Installation and Quick Start

⚙️ Installation

Create conda environment

conda create -n lingbot-map python=3.10 -y
conda activate lingbot-map

Install PyTorch (CUDA 12.8)

pip install torch==2.8.0 torchvision==0.23.0 --index-url https://download.pytorch.org/whl/cu128

PyTorch 2.8.0 is the recommended version because NVIDIA Kaolin (required by the batch rendering pipeline) has prebuilt wheels for torch-2.8.0_cu128. If you only need demo.py you may use a newer PyTorch, but the batch renderer then requires building Kaolin from source. For other CUDA versions, see PyTorch Get Started.

Install lingbot-map

pip install -e .

Install FlashInfer (recommended)

FlashInfer provides paged KV cache attention for efficient streaming inference. It is a pure-Python package that JIT-compiles CUDA kernels on first use, so a single wheel works across CUDA/PyTorch versions:

pip install --index-url https://pypi.org/simple flashinfer-python

--index-url https://pypi.org/simple is only needed if your default pip index is an internal mirror that doesn't have flashinfer-python. (Optional) For faster first-use, you can additionally install a CUDA-specific JIT cache: pip install flashinfer-jit-cache -f https://flashinfer.ai/whl/cu128/flashinfer-jit-cache/. See FlashInfer installation for details. If FlashInfer is not installed, the model falls back to SDPA (PyTorch native attention) via --use_sdpa.

Visualization dependencies (optional)

pip install -e ".[vis]"

📦 Model Download

Model Name	Huggingface Repository	ModelScope Repository	Description
lingbot-map-long	robbyant/lingbot-map	Robbyant/lingbot-map	Better suited for long sequences and large scale scenes (Recommend).
lingbot-map	robbyant/lingbot-map	Robbyant/lingbot-map	Balanced checkpoint — trade off all-around performance across short and long sequences.
lingbot-map-stage1	robbyant/lingbot-map	Robbyant/lingbot-map	Stage-1 training checkpoint of lingbot-map — can be loaded into the VGGT model for bidirectional inference (c2w).

🚀 Quick Start

After installation, run your first scene with one command:

python demo.py --model_path /path/to/lingbot-map-long.pt \
    --image_folder example/courthouse --mask_sky

This launches an interactive viser viewer at http://localhost:8080. See Interactive Demo below for the full set of scenes and flags, or jump to Offline Rendering Pipeline for long-sequence batch rendering.