minGS

This is a minimalistic refactoring of the original 3D Gaussian splatting codebase that follows PyTorch conventions and allow for easy customization and extension, based on the original 3DGS official repository.

It is meant for researchers who want to experiment with 3D Gaussian splatting and need a clean and easy-to-understand codebase to start from.

Installation

Assuming you have CUDA SDK installed, you can view or directly run install.sh to install the required dependencies and compile the CUDA kernels.

Examples

Original training pipeline

example.py shows how to train a 3DGS model using the original training pipeline.

Minimal Custom Training Example

To customize the pipeline GaussianModel can be used just like any other PyTorch model and the training loop can be written from scratch. Below is a minimal example:

import torch
from gs.core.GaussianModel import GaussianModel
from gs.helpers.loss import l1_loss
from gs.io.colmap import load

cameras, pointcloud = load('your_dataset/')
model = GaussianModel.from_point_cloud(pointcloud).cuda()
optimizer = torch.optim.Adam(model.parameters(), lr=0.001, eps=1e-15)

for i in range(5000):

    camera = cameras[i % len(cameras)]
    rendered = model.forward(camera)

    loss = l1_loss(rendered, camera.image)
    loss.backward()

    optimizer.step()
    optimizer.zero_grad(set_to_none=True) 

    torch.cuda.empty_cache()

Structure

The codebase is structured as follows:

gs/: The Gaussian splatting module.
- core/: Core data structures and functions for rendering 3DGS models
  - BaseCamera.py: Base class that represents a camera used for training 3DGS models
  - BasePointCloud.py: Base class for point clouds used for initializing 3DGS models
  - GaussianModel.py: 3DGS model refactored as a nn.Module. Use forward with a camera to render the model
- io/: Functions for importing and exporting image and point cloud data
  - colmap/: Functions for importing COLMAP reconstructions into BaseCamera and BasePointCloud compliant objects
- trainers/: Training scripts for 3DGS models
  - basic/: Re-implementations of the original training script
- helpers/: General functions for rendering and training 3DGS models

Todo

.ply import/export
Live visualization using nerfstudio's viser module

zoonono / minGS