Discarding alpha channel from images stored as Numpy arrays

Question

I load images with numpy/scikit. I know that all images are 200×200 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?

Asked By: cwj

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Source

Answer 1

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

image_without_alpha = image[:,:,:3]

Answered By: Carsten

Answer 2

scikit-image builtin:

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

https://scikit-image.org/docs/dev/user_guide/transforming_image_data.html#conversion-from-rgba-to-rgb-removing-alpha-channel-through-alpha-blending
https://scikit-image.org/docs/dev/api/skimage.color.html#rgba2rgb

Answered By: Kailo

Answer 3

Use PIL.Image to remove the alpha channel

from PIL import Image
import numpy as np

img = Image.open("c:>path_to_image")
img = img.convert("RGB") # remove alpha
image_array = np.asarray(img) # converting image to numpy array
print(image_array.shape)
img.show()

If images are in numpy array to convert the array to Image use Image.fromarray to convert array to Image

pilImage = Image.fromarray(numpy_array)

Answered By: Udesh

Answer 4

If you need higher speed, you can use cvtColor in cv2 (openCV):

img_RGB = cv2.cvtColor(img_RGBA, cv2.COLOR_RGBA2RGB);

It took 1/4 time of numpy slice method.

Answered By: phnghue

Discarding alpha channel from images stored as Numpy arrays

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