Comments (6)
Hi, thanks for your interest.
- Different epochs are set for different datasets. The configuration can be seen in
configs/*.yaml
.
For 3DMatch/3DLoMatch, max_epoch is set 40, which can be seen in https://github.com/zhulf0804/NgeNet/blob/d4917f22e55195132ec6fc602554102d321ce4b5/configs/threedmatch.yaml#L46 - The low training speed is due to the correspondences construction operation (shown below) on CPU. For example, we trained 3DMatch on one RTX 3090 card using about 40 hours.
https://github.com/zhulf0804/NgeNet/blob/d4917f22e55195132ec6fc602554102d321ce4b5/utils/o3d.py#L75-L88
Best regards.
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Thanks for such a quick answer!
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Hello, when I evaluate and visualize, the process is killed when it reaches 14%. It may be a memory overflow problem. Is there any good solution?my graphics card is titan
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Hello,
What's your GPU memory size ? I didn't record the runtime memory size before, but GTX 1080Ti is enough for me.
One way your can try is to use torch.cuda.empty_cache()
after each iteration.
Best.
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Hi,
python eval_3dmatch.py --benchmark 3DMatch --data_root your_path/indoor --checkpoint your_path/3dmatch.pth --saved_path work_dirs/3dmatch
menas using cuda for evaluation.python eval_3dmatch.py --benchmark 3DMatch --data_root your_path/indoor --checkpoint your_path/3dmatch.pth --saved_path work_dirs/3dmatch --vis
menas using cuda for visualization.python eval_3dmatch.py --benchmark 3DMatch --data_root your_path/indoor --checkpoint your_path/3dmatch.pth --saved_path work_dirs/3dmatch --vis --no_cuda
menas visualizing on cpu.
Besides, you may add torch.cuda.empty_cache()
in line 199
as follows:
https://github.com/zhulf0804/NgeNet/blob/d4917f22e55195132ec6fc602554102d321ce4b5/eval_3dmatch.py#L194-L198
Best.
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Related Issues (13)
- What‘s the meaning of “consistent voting”? HOT 2
- How long it takes to train the model HOT 1
- The question about the loss function
- About creating my own data set HOT 2
- re-training 3dmatch HOT 1
- The trainning error HOT 1
- No such file or directory: './3dmatch/test/7-scenes-redkitchen/cloud_bin_1.pth' HOT 4
- About how to understand the meaning of this comparison in this paper? HOT 4
- Test and visualize on custom data HOT 7
- ERROR: Unexpected segmentation fault encountered in worker. HOT 2
- Segmentation fault when evaluate 3DMatch HOT 2
- Perfomance HOT 5
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