---
name: anomalib
summary: "Anomalib is a deep-learning library focused on benchmarking, developing, and deploying anomaly detection algorithms, particularly for visual/image-based defect detection. It bundles state-of-the-art unsupervised and few-shot anomaly detection models with training, evaluation, and edge-deployment tooling."
language: Python
license: Apache-2.0
repo: https://github.com/open-edge-platform/anomalib
source: https://opensources.dev/resource/anomalib
health: 100
---

# anomalib

Anomalib is a deep-learning library focused on benchmarking, developing, and deploying anomaly detection algorithms, particularly for visual/image-based defect detection. It bundles state-of-the-art unsupervised and few-shot anomaly detection models with training, evaluation, and edge-deployment tooling.

#  Anomalib Documentation

## Introduction

This is the source code for the Anomalib documentation. It is built using sphinx-design and myst parser.

## Installation

To install the dependencies, run the following command from the project root:

```bash
pip install .[docs]
```

## Build

To build the documentation, run the following command:

```bash
cd docs
sphinx-build -b html source build
```