Anomaly Detection with FiftyOne and Anomalib

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Scout Monitoring - Free Django app performance insights with Scout Monitoring
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  • fiftyone

    The open-source tool for building high-quality datasets and computer vision models

  • In this post, you'll learn how to perform anomaly detection on visual data using FiftyOne and Anomalib from the OpenVINO toolkit. For demonstration, we'll use the MVTec AD dataset, which contains images of various objects with anomalies like scratches, dents, and holes.

  • anomalib

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

  • In this post, you'll learn how to perform anomaly detection on visual data using FiftyOne and Anomalib from the OpenVINO toolkit. For demonstration, we'll use the MVTec AD dataset, which contains images of various objects with anomalies like scratches, dents, and holes.

  • Scout Monitoring

    Free Django app performance insights with Scout Monitoring. Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.

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  • CLIP

    CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  • pip install -U huggingface_hub umap-learn git+https://github.com/openai/CLIP.git

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