Numpy/Scipy with masks and RGB images

Question

I\'m trying to create a mask for an RGB image using skikit learn. I want to create a mask selecting only pixels which are equal to [0,10,0], ie 10 on green channel. And then

Answer 1

You could get that 2D mask with ALL reduction along the last axis -

mask = (image == [0,10,0]).all(-1)

Then, image[mask] would be (N,3) shaped array of only [0,10,0] values, where N is number of pixels which were of that specific RGB triplet.

So, the step(s) to using mask to show the masked image or overlay would depend on the viewer.

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For an in-situ edit in the image, such that we would mask out everything that's not of that specific RGB triplet, we could multiply with the mask -

image *= mask[...,None]

Or create a copy with a choosing mechanism using np.where -

image_overlayed = np.where(mask[...,None], image, 0)

To get a 3D mask (if that's what needed with viewer), we could replicate the mask along the channels as well -

np.repeat(mask[...,None],3,axis=2)