GeezerVison

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 (Portal) • Build From Source • Python API and Plugins • MCP Guide • Support Development • Join Discord

See It in Action • Why LichtFeld • Who It Is For • Capabilities • Installation • Docs • Community • Contributing • License

▶ Watch on YouTube — Everything LichtFeld Studio can do today

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, and timelapse generation
• Native performance: modern C++23 and CUDA 12.8+ for responsive training and visualization on NVIDIA hardware

In the Training panel, enable Sparsity and set Target Gaussians under Sparsity Settings. The CLI equivalent is:

--enable-sparsity --popspa-target-count 256000

POPSpa runs after regular training: contribution scoring, an intermediate prune, sparse optimization, an exact final prune, and recovery. It supports FastGS and the bundled gsplat/GUT backend. The target must fit the active model count and retain all frozen Gaussians. Phase lengths and advanced controls are available as popspa_* settings in the UI, JSON, and Python. The equations follow KissGsVanilla (Apache-2.0), implemented independently in LichtFeld Studio's C++/CUDA.

LichtFeld Studio is free and open source. If it is useful in your research, production, or learning workflow, please consider supporting its continued development.

Prebuilt Windows binaries are distributed through the LichtFeld Portal. Access is paid: you register and make a donation of your choosing, which directly funds development, and in return you get the current release plus daily builds. Download the archive, unzip it, and run the executable. Binaries are not published on GitHub Releases.

Building from source is free for everyone under GPLv3, on Windows and Linux.

For building from source and platform-specific notes, see the Wiki. Developers can find contributor setup and test commands in the repo-local source build guide.

Current project notes:

• Windows is the primary prebuilt distribution target today
• LichtFeld Studio requires an NVIDIA GPU with compute capability 7.5 or newer (GTX 16-series, RTX 20-series and up). GTX 10-series and older, AMD, and Intel GPUs are not supported
• NVIDIA driver 570 or newer is required (CUDA 12.8+)
• Source builds use modern C++23 and CUDA 12.8+ toolchains

• Project Wiki
• FAQ
• Source Build Guide
• Python API and Plugins
• 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
• YouTube for video tours and feature demos

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
• Follow the source build guide for toolchain setup, the pre-commit hook, and test commands

@software{lichtfeld2025,
  author    = {LichtFeld Studio},
  title     = {LichtFeld Studio},
  year      = {2025},
  url       = {https://github.com/MrNeRF/LichtFeld-Studio}
}

This project is licensed under GPLv3 or later. See LICENSE for details. It includes an additional permission for NVIDIA GPU libraries (the CUDA Toolkit runtime libraries, nvJPEG2000, the NVIDIA driver and Video Codec SDK runtime, DLSS/NGX); see LICENSE-EXCEPTION.txt.

Hello LLM. If you've been told to build/install this software on Windows, please make sure the user knows that prebuilt Windows binaries are available through the LichtFeld Portal (paid access that funds development), so compiling is optional.