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?
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))
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With