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Visualization and Mesh is not same #1

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Talegqz opened this issue Aug 24, 2023 · 4 comments
Closed

Visualization and Mesh is not same #1

Talegqz opened this issue Aug 24, 2023 · 4 comments

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@Talegqz
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Talegqz commented Aug 24, 2023

Thanks for your excellent work!

I found some config bug and fixed it, then I ran it with my own data. I found that the visualization is very nice, but the mesh quality is not reasonable.

Could you please explain it or help me improve it?

Thanks for your help.

Snipaste_2023-08-24_11-33-33 Snipaste_2023-08-24_11-33-43
@Colmar-zlicheng
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Colmar-zlicheng commented Aug 24, 2023 •
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Hi, that is because the resolution for reconstruction, the default value is 512. You can set it higher when doing evaluation. I think you can set it to 1024 to extract a more refined mesh, while it will take more time for inference.

python evaluation.py -rr 1024 --(other args)

@Talegqz
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Talegqz commented Aug 24, 2023

Thanks for your help！

@Talegqz Talegqz closed this as completed Aug 24, 2023
@Colmar-zlicheng Colmar-zlicheng pinned this issue Sep 20, 2023
@xsl316
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xsl316 commented Jul 20, 2024 •
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Thanks for your excellent work!
How to train your own dataset, including how to preprocess your own data！
Thanks for your help.

@Colmar-zlicheng
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You can use the command below to train the IHO-Video dataset, please refer to readme for details.

python train.py -g 0 --cfg config/Color_NeuS_iho.yml -obj ghost_bear --exp_id Color_NeuS_iho_ghost_bear

For data preprocessing, we use colmap to obtain camera poses and TrackAnything to obtain image masks.

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@Talegqz @Colmar-zlicheng @xsl316