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| File | Description | Size |
|---|---|---|
unified.safetensors | Main model (encoder + decoder) | ~1.3 GB |
retrieval.safetensors | Retrieval head for SfM | ~2 MB |
codebook.pkl | Codebook for image retrieval | ~256 MB |
1from mast3r_runtime import load_model
2
3model = load_model("aedelon/mast3r-vit-large")
4points, descriptors = model.forward(image1, image2)1from huggingface_hub import hf_hub_download
2from safetensors.torch import load_file
3import pickle
4
5# Load main model
6unified = load_file(hf_hub_download("Aedelon/mast3r-vit-large-fp16", "unified.safetensors"))
7
8# Load retrieval head
9retrieval = load_file(hf_hub_download("Aedelon/mast3r-vit-large-fp16", "retrieval.safetensors"))
10
11# Load codebook (pickle)
12codebook_path = hf_hub_download("Aedelon/mast3r-vit-large-fp16", "codebook.pkl")
13with open(codebook_path, "rb") as f:
14 codebook = pickle.load(f)1from mast3r.model import AsymmetricMASt3R
2from safetensors.torch import load_file
3
4weights = load_file("unified.safetensors")
5model = AsymmetricMASt3R()
6model.load_state_dict(weights)1# Per image pair:
2{
3 "pts3d_1": Tensor[B, H, W, 3], # 3D points from view 1
4 "pts3d_2": Tensor[B, H, W, 3], # 3D points from view 2
5 "desc_1": Tensor[B, H, W, D], # Descriptors from view 1
6 "desc_2": Tensor[B, H, W, D], # Descriptors from view 2
7 "conf_1": Tensor[B, H, W], # Confidence map view 1
8 "conf_2": Tensor[B, H, W], # Confidence map view 2
9}1@article{leroy2024mast3r,
2 title={Grounding Image Matching in 3D with MASt3R},
3 author={Leroy, Vincent and Cabon, Yohann and Revaud, J{\'e}r{\^o}me},
4 journal={arXiv preprint arXiv:2406.09756},
5 year={2024}
6}
7
8@inproceedings{wang2024dust3r,
9 title={DUSt3R: Geometric 3D Vision Made Easy},
10 author={Wang, Shuzhe and Leroy, Vincent and Cabon, Yohann and Chidlovskii, Boris and Revaud, J{\'e}r{\^o}me},
11 booktitle={CVPR},
12 year={2024}
13}