Label Studio is a multi-type data labeling and annotation tool with standardized output format
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Updated
Jun 28, 2024 - JavaScript
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Data labeling react app that is backend agnostic and can be embedded into your applications — distributed as an NPM package
Full-fledged Data Exploration Tool for Label Studio
Label data using HuggingFace's transformers and automatically get a prediction service
ML backend for the Label Studio tool. The backend uses the YOLOv8 algorithm for image segmentation or detection.
A Streamlit component integrating Label Studio Frontend in Streamlit applications
Custom YOLOv8 backend for Label Studio
Fine tuning YoloV7 to detect white, red bloodcells and platelets to be used as backend in label studio for pre annotating
Exploring NLP weak supervision approaches to train text classification models. The project is also a prototype for a semi-automated text data labelling platform. Approaches: Snorkel and Zero-Shot Learning.
Explore and demo label-studio on OpenShift
A simple python-script to augment an annotated dataset in JPG/XML Format as used by LabelIMG (https://github.com/tzutalin/labelImg) and now Label Studio. The script will rotate the images 4 times and mirror the resulting images and the annotations making for an expansion by the factor of 8.
Implementing Incremental Learning In Label Studio Using River ML Model
Annotation repos
Annotation assistent tool that uses CLIP to find described objects in dataset and label them
Create ready-to-use Label Studio pre-populated JSON files from popular OCR formats.
An AI-aided image segmentation ML-Module for Heartexlab/Label-Studio. Easy to deploy. Great to use.
Use Active Learning to diversely sample the dataset and generate new labels to train a classifier to predict whether the microscopy image contains a linear arrangement of 53BP1 accumulation on chromatin surrounding DNA damage, or irradiation induced foci.
datalabel is a UI-based data editing tool that makes it easy to create labeled text data in a dataframe. With datalabel, you can quickly and effortlessly edit your data without having to write any code. Its intuitive interface makes it ideal for both experienced data professionals and those new to data editing.
This repository provides a convenient way to run Label Studio within a Docker container, simplifying the setup and execution processes.
A desktop graphical tool for labelling image training data for object detection and other machine learning uses. Bounding boxes can be saved in ImageNet Pascal VOC (XML), JSON and CSV formats. Scripts are provided to convert the output to TensorFlow TFRecords for use with the object detection API.
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