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/checkpoints/geometry_pose.pth directory."Your/Data/Path" and "Your/Checkpoint/Path" with the appropriate paths:1torchrun --nproc_per_node=1 run_pose_pointcloud.py \
2 --test_dataset "1 @ CustomDataset(split='train', ROOT='Your/Data/Path', resolution=(512,384), seed=1, num_views=8, gt_num_image=0, aug_portrait_or_landscape=False, sequential_input=False)" \
3 --model "AsymmetricMASt3R(pos_embed='RoPE100', patch_embed_cls='ManyAR_PatchEmbed', img_size=(512, 512), head_type='catmlp+dpt', output_mode='pts3d+desc24', depth_mode=('exp', -inf, inf), conf_mode=('exp', 1, inf), enc_embed_dim=1024, enc_depth=24, enc_num_heads=16, dec_embed_dim=768, dec_depth=12, dec_num_heads=12, two_confs=True, desc_conf_mode=('exp', 0, inf))" \
4 --pretrained "Your/Checkpoint/Path" \
5 --test_criterion "MeshOutput(sam=False)" --output_dir "log/" --amp 1 --seed 1 --num_workers 0sh ./visualizer/vis.sh 1@misc{zhang2025flarefeedforwardgeometryappearance,
2 title={FLARE: Feed-forward Geometry, Appearance and Camera Estimation from Uncalibrated Sparse Views},
3 author={Shangzhan Zhang and Jianyuan Wang and Yinghao Xu and Nan Xue and Christian Rupprecht and Xiaowei Zhou and Yujun Shen and Gordon Wetzstein},
4 year={2025},
5 eprint={2502.12138},
6 archivePrefix={arXiv},
7 primaryClass={cs.CV},
8 url={https://arxiv.org/abs/2502.12138},
9}