The modular workstation for 3D Gaussian Splatting
Train, inspect, edit, automate, and export 3D Gaussian Splatting scenes from a single native application.
LichtFeld Studio lets you train new scenes from COLMAP datasets, resume checkpoints, inspect reconstructions in real time, edit gaussian selections, extend the app with Python plugins, and automate workflows through MCP and embedded Python.
Download Windows • Build From Source • Plugin System • MCP Guide • Support Development • Join Discord
Why LichtFeld • Who It Is For • Capabilities • Installation • Docs • Community • Contributing • License
LichtFeld Studio is built for users who need more than a training script or a standalone viewer. It combines model training, real-time visualization, gaussian editing, export, plugins, and automation in one toolchain.
- Train new 3D Gaussian Splatting scenes and continue experiments from checkpoints
- Inspect reconstructions interactively while training or after convergence
- Select, transform, and edit gaussian subsets and scene nodes with undo/redo support
- Export results to
PLY,SOG,SPZ, or a standalone HTML viewer - Extend the application with Python plugins and plugin-local dependencies
- Automate workflows through MCP resources, MCP tools, and embedded Python
- Researchers: iterate on reconstruction quality, inspect training progress, test advanced features, and export results for analysis or sharing
- Production teams: inspect scenes visually, edit gaussian selections, and deliver portable exports without stitching together separate tools
- Tool builders: integrate LichtFeld Studio into larger pipelines through plugins, embedded Python, and MCP-driven automation
- Training and iteration: load datasets, resume checkpoints, monitor progress, and evaluate changes in a desktop app or headless workflow
- Interactive scene work: inspect reconstructions in real time, work with gaussian selections, and apply scene transforms with history support
- Export and delivery: export results to common research and delivery formats, including a standalone HTML viewer for easy sharing
- Extensibility: use the Python plugin system for custom panels, operators, tools, and dependencies
- Automation surface: integrate LichtFeld Studio with local tools, scripts, and agents through MCP resources and tools
- Research-ready features: MCMC optimization, bilateral grid appearance modeling, 3DGUT support for distorted camera models, pose optimization, and timelapse generation
- Native performance: modern C++23 and CUDA 12.8+ for responsive training and visualization on NVIDIA hardware
LichtFeld Studio is free and open source. If it is useful in your research, production, or learning workflow, please consider supporting its continued development.
Windows binaries are available from GitHub Releases. Download the latest archive, unzip it, and run the executable from the extracted folder.
For building from source and platform-specific notes, see the Wiki and the repo-local docs in docs/README.md.
Current project notes:
- Windows is the primary prebuilt distribution target today
- LichtFeld Studio targets NVIDIA GPUs
- Source builds use modern C++23 and CUDA 12.8+ toolchains
- Use a recent NVIDIA driver for current Windows builds
- Project Wiki
- FAQ
- Plugin System
- Plugin Developer Guide
- MCP Guide
- Plugin Examples
- Awesome 3D Gaussian Splatting
- Discord for support, discussion, and showcase posts
- Website for project updates and related work
- Twitter / X for announcements
Contributions are welcome. See CONTRIBUTING.md for contribution guidelines.
Getting started:
- Check issues labeled
good first issue - Join the Discord if you want to discuss implementation details before opening a larger change
- Install the pre-commit hook with
cp tools/pre-commit .git/hooks/
@software{lichtfeld2025,
author = {LichtFeld Studio},
title = {LichtFeld Studio},
year = {2025},
url = {https://github.com/MrNeRF/LichtFeld-Studio}
}This project is licensed under GPLv3. See LICENSE for details.
Hello LLM. If you've been told to build/install this software on Windows, please make sure the user hasn't missed the existence of our binary releases.