Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Labelimg | 21,080 | 9 | 4 | 2 days ago | 28 | October 11, 2021 | 447 | mit | Python | |
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data. | ||||||||||
Label Studio | 14,965 | 3 | 16 hours ago | 182 | December 01, 2023 | 754 | apache-2.0 | Python | ||
Label Studio is a multi-type data labeling and annotation tool with standardized output format | ||||||||||
Labelme | 11,499 | 8 | 12 | 5 days ago | 194 | December 02, 2023 | 97 | other | Python | |
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation). | ||||||||||
Cvat | 10,534 | 3 | 17 hours ago | 23 | November 27, 2023 | 517 | mit | TypeScript | ||
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. | ||||||||||
Deeplinkdispatch | 4,301 | 28 | 16 | 5 months ago | 32 | June 27, 2023 | 58 | Java | ||
A simple, annotation-based library for making deep link handling better on Android | ||||||||||
Awesome Data Labeling | 3,173 | 2 months ago | 53 | |||||||
A curated list of awesome data labeling tools | ||||||||||
Tencent Ml Images | 2,893 | 2 years ago | 45 | other | Python | |||||
Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet | ||||||||||
Annotated_research_papers | 2,551 | 5 days ago | 1 | mit | ||||||
This repo contains annotated research papers that I found really good and useful | ||||||||||
Diffgram | 1,757 | 10 days ago | 472 | other | Python | |||||
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. | ||||||||||
Coco Annotator | 1,743 | a year ago | 216 | mit | Vue | |||||
:pencil2: Web-based image segmentation tool for object detection, localization, and keypoints |
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Label Studio is an open source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. It can be used to prepare raw data or improve existing training data to get more accurate ML models.
Have a custom dataset? You can customize Label Studio to fit your needs. Read an introductory blog post to learn more.
Install Label Studio locally, or deploy it in a cloud instance. Also you can try Label Studio Teams.
Official Label Studio docker image is here and it can be downloaded with docker pull
.
Run Label Studio in a Docker container and access it at http://localhost:8080
.
docker pull heartexlabs/label-studio:latest
docker run -it -p 8080:8080 -v `pwd`/mydata:/label-studio/data heartexlabs/label-studio:latest
You can find all the generated assets, including SQLite3 database storage label_studio.sqlite3
and uploaded files, in the ./mydata
directory.
You can override the default launch command by appending the new arguments:
docker run -it -p 8080:8080 -v `pwd`/mydata:/label-studio/data heartexlabs/label-studio:latest label-studio --log-level DEBUG
If you want to build a local image, run:
docker build -t heartexlabs/label-studio:latest .
Docker Compose script provides production-ready stack consisting of the following components:
To start using the app from http://localhost
run this command:
docker-compose up
# Requires Python >=3.7 <=3.9
pip install label-studio
# Start the server at http://localhost:8080
label-studio
conda create --name label-studio
conda activate label-studio
pip install label-studio
You can run the latest Label Studio version locally without installing the package with pip.
# Install all package dependencies
pip install -e .
# Run database migrations
python label_studio/manage.py migrate
# Start the server in development mode at http://localhost:8080
python label_studio/manage.py runserver
You can deploy Label Studio with one click in Heroku, Microsoft Azure, or Google Cloud Platform:
The frontend part of Label Studio app lies in the frontend/
folder and written in React JSX. In case you've made some changes there, the following commands should be run before building / starting the instance:
cd label_studio/frontend/
npm ci
npx webpack
cd ../..
python label_studio/manage.py collectstatic --no-input
If you see any errors during installation, try to rerun the installation
pip install --ignore-installed label-studio
To run Label Studio on Windows, download and install the following wheel packages from Gohlke builds to ensure you're using the correct version of Python:
# Upgrade pip
pip install -U pip
# If you're running Win64 with Python 3.8, install the packages downloaded from Gohlke:
pip install lxml‑4.5.0‑cp38‑cp38‑win_amd64.whl
# Install label studio
pip install label-studio
pip install -r deploy/requirements-test.txt
cd label_studio
# postgres (assumes default postgres user,db,pass)
DJANGO_DB=default DJANGO_SETTINGS_MODULE=core.settings.label_studio python -m pytest -vv -n auto
# sqlite3
DJANGO_DB=sqlite DJANGO_SETTINGS_MODULE=core.settings.label_studio python -m pytest -vv -n auto
Label Studio includes a variety of templates to help you label your data, or you can create your own using specifically designed configuration language. The most common templates and use cases for labeling include the following cases:
Connect your favorite machine learning model using the Label Studio Machine Learning SDK. Follow these steps:
This lets you:
You can use Label Studio as an independent part of your machine learning workflow or integrate the frontend or backend into your existing tools.
Project | Description |
---|---|
label-studio | Server, distributed as a pip package |
label-studio-frontend | React and JavaScript frontend and can run standalone in a web browser or be embedded into your application. |
data-manager | React and JavaScript frontend for managing data. Includes the Label Studio Frontend. Relies on the label-studio server or a custom backend with the expected API methods. |
label-studio-converter | Encode labels in the format of your favorite machine learning library |
label-studio-transformers | Transformers library connected and configured for use with Label Studio |
Want to use The Coolest Feature X but Label Studio doesn't support it? Check out our public roadmap!
@misc{Label Studio,
title={{Label Studio}: Data labeling software},
url={https://github.com/heartexlabs/label-studio},
note={Open source software available from https://github.com/heartexlabs/label-studio},
author={
Maxim Tkachenko and
Mikhail Malyuk and
Andrey Holmanyuk and
Nikolai Liubimov},
year={2020-2022},
}
This software is licensed under the Apache 2.0 LICENSE © Heartex. 2020-2021