clearml-helm-charts
Helm chart repository for the new unified way to deploy ClearML on Kubernetes. ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution (by allegroai)
anomalib
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference. (by openvinotoolkit)
clearml-helm-charts | anomalib | |
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2 | 17 | |
34 | 3,291 | |
- | 5.0% | |
7.4 | 9.3 | |
7 days ago | 7 days ago | |
Smarty | Python | |
- | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
clearml-helm-charts
Posts with mentions or reviews of clearml-helm-charts.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-13.
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
On another front, ClearML excels at automating the monitoring and graphic representation of models while facilitating training tasks remotely.
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ClearML with a low-cost GPU backend
I started by Deploying the ClearML K8s helm charts within our k8s cluster
anomalib
Posts with mentions or reviews of anomalib.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-05-09.
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Computer Vision Meetup: Anomaly Detection with Anomalib and FiftyOne
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.
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Recapping the AI, Machine Learning and Data Science Meetup — May 8, 2024
Anomalib GitHub
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Anomaly Detection with FiftyOne and Anomalib
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.
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May 8, 2024 AI, Machine Learning and Computer Vision Meetup
This talk highlights the role of Anomalib, an open-source deep learning framework, in advancing anomaly detection within AI systems, particularly showcased at the upcoming CVPR Visual Anomaly and Novelty Detection (VAND) workshop. Anomalib integrates advanced algorithms and tools to facilitate both academic research and practical applications in sectors like manufacturing, healthcare, and security. It features capabilities such as experiment tracking, model optimization, and scalable deployment solutions. Additionally, the discussion will include Anomalib’s participation in the VAND challenge, focusing on robust real-world applications and few-shot learning for anomaly detection.
- Anomalib: Anomaly detection library comprising cutting-edge algorithms
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Then, when it comes to semi-supervised learning for anomaly detection, I had positive experiences with Anomalib which offers a robust library dedicated to deep learning anomaly detection algorithms. They implemented the latest models with PyTorch and offer tools to benchmark their performance.
- Defect Detection using Computer Vision
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From Lab to Live: Implementing Open-Source AI Models for Real-Time Unsupervised Anomaly Detection in Images
Anomalib is an open-source library for unsupervised anomaly detection in images. It offers a collection of state-of-the-art models that can be trained on your specific images.
- FLaNK Stack Weekly for 07August2023
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Powering Anomaly Detection for Industry 4.0
Anomalib is an open-source deep learning library developed by Intel that makes it easy to benchmark different anomaly detection algorithms on both public and custom datasets, all by simply modifying a config file. As the largest public collection of anomaly detection algorithms and datasets, it has a strong focus on image-based anomaly detection. It’s a comprehensive, end-to-end solution that includes cutting-edge algorithms, relevant evaluation methods, prediction visualizations, hyperparameter optimization, and inference deployment code with Intel’s OpenVINO Toolkit.