A simple image concat script
← Posts & Notes ·
21/05/2021
·
1 minute
Usage
./image_concat.py --resize 256x256 hazelnut.png leather.png out.png
Result
.](https://user-images.githubusercontent.com/9824244/119120482-9cfbb100-ba2c-11eb-98eb-a66665406deb.png)
Source
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| #!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) |