Image concat

image_concat.py

#!python
import argparse

from PIL import Image
from torchvision import utils, transforms

def parse_args():
    parser = argparse.ArgumentParser("Image concat")
    parser.add_argument("inputs", metavar="input", nargs="+")
    parser.add_argument("output")
    parser.add_argument("--resize", type=str)
    return parser.parse_args()


def main(args):
    inputs = args.inputs
    output = args.output
    size = args.resize

    if size is not None:
        to_tensor = transforms.Compose([
            transforms.ToTensor(),
            transforms.Resize(tuple(map(int, size.split("x")))),
        ])
    else:
        to_tensor = transforms.ToTensor()

    img_tensors = []
    for input_file in inputs:
        img = Image.open(input_file)
        img = to_tensor(img)
        img_tensors.append(img)

    utils.save_image(img_tensors, output, ncol=1)


if __name__ == "__main__":
    args = parse_args()
    main(args)

Example usage:

./image_concat.py --resize 256x256 hazelnut.png leather.png out.png

Result:

Image from the MVTec-AD dataset