fiftyone
oasdiff
fiftyone | oasdiff | |
---|---|---|
19 | 12 | |
6,712 | 584 | |
2.1% | 4.8% | |
10.0 | 9.2 | |
about 13 hours ago | 3 days ago | |
Python | Go | |
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.
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?
oasdiff
- FLaNK AI for 11 March 2024
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Serverless APIs: Auto-Generate OpenAPI Docs & CI/CD Protections
We will use an open-source GitHub action, oasdiff-action, based on the tool ‘oasdiff.’
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How Can You Achieve Continuous Deployment for *APIs*?
Nice, Have you come across this tool oasdiff from the article? It may help with detect API breaking changes in swagger
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How to prevent breaking API changes with API Gateway
While you might wish that pull request reviewers would spot any breaking changes, relying solely on this method is not certain and might lead to failure eventually. If you have OpenAPI/Swagger documentation for your APIs, these can be version-controlled and included in a CI pipeline. APISIX doesn't natively support direct integration with version control systems like Git for API specification changes. However, you can set up a process outside APISIX. Tools like Oasdiff or Bump can identify changes in API specs, and trigger a CI pipeline (add GitHub Action) that runs tests against the route endpoints in APISIX to ensure no breaking changes are introduced.
- Would you like to be notified when your API provider makes a breaking change?
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Testing for Breaking Changes in Fastify APIs
Now that we have a way to lookup our API’s behavior with Git, we can start testing for breaking changes between versions of our API. We’ll be using Optic (an open source tool I created) to do just that. If you are looking for other options I recommend https://github.com/OpenAPITools/openapi-diff or https://github.com/Tufin/oasdiff.
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Ask HN: Non-Breaking API deprecation in OpenAPI spec – what do you think?
2. Delete the API at the sunset date or later
People seem to want such a process in order to prevent breaking-changes.
I wrote a diff tool for OpenAPI spec which supports detection of breaking-changes and I recently extended it to support this process and a bit more.
Now I'm looking for feedback.
Proposed Solution (currently in Beta): https://github.com/Tufin/oasdiff#non-breaking-removal-of-deprecated-resources
Related requests:
- A diff tool and Go module for OpenAPI Specification
- OpenAPI Diff
What are some alternatives?
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
openapi-preprocessor - An authoring tool for OpenAPI specifications
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]
apiclarity - An API security tool to capture and analyze API traffic, test API endpoints, reconstruct Open API specification, and identify API security risks.
ZnTrack - Create, visualize, run & benchmark DVC pipelines in Python & Jupyter notebooks.
openapi-diff - Utility for comparing two OpenAPI specifications.
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
openapi-generator-go - An opinionated OpenAPI v3 code generator for Go. Use this to generate API models and router scaffolding.
streamlit - Streamlit — A faster way to build and share data apps.
api-firewall - Fast and light-weight API proxy firewall for request and response validation by OpenAPI specs.
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
Optic - OpenAPI linting, diffing and testing. Optic helps prevent breaking changes, publish accurate documentation and improve the design of your APIs.