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Florian-Barthel / splatviz

Full python interactive 3D Gaussian Splatting viewer for real-time editing and analyzing.
MIT License
1.18k stars 79 forks source link
3d-gaussian-splatting 3dgs analyzing imgui interactive python real-time-editing viewer

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splatviz

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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 it. This enables endless editing and visualization possibilities. You can also evaluate python expressions just after the rendering, allowing you to access and debug the 3D scene just in time. Additionally, you can visualize multiple scenes at the same time by comparing them side by side or in a splitscreen view. Lastly, you can also save renderings, ply files of the current scene and even videos of a 360° rotation around the scene. See some example editings in this video. **NEW UPDATE:** splatviz now supports live tracking of a running 3DGS training: video.

Install

1. Download Clone repository recursively in order to install glm from the diff_gaussian_rasterization package. ```bash git clone https://github.com/Florian-Barthel/splatviz.git --recursive ```
2. Install Create conda environment with conda: ```bash conda env create \ -f environment.yml conda activate gs-view ``` Alternatively, create the environment with micromamba: ```bash micromamba env create \ --file environment.yml \ --channel-priority flexible -y micromamba activate gs-view ```

Launch

ModeDescriptionCommand
Default Mode The default mode loads and renders standard 3DGS scenes stored in ply files or compressed yml files. ```bash python run_main.py ``` or launch with a specified path to look for .ply or .yml files: ```bash python run_main.py --data_path=path/with/ply/files ```
Attach to Training The _attach_ mode allows you to view and edit a running 3DGS training. This works with the default implementation of 3DGS. In order to edit the scene during the training and to view some extra information, follow the simple steps described here: https://github.com/Florian-Barthel/splatviz_network. ```bash python run_main.py --mode=attach ```
Decoder Mode The decoder mode renders human heads generated by 3D GANs from this paper. ```bash python run_main.py \ --mode=decoder \ --data_path=path/with/pkl/files \ --ggd_path=path/to/gaussian_gan_decoder/project ```

In some cases you will have to add this variable so that opengl uses the correct version: export MESA_GL_VERSION_OVERRIDE=3.3

Widgets

🗃️ Load Widget

 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_ files (or _.yml_ files that correspond to compressed gaussian scenes using this compression method). If you have a lot of scenes to chose from, you can also use the **Filter** textfield providing comma separated keywords (eg. _lego,30000,baseline_). 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. You can download some example scenes [here](https://drive.google.com/drive/folders/1RNMis5ibSrl2a87ZX614ZPsHKaY6ams6?usp=sharing). They were created using the gaussian splatting compression method from: https://fraunhoferhhi.github.io/Self-Organizing-Gaussians.

🛠️ Edit Widget

 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 code that you type in this text area will be executed just before the gaussian object is forwarded to the cuda renderer. This means, the editing capabilities are unlimited. As long as the provided code is executable, you can type any kind of python code and also import new libraries. 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. ```python gaussian._scaling = gaussian._scaling * 0 - 8 gaussian._opacity = gaussian._opacity * 0 + 10 self.bg_color[:] = 1 ``` To 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**. ```python 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).

🔍 Eval Widget

 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.

🎥 Camera 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. 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 **. If you were looking down, you will have to press the **Flip** button, since the scene is now upside down.

🎞️ Video Widget

 The video widget creates a video sequence of a full rotation around the current object. Simply define the height of the camera and the rendering resolution. While the video is rendering, the UI is frozen. A loading screen is shown in the terminal output. 🚧This feature is still under construction 🚧. Currently, it is not very intuitive to generate videos, as the camera position is only defined by the Camera Height parameter. This will be changed in the future.

📈 Performance Widget

 In the performance widget, you can track the FPS of the viewer and the FPS of the renderer. You can also specify limits for FPS and enable vertical synchronisation. In the future, there will also be a performance mode which skips some editing and evaluation calculations.

🖥️ Render Widget

 In the render tab, you can specify the rendering resolution (at the moment only squared resolutions) and the rendering mode. Next to RGB, you can also render the image 3D depth and the alpha values.

💾 Save Widget

 To save the .ply file or a rendering of the current (edited) 3D scene press the respective button in the save widget. Those files will be saved under _screenshots or _ply_files. The viewer might be frozen for a short while, after saving a ply file.

⭐ Recent Features

Version 1.1.0

Version 1.0.0

🔭 Future Plans

Contribute

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.

Citation

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}
}

References

This viewer is inspired by the visualizer from Efficient Geometry-aware 3D Generative Adversarial Networks (EG3D).