README.md

---
title: OOD Detection
emoji: 🧐
colorFrom: purple
colorTo: purple
sdk: gradio
sdk_version: 3.12.0
app_file: app.py
pinned: true
license: mit
---

# OOD Detection Demo

Out-of-distribution (OOD) detection is an essential safety measure for machine learning models. This app demonstrates how these methods can be useful in determining wether the inputs of a ResNet-50 model trained on ImageNet-1K can be trusted by the model.

This demo is [online](https://huggingface.co/spaces/edadaltocg/ood-detection) at `https://huggingface.co/spaces/edadaltocg/ood-detection`

## Running Gradio app locally:

1. Install dependencies:

```bash
pip install -r requirements.txt
```

2. Run the app:

```bash
python app.py
```

3. Open the app in your browser at `http://localhost:7860`.

## Methods implemented

- [ ] [Mahalanobis Distance](https://arxiv.org/abs/1807.03888)
- [x] [Maximum Softmax Probability](https://arxiv.org/abs/1610.02136)
- [x] [Energy Based Out-of-Distribution Detection](https://arxiv.org/abs/2010.03759)