NeuralAtlas

Generate attribution maps for image classification models and serve them through a React viewer.

Backend (Python)

The backend is managed with uv. Dependencies and the Python version are pinned in pyproject.toml / uv.lock / .python-version

1. Install uv

2. Create the local environment and install locked dependencies:

   uv sync

   This creates a project-local .venv/ and installs the exact versions from uv.lock.

3. Run the attribution pipeline:

   uv run python main.py --help

   The default dataset is imagenet-pico-ai. You can select another dataset directory under interpretability-viewer/public/ with --dataset:

   uv run python main.py --dataset imagenet-pico --num-samples 20

The paired AI dataset generation feature lives in the backend and can be run with:

uv run python -m backend.ai_dataset --help

Frontend (React + Vite)

To run in development mode:

1. Clone the repository
2. Navigate to the interpretability-viewer directory
3. Install dependencies with npm install
4. Start the development server with npm run dev