python OpenCV - add alpha channel to RGB image

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);

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))

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))

python OpenCV - add alpha channel to RGB image

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