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janusch edited this page Oct 29, 2025
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Binaries are not provided yet. Please follow the instructions to build LichtFeld Studio from source.
- OS: Linux (Ubuntu 22.04+) or Windows
- CMake: 3.30 or higher
- Compiler: C++23 compatible (GCC 14+ or Clang 17+)
- CUDA: 12.8 or higher (required)
- LibTorch: 2.7.0 (setup instructions below)
- vcpkg: For dependency management
- GPU: NVIDIA GPU with compute capability 7.5+
- VRAM: Minimum 8GB recommended
- Tested GPUs: RTX 4090, RTX A5000, RTX 3090Ti, A100, RTX 2060 SUPER
The preferred way to use LichtFeld Studio is to import your data (undistorted images + pointcloud + camera locations) in COLMAP format.
Have a look at these 2 introduction videos on how to get your images ready for use in LichtFeld Studio:
Example datasets can be found here
Once your dataset is ready, you can use LFS to train your images to create a Gaussian Splat, either using the GUI or the command line.
- GUI: start LightFeld Studio and use "Import dataset" to load your dataset
- Command line: Basic training:
./build/LichtFeld-Studio -d data/garden -o output/gardenTraining with evaluation and visualization:
./build/LichtFeld-Studio \
-d data/garden \
-o output/garden \
--eval \
--save-eval-images \
--render-mode RGB_D \
-i 30000MCMC strategy with limited Gaussians:
./build/LichtFeld-Studio \
-d data/garden \
-o output/garden \
--strategy mcmc \
--max-cap 500000More command line options: command line options


