Python anomaly-detection

Open-source Python projects categorized as anomaly-detection

Top 23 Python anomaly-detection Projects

anomaly-detection
  1. pyod

    A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

  2. Nutrient

    Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers. Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.

    Nutrient logo
  3. anomaly-detection-resources

    Anomaly detection related books, papers, videos, and toolboxes

  4. darts

    A python library for user-friendly forecasting and anomaly detection on time series.

    Project mention: Darts: Python lib for forecasting and anomaly detection on time series | news.ycombinator.com | 2024-03-05
  5. sktime

    A unified framework for machine learning with time series

  6. anomalib

    An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

    Project mention: Computer Vision Meetup: Anomaly Detection with Anomalib and FiftyOne | dev.to | 2024-05-10

    In this brief walkthrough, I will illustrate how to leverage open-source FiftyOne and Anomalib to build deployment-ready anomaly detection models. First, we will load and visualize the MVTec AD dataset in the FiftyOne App. Next, we will use Albumentations to test out augmentation techniques. We will then train an anomaly detection model with Anomalib and evaluate the model with FiftyOne.

  7. stumpy

    STUMPY is a powerful and scalable Python library for modern time series analysis

    Project mention: Powerful and scalable Python library for modern time series analysis | news.ycombinator.com | 2024-08-01
  8. Merlion

    Merlion: A Machine Learning Framework for Time Series Intelligence

  9. CodeRabbit

    CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.

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  10. ailia-models

    The collection of pre-trained, state-of-the-art AI models for ailia SDK

  11. flow-forecast

    Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

  12. surpriver

    Find big moving stocks before they move using machine learning and anomaly detection

  13. logparser

    A machine learning toolkit for log parsing [ICSE'19, DSN'16]

  14. tods

    TODS: An Automated Time-series Outlier Detection System

  15. pygod

    A Python Library for Graph Outlier Detection (Anomaly Detection)

  16. luminol

    Anomaly Detection and Correlation library

  17. OpenOOD

    Benchmarking Generalized Out-of-Distribution Detection

  18. ADBench

    Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

  19. luminaire

    Luminaire is a python package that provides ML driven solutions for monitoring time series data.

  20. DGFraud

    A Deep Graph-based Toolbox for Fraud Detection

  21. DeepADoTS

    Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

  22. TranAD

    [VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.

  23. opensnitch

    OpenSnitch is a GNU/Linux application firewall (by gustavo-iniguez-goya)

  24. matrixprofile

    A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

    Project mention: The Matrix Profile | news.ycombinator.com | 2025-01-06
  25. CSI

    CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)

  26. SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

    SaaSHub logo
NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

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Python anomaly-detection related posts

  • Computer Vision Meetup: Anomaly Detection with Anomalib and FiftyOne

    1 project | dev.to | 10 May 2024
  • Anomalib: Anomaly detection library comprising cutting-edge algorithms

    1 project | news.ycombinator.com | 24 Apr 2024
  • RAG Using Structured Data: Overview and Important Questions

    5 projects | news.ycombinator.com | 10 Jan 2024
  • Open source anomaly detection for metrics

    1 project | news.ycombinator.com | 18 Dec 2023
  • Defect Detection using Computer Vision

    1 project | /r/computervision | 5 Dec 2023
  • anomaly-detection-resources: NEW Extended Research - star count:7507.0

    1 project | /r/algoprojects | 24 Oct 2023
  • anomaly-detection-resources: NEW Extended Research - star count:7507.0

    1 project | /r/algoprojects | 22 Oct 2023
  • A note from our sponsor - Nutrient
    www.nutrient.io | 17 Feb 2025
    Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries. Learn more →

Index

What are some of the best open-source anomaly-detection projects in Python? This list will help you:

# Project Stars
1 pyod 8,810
2 anomaly-detection-resources 8,548
3 darts 8,323
4 sktime 8,196
5 anomalib 4,044
6 stumpy 3,777
7 Merlion 3,522
8 ailia-models 2,125
9 flow-forecast 2,120
10 surpriver 1,799
11 logparser 1,670
12 tods 1,478
13 pygod 1,378
14 luminol 1,195
15 OpenOOD 920
16 ADBench 900
17 luminaire 771
18 DGFraud 704
19 DeepADoTS 568
20 TranAD 552
21 opensnitch 397
22 matrixprofile 362
23 CSI 277

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Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers
Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.
www.nutrient.io