Pad portrait images that do not fit for instagram.

portrait_ig_pad.py

import imageio
import numpy as np
import sys
import os
import imagesize


if __name__ == '__main__':
    assert len(sys.argv) >= 2, 'must supply at least 1 file argument'

    WIDTH = 1080
    HEIGHT = 1350
    ASPECT_RATIO = HEIGHT / WIDTH

    for i, path in enumerate(sys.argv[1:]):
        try:
            # get image size
            w, h = imagesize.get(path)
            aspect_ratio = h / w
            if aspect_ratio <= ASPECT_RATIO:
                print(f'\033[90m{i}: SKIPPING... {h}x{w} (~{HEIGHT}x{int(HEIGHT/h*w)}) {path=}\033[0m')
                continue

            # load image
            img = imageio.imread(path)
            h, w = img.shape[:2]

            # compute new image size
            new_w = int(np.ceil(h / ASPECT_RATIO))
            new_size = (h, new_w, *img.shape[2:])
            offset = (new_w - w) // 2

            # create new image
            new_img = np.full(new_size, 255, dtype=np.uint8)
            new_img[:, offset:offset+w, :] = img

            # write image to disk
            name, ext = os.path.splitext(path)
            new_path = f'{name}_padded{ext}'
            imageio.imsave(new_path, new_img, quality=90)

            print(f'{i}: Saved: {h}x{w} (~{HEIGHT}x{int(HEIGHT/h*w)}) -> {h}x{new_w} (~{HEIGHT}x{int(HEIGHT/h*new_w)}) {new_path=}')

        except Exception as e:
            print(f'{i}: Failed to process image {path=} with error {e=}')

Only processes images that need padding, does not overwrite original images & skips previously padded images.

Example usage with wildcard:

python portrait_ig_pad.py image_folder/IMG*.jpg