Anomalib

7.1easy start · #3 of 19
in Anomaly Detection Software

Free to practise onyes
Free trialnot on record
Well documentedyes
Runs where you workyes

Runs on Linux, self-hosted, Web, Windows.

Anomalib is ranked #3 of 19 in anomaly detection software on The Geeks Club. It runs on Linux, Self-hosted, Web, Windows. There is a free plan.

Anomalib plans and pricing

All plans

Open-source library Free Apache-2.0 licensed library · Install from PyPI or source github.com · 4 Oct 2026

Compared on anomaly detection software

Detection method: machine-learning
Supported data: images, videos
Deployment options: self-hosted

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The record

Purpose: Anomalib is a deep learning library for benchmarking, developing, and deploying anomaly detection algorithms, with a focus on detecting or localizing anomalies in images and videos.
Training and benchmarking: It provides a modular Python API and CLI for training, inference, and benchmarking.
Algorithms and datasets: The project describes its collection as ready-to-use deep learning anomaly detection algorithms and benchmark datasets.
Model framework: Its model implementations are based on Lightning.
Edge inference: Most models can be exported to OpenVINO Intermediate Representation for accelerated inference on Intel hardware.
Experiment tracking: The documented logging integrations include Weights & Biases, Comet.ml, and TensorBoard through PyTorch Lightning loggers.
Deployment: Inference options include Torch, Lightning, Gradio, and OpenVINO.
Studio: Anomalib Studio is a low/no-code web application that accepts USB or IP cameras or image folders and can output to industrial pipelines through ROS messages or MQTT.
Studio availability: Studio is described as a pre-release under active development, with features that may change and functionality that may be incomplete or unstable; it is offered as a Docker container or standalone application.
Hardware support: Installation options include CPU, CUDA on Linux or Windows with NVIDIA GPUs, ROCm on Linux with AMD GPUs, and Intel XPU on Linux.
Intel GPU limit: The README says Intel GPU training currently supports only a single GPU and notes testing on Arc 750 and Arc 770.
Security: The project documents continuous security scanning with CodeQL, Semgrep, Bandit, Zizmor, Trivy, and Dependabot, and directs vulnerability reports to Intel's vulnerability handling guidelines.
License: The repository identifies its license as Apache-2.0.
Price from: Free

Where it ranks on The Geeks Club

Best Anomaly Detection Software in 2026#3 of 19

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Sources

github.com/open-edge-platform/anomalib· checked 4 Oct 2026
github.com/open-edge-platform/anomalib/blob/main/S· checked 4 Oct 2026