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A newer version of the Gradio SDK is available: 6.16.0
Backend Environment Setup
Use Python 3.12. The .venv/ directory is disposable and ignored by git.
macOS CPU setup
cd backend/floor-visualizer
python3.12 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -r requirements-mac.txt
VISUALIZER_CONFIG=visualizer.local.toml uvicorn app:app --host 0.0.0.0 --port 7860
NVIDIA GPU setup
Use this on the GPU machine. This installs the CUDA 12.6 PyTorch wheels.
cd backend/floor-visualizer
python3.12 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install --index-url https://download.pytorch.org/whl/cu126 torch==2.7.0 torchvision==0.22.0
python -m pip install -r requirements-base.txt
VISUALIZER_CONFIG=visualizer.gpu.toml uvicorn app:app --host 0.0.0.0 --port 7860
The first GPU run downloads shi-labs/oneformer_ade20k_swin_large and the depth model into the Hugging Face cache.
Notes
- Environment variables override TOML values, for example
SEGMENTATION_MODEL=segformer. requirements.txtis a full freeze from an existing environment. Prefer the smaller platform files above when recreating.venv.