Comments (3)
ThanTT
commented on September 12, 2024
By the way, I trained VolSDF on the DTU dataset and evaluated the model using eval.py. However, the process is killed and the evaluation fails. I find more than 100% RAM used and my computer has 128G RAM. How to solve the problem?
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lioryariv
commented on September 12, 2024
Hi and sorry for the late reply.
It takes around 8 hours to train a model on a single GPU.
We did not published pre-trained model.
To solve OOM issue you can decrease the grid resolution used for marching cube, or spread/break the grid computation.
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VitorGuizilini-TRI
commented on September 12, 2024
Hi, would it be possible to share a pre-trained model for any of the evaluations?
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Related Issues (20)
- May I ask if this project has the requirement. txt file? If not, can anyone provide one? HOT 2
- Some question on rend_util.py HOT 2
- Some questions about rend_util.py HOT 3
- project page
- Questions about the camera-normalization step
- using multiple image resolution and intrinsics HOT 1
- about sampling implementation. HOT 1
- Preprocess script for the official DTU dataset
- DTU's coordinate system convention
- Hello, is the psnr of each image compared? Thanks you!
- Hi！ Where can I get the supplement?
- Question about normalization HOT 1
- the mesh generated by NeRF in the paper HOT 2
- LaplaceDensity HOT 4
- How to reconstruct texture after generating mesh ? HOT 2
- about implemention of eq (6)
- about training on other datasets HOT 1
- Evaluation on BlendedMVS HOT 2
- Model not training, evaluation generate blank, lower resolution is not handled HOT 1
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