)

How to merge them and save to file?

Answer 1

With opencv3, this should work:

Python

# First create the image with alpha channel
rgba = cv2.cvtColor(rgb_data, cv2.COLOR_RGB2RGBA)

# Then assign the mask to the last channel of the image
rgba[:, :, 3] = alpha_data

C++

# First create the image with alpha channel
cv::cvtColor(rgb_data, rgba , cv::COLOR_RGB2RGBA);

# Split the image for access to alpha channel
std::vector<cv::Mat>channels(4);
cv::split(rgba, channels);

# Assign the mask to the last channel of the image
channels[3] = alpha_data;

# Finally concat channels for rgba image
cv::merge(channels, 4, rgba);

Answer 2

You may use cv2.merge() to add the alpha channel to the given RGB image, but first you need to split the RGB image to R, G and B channels, as per the documentation :

Python: cv2.merge(mv[, dst])

• mv – input array or vector of matrices to be merged; all the matrices in mv must have the same size and the same depth.

And this can be done as:

b_channel, g_channel, r_channel = cv2.split(img)

alpha_channel = np.ones(b_channel.shape, dtype=b_channel.dtype) * 50 #creating a dummy alpha channel image.

img_BGRA = cv2.merge((b_channel, g_channel, r_channel, alpha_channel))

Answer 3

Here is an another simple example using Grabcut, it helps to get the right order of channels when saving the image on disk vs pyplot .

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

img = cv2.imread('image.jpg')

mask = np.zeros(img.shape[:2], np.uint8)
bgdModel = np.zeros((1,65), np.float64)
fgdModel = np.zeros((1,65), np.float64)
rect = (50, 50, 450, 290)

# Grabcut 
cv2.grabCut(img, mask, rect, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)

r_channel, g_channel, b_channel = cv2.split(img) 
a_channel = np.where((mask==2)|(mask==0), 0, 255).astype('uint8')  

img_RGBA = cv2.merge((r_channel, g_channel, b_channel, a_channel))
cv2.imwrite("test.png", img_RGBA)

# Now for plot correct colors : 
img_BGRA = cv2.merge((b_channel, g_channel, r_channel, a_channel))

plt.imshow(img_BGRA), plt.colorbar(),plt.show()

Answer 4

Since OpenCV images are just Numpy arrays, you can do this in one-line, nice and fast with Numpy. So here is the setup code:

import numpy as np

# We'll synthesise a random image and a separate alpha channel full of 128 - semitransparent
im    = np.random.randint(0,256,(480,640,3), dtype=np.uint8)
alpha = np.full((480,640), 128, dtype=np.uint8)

And here is the solution which is simply to stack the alpha channel onto the image in the "depth" axis, hence dstack() :

result = np.dstack((im, alpha))

Answer 5

I'll post here my answer in C++ since it may be helpful to others (there are already enough answers in python):

  std::vector<cv::Mat> matChannels;
  cv::split(mat, matChannels);
  
  // create alpha channel
  cv::Mat alpha(...);
  matChannels.push_back(alpha);

  cv::merge(matChannels, dst);

Answer 6

import cv2
import numpy as np
import skimage.exposure



path_input_image="./input_image.png"


input_image = cv2.imread(path_input_image2, cv2.IMREAD_UNCHANGED)


input_image_alphachann = np.full((input_image.shape[0],input_image.shape[1]), 128, dtype=np.uint8)

output_image = np.dstack((input_image, input_image_alphachann))


print(input_image.shape)
print(output_image.shape)
#(400, 200, 3); 3 channell rgb
#(400, 200, 4); 4c channel rgba



print(input_image.dtype)
print(output_image.dtype)
# uint8




path_output_image=path_input_image+'.alpha.png'
cv2.imwrite(path_output_image, output_image)

Answer 7

如何在打开的简历中添加Alpha Cheel或将其透明度值设置为255