Discarding alpha channel from images stored as Numpy arrays

Question

I load images with numpy/scikit. I know that all images are 200x200 pixels.

When the images are loaded, I notice some have an alpha channel, and therefore have shape (200, 200, 4) instead of (200, 200, 3) which I expect.

Is there a way to delete that last value, discarding the alpha channel and get all images to a nice (200, 200, 3) shape?

Assuming, you are using `Image.open()` you can discard the alpha value by doing `Image.open().convert('RGB')`. Hope this helps someone in the future. — Pramesh Bajracharya, Feb 11 '19 at 11:08

score 98 · Accepted Answer · answered Mar 09 '16 at 20:53

98

Just slice the array to get the first three entries of the last dimension:

image_without_alpha = image[:,:,:3]

answered Mar 09 '16 at 20:53

Carsten

I think this will reduce the quality of the image? – Aleksandar Jovanovic Sep 19 '17 at 11:33
14

@AleksandarJovanovic do you precisely know what you mean by "quality of the image"? Dropping alpha removes information about transparency of pixels but does not influence other information (e.g., color). – dolphin Nov 25 '17 at 20:42

score 3 · Answer 2 · answered Apr 15 '21 at 09:45

scikit-image builtin:

from skimage.color import rgba2rgb
from skimage import data
img_rgba = data.logo()
img_rgb = rgba2rgb(img_rgba)

2 Answers2