This interactive viewer allows you to display and edit 3D Gaussian Splatting scenes in real time. By using the python GUI library (pyimgui) we can directly manipulate the Gaussian python object just before rendering. This enables endless editing and visualization possibilities.
Additionally, you can visualize multiple scenes at the same time by comparing them side by side or in a splitscreen view or evaluate python expressions on the resulting scene.
See some example editings in this video.
NEW UPDATE: splatviz supports rendering the output of 3D GANs and allows for exploring the latent space.
Clone repository recursively in order to install glm from the diff_gaussian_rasterization package.
git clone https://github.com/Florian-Barthel/splatviz.git --recursiveCreate environment with conda:
conda env create -f environment.yml
conda activate gs-viewAlternatively, use micromamba:
micromamba env create --file environment.yml --channel-priority flexible -y
micromamba activate gs-viewIn some cases you will have to add this variable so that opengl uses the correct version:
export MESA_GL_VERSION_OVERRIDE=3.3
The default mode loads and renders standard 3DGS scenes stored in ply files or compressed yml files.
python run_main.py --data_path=parent/path/with/ply/filesDownload example scenes here.
Attaches to a running training (local or remote). By default the splatviz listens to the local host 127.0.0.1:6007, which is used by 3DGS. Modify the host and port with --host and --port.
python run_main.py --mode=attachTo enable editing the scene during training, follow the steps described here.
The GAN mode renders 3D human heads generated by CGS-GAN. First check out the cgs-gan repository: https://github.com/fraunhoferhhi/cgs-gan and download the network checkpoints: ffhq_512.pkl, ffhq_1024.pkl or ffhq_2048.pkl. Then run the main file in gan mode:
python run_main.py --mode=gan --data_path=dir/with/network_pkl/files --gan_path=path/to/cgs-gan/project/rootRunning splatviz in GAN mode (using --mode=gan), allows you to render and manipulate the results of CGS-GAN. Simply drag the white dot across the 2D plane to interpolate in the latent space of the GAN.
Once you run the run_main.py file, the viewer will directly load the first scene that is found in the data
directory you have specified. You can change the scene by clicking the Browse button. You will be displayed a list
of available .ply or .yml files. If you have a lot of
scenes, you can also use the Filter textfield and provide comma separated keywords (eg. lego,30000).
You will then only see those scenes that contain all keywords.
Additionally, you can also view multiple 3D scenes at once. Simply click Add Scene, which loads the same scene as
before and then change the respective scene to another .ply file using the new browse button. The scenes are either
rendered next to each other or in a split screen mode when activating the Splitscreen checkbox.
The edit widget is the core functionality of this 3D viewer. It allows for real time editing of the gaussian python object during runtime. The python code that you type in this text area will be executed just before rendering. An example could look like this, where all scales are set to -8 (before activating with exp()) and all opacity values are set to 10 (before activating with sigmoid()), while also the background is set to 1, which corresponds to white.
gaussian._scaling = gaussian._scaling * 0 - 8
gaussian._opacity = gaussian._opacity * 0 + 10To enable smooth editing transitions, you can create sliders (press Add Slider) which you can access in the editor text by typing slider.name (eg. slider.x). An example could look as follows. Here, we create a boolean mask that filters all gaussians that are smaller than the value stored in slider.x.
mask = torch.linalg.norm(gaussian._scaling, dim=-1) < slider.x
gaussian._xyz = gaussian._xyz[mask]
gaussian._rotation = gaussian._rotation[mask]
gaussian._scaling = gaussian._scaling[mask]
gaussian._opacity = gaussian._opacity[mask]
gaussian._features_dc = gaussian._features_dc[mask]
gaussian._features_rest = gaussian._features_rest[mask]Lastly, you can save and load presets of code snippets so that you don't have to type the same code again after
closing the application. Those presets are stored in a .json file (presets.json).
The evaluate widget can be used to debug the gaussian splatting object. By typing python code, which is executed after the rendering, you can access any variable from the rendering context and visualize them in a histogram. Some useful variables might be:
- gaussian
- render
- render_cam
- self
You can also access variables that you have defined in the editor of the Edit Widget.
In the camera widget you can define the type and parameters of the camera. Most importantly, you can choose between the two modes Orbit and WASD. In Orbit mode, the camera is looking at a specific point in 3D space, and you control the pitch and yaw of the camera rotating on a sphere around that point by dragging with the mouse over the rendered view. And in WASD mode, you fly through the scene using the mouse and the WASD keys similar to the camera controls in Unity.
Important: If the loaded scene is rotated incorrectly, you can adjust that by steering the camera so that it is looking straight up or down. Then set the up-vector to the current viewing direction by pressing **Set Current Direction **.
Version 1.2.0
- 2025-05-26: Added GAN mode.
Version 1.1.0
- 2024-08-12: Added a new Training Widget to inspect live training stats and to pause training
- 2024-08-11: Attach to a running 3DGS training
- 2024-08-10: Refactor rendering class for easier addition of new renderer
- 2024-08-07: Better Mouse Control (translate with middle mouse button)
- 2024-08-05: Allow editing of existing sliders
- 2024-07-30: Store slider values in presets
- 2024-07-28: New Performance Widget
- 2024-07-28: Editor now highlights special variables (gs, self, slider) and gives tooltips
Version 1.0.0
- 2024-07-12: Rebuild the whole application with imgui_bundle
- 2024-07-05: Compare two or more Gaussian Splatting scenes side by side
- Test other 3DGS render for OSX support
- Improve the Video Widget
- Tutorial for coding new widgets or renderer
You are more than welcome to add further functionality or a better design to this interactive viewer! The main goal is to create an easy-to-use tool that can be applied for debugging and for understanding 3D Gaussian Splatting objects. For reformating code please use black with --line-length 120.
If you find this viewer useful, please consider citing our work:
@misc{barthel2024gaussian,
title={Gaussian Splatting Decoder for 3D-aware Generative Adversarial Networks},
author={Florian Barthel and Arian Beckmann and Wieland Morgenstern and Anna Hilsmann and Peter Eisert},
year={2024},
eprint={2404.10625},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
This viewer is inspired by the visualizer from Efficient Geometry-aware 3D Generative Adversarial Networks (EG3D).
- GUI: pyimgui and imgui_bundle which are python wrappers for the c++ library ImGUI
- Original code base: EG3D
- 3DGS: 3D Gaussian Splatting
- Compressing 3DGS scenes: Compact 3D Scene Representation via Self-Organizing Gaussian Grids
- 3DGS Rasterizer with depth and alpha: Diff rasterizer with depth and alpha
