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import os |
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import torch |
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import tempfile |
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import mast3r.utils.path_to_dust3r |
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from dust3r.model import AsymmetricCroCo3DStereo |
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from mast3r.model import AsymmetricMASt3R |
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from dust3r.demo import get_args_parser as dust3r_get_args_parser |
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from dust3r.demo import main_demo |
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import matplotlib.pyplot as pl |
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pl.ion() |
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torch.backends.cuda.matmul.allow_tf32 = True |
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def get_args_parser(): |
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parser = dust3r_get_args_parser() |
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actions = parser._actions |
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for action in actions: |
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if action.dest == 'model_name': |
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action.choices.append('MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric') |
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parser.prog = 'mast3r demo' |
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return parser |
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if __name__ == '__main__': |
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parser = get_args_parser() |
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args = parser.parse_args() |
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if args.tmp_dir is not None: |
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tmp_path = args.tmp_dir |
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os.makedirs(tmp_path, exist_ok=True) |
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tempfile.tempdir = tmp_path |
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if args.server_name is not None: |
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server_name = args.server_name |
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else: |
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server_name = '0.0.0.0' if args.local_network else '127.0.0.1' |
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if args.weights is not None: |
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weights_path = args.weights |
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else: |
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weights_path = "naver/" + args.model_name |
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try: |
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model = AsymmetricMASt3R.from_pretrained(weights_path).to(args.device) |
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except Exception as e: |
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model = AsymmetricCroCo3DStereo.from_pretrained(weights_path).to(args.device) |
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with tempfile.TemporaryDirectory(suffix='dust3r_gradio_demo') as tmpdirname: |
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if not args.silent: |
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print('Outputing stuff in', tmpdirname) |
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main_demo(tmpdirname, model, args.device, args.image_size, server_name, args.server_port, silent=args.silent) |
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