label-studio
cleanlab
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label-studio | cleanlab | |
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49 | 69 | |
16,469 | 8,592 | |
4.5% | 6.9% | |
9.8 | 9.4 | |
1 day ago | 7 days ago | |
JavaScript | Python | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
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.
label-studio
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First 15 Open Source Advent projects
14. LabelStudio by Human Signal | Github | tutorial
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
For instance, the COCO Annotator is a web-based image annotation tool tailored for the COCO dataset format, allowing collaborative labeling with features like attribute tagging and automatic segmentation. Similarly, Label Studio offers an easy-to-use interface for bounding box object labeling in images.
- FLaNK Stack Weekly for 14 Aug 2023
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You Can't Have a Free Software AI Stack
Huh?
I wrote my own system for classifying a stream of texts in Python, I might Open Source it one of these days but I have to get it to the point where it is modular enough that I can customize it to do the particular things I want without subjecting people to my whims... I use it every day and I'm not afraid to demo it because it is rock solid.
My understanding is that my system would not be hard to adapt to work on images for certain kinds of tasks.
Pytorch is open source, Huggingface is open source. CUDA isn't. This is
https://labelstud.io/
and for annotating text spans there are so many open source tools
https://github.com/doccano/doccano
I worked for a company a few years back that built annotation tools for projects we sold to customers but never quite got to a polished general purpose annotator. Today there are an overwhelming number of companies in this space and products I never heard of, many of which are cloud based or paid. Looks like a gold rush to me.
- Label Studio: Open-Source Data Labeling Platform
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Best (quickest) way to annotate images for whole-image classification?
LabelStudio is free for single use. https://labelstud.io/
- Label Studio – Free multi-type data ML labeling and annotation tool
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Way to label yolov7 images fast
LabelStudio is pretty nice, and free & open source, but I have yet to try out their ML integration with a YOLO object detection model.
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image labeling online Tools
Label Studio is an open source data labeling tool that includes annotation functionality. It provides a simple user interface (UI) that lets you label various data types, including text, audio, time series data, videos, and images, and export the information to various model formats.
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Preprocessing data for CNN tips?
I’m fairly new to deep learning and learning as I got so sorry if this is very basic, but I’m working on a model for detecting invasive coconut rhinoceros beetles destroying palm trees using drone photography. The 1080p photos I’m given were taken 250ft AGL and were cropped into equal size smaller images with some having one or more palm trees and some having none. Im using I’m using labelStudio to generate the XML files that point to their jpg counterparts path.
cleanlab
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[Research] Detecting Annotation Errors in Semantic Segmentation Data
We have feely open-sourced our new method for improving segmentation data, published a paper on the research behind it, and released a 5-min code tutorial. You can also read more in the blog if you'd like.
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[R] Automated Quality Assurance for Object Detection Datasets
We’ve open-sourced one line of code to find errors in any object detection dataset via Cleanlab Object Detection, which can utilize any existing object detection model you’ve trained.
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[Research] Detecting Errors in Numerical Data via any Regression Model
If you'd like to learn more, you can check out the blogpost, research paper, code, and tutorial to run this on your data.
- Detecting Errors in Numerical Data via Any Regression Model
- cleanlab v2.5 now supports all major ML tasks (adds regression, object detection, and image segmentation)
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Automated Data Quality at Scale
Sharing some context here: in grad school, I spent months writing custom data analysis code and training ML models to find errors in large-scale datasets like ImageNet, work that eventually resulted in this paper (https://arxiv.org/abs/2103.14749) and demo (https://labelerrors.com/).
Since then, I’ve been interested in building tools to automate this sort of analysis. We’ve finally gotten to the point where a web app can do automatically in a couple of hours what I spent months doing in Jupyter notebooks back in 2019—2020. It was really neat to see the software we built automatically produce the same figures and tables that are in our papers.
The blog post shared here is results-focused, talking about some of the data and dataset-level issues that a tool using data-centric AI algorithms can automatically find in ImageNet, which we used as a case study. Happy to answer any questions about the post or data-centric AI in general here!
P.S. all of our core algorithms are open-source, in case any of you are interested in checking out the code: https://github.com/cleanlab/cleanlab
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Enhancing Product Analytics and E-commerce Business
Cleanlab Studio offers a user-friendly interface that allows you to visualize and review the identified issues in your dataset. You can easily explore the detected errors and make corrections with confidence. It's a hassle-free solution that can save you valuable time and improve your overall e-commerce operations. If you'd like more details you can check this article out.
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Databricks users can now automatically correct data and improve ML models
I thought this community might find it very useful that Databricks has partnered with Cleanlab to bring automated data correction and ML model improvement for both structured and unstructured datasets to all Databricks users.
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[R] Automated Checks for Violations of Independent and Identically Distributed (IID) Assumption
I just published a paper detailing this non-IID check and open-sourced its code in the cleanlab package — just one line of code will check for this and many other types of issues in your dataset.
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[P] Datalab: A Linter for ML Datasets
I recently published a blog introducing Datalab and an open-source Python implementation that is easy-to-use for all data types (image, text, tabular, audio, etc). For data scientists, I’ve made a quick Jupyter tutorial to run Datalab on your own data.
What are some alternatives?
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]
alibi-detect - Algorithms for outlier, adversarial and drift detection
doccano - Open source annotation tool for machine learning practitioners.
argilla - Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
awesome-data-labeling - A curated list of awesome data labeling tools
labelflow - The open platform for image labelling
diffgram - The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
karateclub - Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
SSL4MIS - Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
labelbox-custom-labeling-apps - Explore example custom labeling apps built with Labelbox SDK
susi - SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)