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VITA-Group / LightGaussian

"LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS", Zhiwen Fan, Kevin Wang, Kairun Wen, Zehao Zhu, Dejia Xu, Zhangyang Wang
https://lightgaussian.github.io/
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Error about quantizing 3DGS checkpoint #15

Closed Aeson-Hsu closed 5 months ago

Aeson-Hsu commented 5 months ago

Hi, I get an error when I run vectree.py.

================== Print Info ================== Input_feats_shape: torch.Size([1554770, 62]) VQ_feats_shape: torch.Size([1554770, 27]) SH_degree: 2 Quantization_ratio: 0.6 Add_important_score: True Codebook_size: 8192 ================================================ IS_percent: tensor(0.7985) 100%|██████████| 1000/1000 [01:00<00:00, 16.41it/s]

=============== Start vector quantize =============== 100%|██████████| 190/190 [00:01<00:00, 186.61it/s] updating: ../vectree/output/bicycle/extreme_saving/ (stored 0%) updating: ../vectree/output/bicycle/extreme_saving/metadata.npz (deflated 12%) updating: ../vectree/output/bicycle/extreme_saving/non_vq_feats.npz (deflated 0%) updating: ../vectree/output/bicycle/extreme_saving/xyz.npz (deflated 0%) updating: ../vectree/output/bicycle/extreme_saving/non_vq_mask.npz (deflated 0%) updating: ../vectree/output/bicycle/extreme_saving/other_attribute.npz (deflated 0%) updating: ../vectree/output/bicycle/extreme_saving/codebook.npz (deflated 0%) updating: ../vectree/output/bicycle/extreme_saving/vq_indexs.npz (deflated 0%) Size = 70.69165706634521 MB

==================== Load saved data & Dequantize ==================== Traceback (most recent call last): File "/home/zxq/MachineLearning/SLAM/3DGS/LightGaussian/vectree/vectree.py", line 224, in vq.dequantize() File "/home/zxq/MachineLearning/SLAM/3DGS/LightGaussian/vectree/vectree.py", line 215, in dequantize write_ply_data(dequantized_feats.cpu().numpy(), self.ply_path, self.sh_dim) File "/home/zxq/MachineLearning/SLAM/3DGS/LightGaussian/vectree/utils.py", line 101, in write_ply_data elements[:] = list(map(tuple, feats)) ValueError: could not assign tuple of length 62 to structure with 41 fields.

I found that the shape of feats is [1554770, 62] and the dtype of elements is [1554770, 41], which caused the error. Besides, elementsdtype is defined by dtype_full：

dtype_full = [(attribute, 'f4') for attribute in construct_list_of_attributes()]

So, I'd like to know the reason why the demensions between dtype_full and feats is inconsistent. Thanks in advance！

Kevin-2017 commented 5 months ago

Hi, Thank you for your interest in our work :) This inconsistency is likely caused by an incorrect SH degree setting. You might want to add the argument "--sh_degree 3" for python vectree/vectree.py if you are using the default SH degree for 3DGS.