Metadata-Version: 2.4
Name: unicorn_baseline
Version: 1.2.0
Summary: Baseline inference algorithm for the UNICORN Challenge
Home-page: https://github.com/DIAGNijmegen/unicorn_baseline
Author: Joeran Bosma, Clément Grisi, Marina D`Amato, Luc Builtjes, Lena Philipp, Fennie van der Graaf, Judith Lefkes, Michelle Stegeman, Rianne Weber
Author-email: Clement.Grisi@radboudumc.nl
Project-URL: Bug Tracker, https://github.com/DIAGNijmegen/unicorn_baseline/issues
Platform: unix
Platform: linux
Platform: osx
Platform: cygwin
Platform: win32
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch
Requires-Dist: numpy<2
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Requires-Dist: pillow
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Requires-Dist: torchvision
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Provides-Extra: testing
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# UNICORN Basline 🦄

This repository contains the baseline code for various tasks in the [UNICORN challenge](https://unicorn.grand-challenge.org/).

[![PyPI version](https://img.shields.io/pypi/v/unicorn-baseline)](https://pypi.org/project/unicorn-baseline/)

## Repository Structure 🗂️

The repository is structured as follows:
```
unicorn_baseline
├── src/unicorn_baseline
│   ├── vision/             # Code for vision tasks
│   ├── language/           # Code for language tasks
│   ├── vision_language/    # Code for vision-language tasks
│   └── inference.py        # Entrypoint script
├── example-data/           # Examples of interfaces and sample files
└── Dockerfile              # Example docker file
```

## 🚀 Getting Started

System requirements: Linux-based OS (e.g., Ubuntu 22.04) with Python 3.10+ and Docker installed.

1. [Local development with Docker using public shots from Zenodo](./setup-docker.md).
