init
Browse files- .gitmodules +3 -0
- app.py +36 -0
- mast3r +1 -0
- requirements.txt +15 -0
.gitmodules
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[submodule "mast3r"]
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path = mast3r
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url = https://github.com/naver/mast3r
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app.py
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# Copyright (C) 2024-present Naver Corporation. All rights reserved.
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# Licensed under CC BY-NC-SA 4.0 (non-commercial use only).
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#
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# --------------------------------------------------------
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# masst3r demo
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# --------------------------------------------------------
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import os
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import sys
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import os.path as path
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import torch
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import tempfile
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HERE_PATH = path.normpath(path.dirname(__file__)) # noqa
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MASt3R_REPO_PATH = path.normpath(path.join(HERE_PATH, './mast3r')) # noqa
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sys.path.insert(0, MASt3R_REPO_PATH) # noqa
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from mast3r.demo import main_demo
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from mast3r.model import AsymmetricMASt3R
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from mast3r.utils.misc import hash_md5
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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 # for gpu >= Ampere and pytorch >= 1.12
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batch_size = 1
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weights_path = "naver/" + 'MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric'
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device = 'cuda' if torch.cuda.is_available() else 'cpu'
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model = AsymmetricMASt3R.from_pretrained(weights_path).to(device)
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chkpt_tag = hash_md5(weights_path)
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# mast3r will write the 3D model inside tmpdirname/chkpt_tag
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with tempfile.TemporaryDirectory(suffix='_mast3r_gradio_demo') as tmpdirname:
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cache_path = os.path.join(tmpdirname, chkpt_tag)
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os.makedirs(cache_path, exist_ok=True)
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main_demo(tmpdirname, model, device, 512, server_name=None, server_port=None, silent=True, share=None)
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mast3r
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Subproject commit f64a2f2a44834824dc1d34f445ad747cbfc4f1e2
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requirements.txt
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scikit-learn
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pillow-heif
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torch
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torchvision
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roma
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gradio
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matplotlib
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tqdm
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opencv-python
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scipy
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einops
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trimesh
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tensorboard
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pyglet<2
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huggingface-hub[torch]>=0.22
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