FieldNeuroToolbox (fnt)

Preprocessing and analysis toolbox for neurobehavioral data.

Authored by Caleb C. Vogt, PhD in collaboration with Claude.

Pre-requisites

• Git
• Anaconda
• ffmpeg (and the bin file saved to your system PATH)
• GitHub Desktop (suggested)

Windows Installation

Clone the fnt GitHub repo and install the package in editable mode:

conda create --name fnt python
conda activate fnt
cd path\to\fnt
pip install -e .

GPU Support for Video Tracking (Recommended)

For SAM-based video tracking, GPU acceleration provides ~50x speedup. Install PyTorch with CUDA support:

conda activate fnt
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118

Note: This requires an NVIDIA GPU with CUDA support. The tracker will work on CPU but will be significantly slower (~10s per SAM frame vs ~0.1s on GPU).

To verify GPU detection:

python -c "import torch; print('CUDA available:', torch.cuda.is_available()); print('GPU:', torch.cuda.get_device_name(0) if torch.cuda.is_available() else 'None')"

You should see CUDA available: True and your GPU name.

Mac Installation

Open terminal:

conda create --name fnt python
conda activate fnt
cd path/to/fnt
pip install -e .

Launch the GUI

After installation, launch the FieldNeuroToolbox GUI:

conda activate fnt
fnt-gui

Updating

Because the package is installed in editable mode, updating is simple:

cd path/to/fnt
git pull

That's it — the updated code is immediately available the next time you run fnt-gui.

Note: If the update includes changes to pyproject.toml (e.g., new dependencies), you will need to re-run the install:

conda activate fnt
pip install -e .

Notes

• Package dependencies are listed in pyproject.toml