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| #!/usr/bin/env python3 | |
| # Copyright (C) 2024-present Naver Corporation. All rights reserved. | |
| # Licensed under CC BY-NC-SA 4.0 (non-commercial use only). | |
| # | |
| # -------------------------------------------------------- | |
| # dust3r gradio demo executable | |
| # -------------------------------------------------------- | |
| import os | |
| import torch | |
| import tempfile | |
| from dust3r.model import AsymmetricCroCo3DStereo | |
| from dust3r.demo import get_args_parser, main_demo | |
| import matplotlib.pyplot as pl | |
| pl.ion() | |
| torch.backends.cuda.matmul.allow_tf32 = True # for gpu >= Ampere and pytorch >= 1.12 | |
| if __name__ == '__main__': | |
| parser = get_args_parser() | |
| args = parser.parse_args() | |
| if args.tmp_dir is not None: | |
| tmp_path = args.tmp_dir | |
| os.makedirs(tmp_path, exist_ok=True) | |
| tempfile.tempdir = tmp_path | |
| if args.server_name is not None: | |
| server_name = args.server_name | |
| else: | |
| server_name = '0.0.0.0' if args.local_network else '127.0.0.1' | |
| if args.weights is not None: | |
| weights_path = args.weights | |
| else: | |
| weights_path = "naver/" + args.model_name | |
| model = AsymmetricCroCo3DStereo.from_pretrained(weights_path).to(args.device) | |
| # dust3r will write the 3D model inside tmpdirname | |
| with tempfile.TemporaryDirectory(suffix='dust3r_gradio_demo') as tmpdirname: | |
| if not args.silent: | |
| print('Outputing stuff in', tmpdirname) | |
| main_demo(tmpdirname, model, args.device, args.image_size, server_name, args.server_port, silent=args.silent) | |