mlem
fiftyone
mlem | fiftyone | |
---|---|---|
18 | 19 | |
704 | 6,674 | |
- | 1.5% | |
8.2 | 10.0 | |
8 months ago | 6 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
mlem
- The open-source tool to simplify your ML model deployments
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Anyone else just holding out hope that Apollo will find a way to live on (even tho it’s probably like .01% chance)?
Mlem for Lemmy has a similar look and feel to Apollo. Still missing a lot of features though. https://github.com/iterative/mlem
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How to log model artifacts with MLFLOW and DVC?
Here are a few things to consider: 1. You're using both DVC and MLflow to store the model artifact, why? 2. How I envision MLflow, DVC and git to work together is like this. DVC to manage the training dataset, git to manage the code, and MLflow will do the rest. About the part about "versioning" the model, MLflow has a model registry feature to "tag" a well-performing experiment. 3. Or just to do everything in DVC. DVC also has a way to do experiment tracking. Then if you need a model registry there's MLEM by the same company.
- MLEM: Open-source tool to package, serve, and deploy ML models on any platform
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Open-source tool to simplify ML model deployment
No, it's a completely separate open source tool, not directly related to DVC - https://github.com/iterative/mlem
- Tool to package, serve, and deploy any ML model on any platform
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Git-based Model Registry
This functionality can be used from open source tool mlem.ai and our released UI - https://studio.iterative.ai/
- Open source tool to package and deploy models
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MLEM - versioning and deploying your machine learning models using GitOps principles and a standard format for ML models
MLEM is a new MLOps tool to bridge the gap between ML engineers and DevOps teams by using the git-based approach that developers are already familiar with. Using MLEM, developers can store and track their ML models throughout their lifecycle: GitHub - iterative/mlem: 🐶 Version and deploy your ML models following GitOps principles
fiftyone
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May 8, 2024 AI, Machine Learning and Computer Vision Meetup
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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Voxel51 Is Hiring AI Researchers and Scientists — What the New Open Science Positions Mean
My experience has been much like this. For twenty years, I’ve emphasized scientific and engineering discovery in my work as an academic researcher, publishing these findings at the top conferences in computer vision, AI, and related fields. Yet, at my company, we focus on infrastructure that enables others to unlock scientific discovery. We have built a software framework that enables its users to do better work when training models and curating datasets with large unstructured, visual data — it’s kind of like a PyTorch++ or a Snowflake for unstructured data. This software stack, called FiftyOne in its single-user open source incarnation and FiftyOne Teams in its collaborative enterprise version, has garnered millions of installations and a vibrant user community.
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How to Estimate Depth from a Single Image
We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics.
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How to Cluster Images
With all that background out of the way, let’s turn theory into practice and learn how to use clustering to structure our unstructured data. We’ll be leveraging two open-source machine learning libraries: scikit-learn, which comes pre-packaged with implementations of most common clustering algorithms, and fiftyone, which streamlines the management and visualization of unstructured data:
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Efficiently Managing and Querying Visual Data With MongoDB Atlas Vector Search and FiftyOne
FiftyOne is the leading open-source toolkit for the curation and visualization of unstructured data, built on top of MongoDB. It leverages the non-relational nature of MongoDB to provide an intuitive interface for working with datasets consisting of images, videos, point clouds, PDFs, and more.
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FiftyOne Computer Vision Tips and Tricks - March 15, 2024
Welcome to our weekly FiftyOne tips and tricks blog where we recap interesting questions and answers that have recently popped up on Slack, GitHub, Stack Overflow, and Reddit.
- FLaNK AI for 11 March 2024
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How to Build a Semantic Search Engine for Emojis
If you want to perform emoji searches locally with the same visual interface, you can do so with the Emoji Search plugin for FiftyOne.
- FLaNK Stack Weekly for 07August2023
- Please don't post like 20 similar images to the art sites?
What are some alternatives?
ZnTrack - Create, visualize, run & benchmark DVC pipelines in Python & Jupyter notebooks.
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
truckfactor - Tool to compute the truck factor of a Git repository
streamlit - Streamlit — A faster way to build and share data apps.
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
torchlambda - Lightweight tool to deploy PyTorch models to AWS Lambda
git-repo-updater - A console script that allows you to easily update multiple git repositories at once
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.