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Running
on
Zero
| #!/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). | |
| # | |
| # -------------------------------------------------------- | |
| # gradio demo executable | |
| # -------------------------------------------------------- | |
| import os | |
| import torch | |
| import tempfile | |
| from contextlib import nullcontext | |
| from mast3r.demo import get_args_parser, main_demo | |
| from mast3r.model import AsymmetricMASt3R | |
| from mast3r.utils.misc import hash_md5 | |
| import mast3r.utils.path_to_dust3r # noqa | |
| from dust3r.demo import set_print_with_timestamp | |
| 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() | |
| set_print_with_timestamp() | |
| 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 = AsymmetricMASt3R.from_pretrained(weights_path).to(args.device) | |
| chkpt_tag = hash_md5(weights_path) | |
| def get_context(tmp_dir): | |
| return tempfile.TemporaryDirectory(suffix='_mast3r_gradio_demo') if tmp_dir is None \ | |
| else nullcontext(tmp_dir) | |
| with get_context(args.tmp_dir) as tmpdirname: | |
| cache_path = os.path.join(tmpdirname, chkpt_tag) | |
| os.makedirs(cache_path, exist_ok=True) | |
| main_demo(cache_path, model, args.device, args.image_size, server_name, args.server_port, silent=args.silent, | |
| share=args.share, gradio_delete_cache=args.gradio_delete_cache) | |