This is the Windows app named Anomalib whose latest release can be downloaded as AnomalibLibraryv2.3.1sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Anomalib
DESCRIPTION
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to plug in custom models, track experiments, tune hyperparameters, and generate visualizations that highlight anomalous regions. Its design supports unsupervised or semi-supervised paradigms, making it especially powerful for scenarios where only “normal” data is readily available and defects must be detected without exhaustive labeling. Combined with its CLI and integration with optimization tools like OpenVINO, it’s suitable for both research and edge deployment tasks.
Features
- Collection of state-of-the-art anomaly detection models
- Modular API for training, inference, benchmarking
- Hyperparameter optimization and experiment tracking
- Visualization tools for anomaly localization
- CLI support for common workflows
- Export models for accelerated inference on OpenVINO
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/anomalib.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
