label-studio
awesome-data-labeling
| label-studio | awesome-data-labeling | |
|---|---|---|
| 50 | 7 | |
| 18,504 | 3,725 | |
| 2.7% | 1.2% | |
| 9.9 | 0.0 | |
| 2 days ago | 4 months ago | |
| JavaScript | ||
| Apache License 2.0 | - |
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label-studio
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Annotation is dead
If instead you have a cohort on hand — -i.e., you do not want to send your data to a third party for any reason, or perhaps you have energetic undergrads — -then you could alternatively consider local, open-source annotation such as CVAT and Label Studio. Finally, nowadays, you might instead work with Large Multimodal Models to have them annotate your data; more on this awkward angle later.
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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.
awesome-data-labeling
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CVAT alternatives for video frame annotation
GitHub - heartexlabs/awesome-data-labeling: A curated list of awesome data labeling tools
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[P] Can anyone suggest free Image annotation tool for multi labelling?
Checkout this curated list on heartexlabs github. I used the list to find server-like annotation tools.
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Segmentation Maps
A Google search throws plenty of results for labelling tools: - https://github.com/heartexlabs/awesome-data-labeling - https://www.folio3.ai/blog/labelling-images-annotation-tool/ - https://neptune.ai/blog/data-labeling-software/amp
- How would you structure a dataset for both image counting and classification? And what would be the best approach for this task?
- Awesome-Data-Labeling
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How to get image dataset annotated? Any idea?
If you're looking for a tool or something, there are plenty out there. Of course, even with these tools, labeling 50k images is likely not feasible for an individual.
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[D] Suggestions for sentiment analysis tools
You can have a look at aws ground truth for this, or have a look at this https://github.com/heartexlabs/awesome-data-labeling
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]
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.
doccano - Open source annotation tool for machine learning practitioners.
SSL4MIS - Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
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/opencv/cvat]
haystack - :mag: AI 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.
labelbox-custom-labeling-apps - Explore example custom labeling apps built with Labelbox SDK
labelbee-client - Out-of-the-box Annotation Toolbox
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
ScrivanoForLinux - Scrivano is a notetaking application for handwritten notes.