I'm trying to resize a batch of grayscale images that are 256 x N pixels (N varies, but is always ≤256).

My intention is to downscale the images.

The resize would have to output a square (1:1) image, with:

• resized image centered vertically
• aspect ratio maintained
• remaining pixels rendered black

Visually this would be the desired result:

I have tried creating a numpy zeroes matrix with the target size (e.g. 200 x 200) but have not been able to paste the resized image into its vertical center.

Any suggestions using cv2, PIL or numpy are welcome.

You can use Pillow to accomplish that:

Code:

from PIL import Imagedef make_square(im, min_size=256, fill_color=(0, 0, 0, 0)):x, y = im.sizesize = max(min_size, x, y)new_im = Image.new('RGBA', (size, size), fill_color)new_im.paste(im, (int((size - x) / 2), int((size - y) / 2)))return new_im

Test Code:

test_image = Image.open('hLarp.png')
new_image = make_square(test_image)
new_image.show()

For a white background you can do:

new_image = make_square(test_image, fill_color=(255, 255, 255, 0))

Result: