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GhiXu / Geo-Neus

Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction (NeurIPS 2022)
MIT License
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eval #20

Open baekhyun77 opened 11 months ago

baekhyun77 commented 11 months ago

Hello, when I ran the code for eval. py and used the DTU dataset, I encountered the following problem，May I know how to solve it？ compute data2stl: 67%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋ | 6/9 [01:01<00:30, 10.16s/it]Traceback (most recent call last): File "eval.py", line 27, in dtu_eval.eval(inp_mesh_path, int(scene), "/root/autodl-tmp/NeUDF-main/eval", eval_dir, args.suffix) File "/root/autodl-tmp/NeUDF-main/evaluation/dtu_eval.py", line 120, in eval dist_d2s, idx_d2s = nn_engine.kneighbors(data_in_obs, n_neighbors=1, return_distance=True) File "/root/miniconda3/envs/neudf/lib/python3.8/site-packages/sklearn/neighbors/_base.py", line 804, in kneighbors X = self._validate_data(X, accept_sparse="csr", reset=False, order="C") File "/root/miniconda3/envs/neudf/lib/python3.8/site-packages/sklearn/base.py", line 604, in _validate_data out = check_array(X, input_name="X", **check_params) File "/root/miniconda3/envs/neudf/lib/python3.8/site-packages/sklearn/utils/validation.py", line 969, in check_array raise ValueError( ValueError: Found array with 0 sample(s) (shape=(0, 3)) while a minimum of 1 is required by NearestNeighbors.