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kafei123456 avatar kafei123456 commented on June 12, 2024

Now, I have new questions. How much memory of GPU is needed. My GPU has 8G and it print out of memory.

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zhuomanliu avatar zhuomanliu commented on June 12, 2024

Now, I have new questions. How much memory of GPU is needed. My GPU has 8G and it print out of memory.

Thanks for your attention to our paper. We ran the experiment on a GPU with 24G memory (RTX3090). The memory usage depends on the settings of N_rand and N_views. It is suggested to decrease these hyper parameters if the GPU memory is limited.

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zhuomanliu avatar zhuomanliu commented on June 12, 2024

May I ask what type of dataset you own? Is it RGB frames/video or depth scans?

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Zhong2017WHU avatar Zhong2017WHU commented on June 12, 2024

May I ask what type of dataset you own? Is it RGB frames/video or depth scans?

I have several datesets for 3D reconstruction. They are all RGB frames and can be aligned using Colmap. So I wonder how to transform my own datasets into the format that this code requires.

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JuliusQv avatar JuliusQv commented on June 12, 2024

May I ask what type of dataset you own? Is it RGB frames/video or depth scans?

I have several datesets for 3D reconstruction. They are all RGB frames and can be aligned using Colmap. So I wonder how to transform my own datasets into the format that this code requires.

same question.

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zhuomanliu avatar zhuomanliu commented on June 12, 2024

May I ask what type of dataset you own? Is it RGB frames/video or depth scans?

I have several datesets for 3D reconstruction. They are all RGB frames and can be aligned using Colmap. So I wonder how to transform my own datasets into the format that this code requires.

For camera settings, we use colmap2nerf.py from Instant-NGP to convert the Colmap outputs (cameras.txt, images.txt) to transforms.json.

As for distance supervisions, you can first load depths obtained by Colmap (*.geometric.bin) and convert them to distance values using the coversion function convert_d(d, scene_info, out='dist') provided in utils/math.py.

About the hyper-parameters sphere_center and radius, they can be computed from the mesh obtained by Colmap. In particular, sphere_center is the center of the mesh, and radius is half the maximum length of the mesh's bounding box.

Then you can rewrite the dataloader script data/load_${dataset}.py according to your own dataset.

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