-
Notifications
You must be signed in to change notification settings - Fork 4
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Have any code to process my own datasets? #1
Comments
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. |
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. |
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 About the hyper-parameters Then you can rewrite the dataloader script data/load_${dataset}.py according to your own dataset. |
No description provided.
The text was updated successfully, but these errors were encountered: