sweppner/labeld
LabelD is a quick and easy-to-use image annotation tool, built for academics, data scientists, and software engineers to enable single track or distributed image tagging. LabelD supports both localized, in-image (multi-)tagging, as well as image categorization.
This tool helps researchers, data scientists, or anyone working with large collections of images quickly add descriptive tags to them. You feed it a set of images, either from your computer or by searching Imgur, and it provides a streamlined interface to categorize or mark specific objects and features within each image. The output is a structured set of labels for your image dataset, ready for further analysis or machine learning.
132 stars. No commits in the last 6 months.
Use this if you need a straightforward way to tag or categorize a large collection of images, especially for tasks like creating training datasets for machine learning models or organizing visual research data.
Not ideal if you require highly specialized annotation types like polygon drawing, semantic segmentation, or 3D object annotation.
Stars
132
Forks
31
Language
JavaScript
License
AGPL-3.0
Category
Last pushed
May 03, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sweppner/labeld"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
cvat-ai/cvat
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and...
HumanSignal/label-studio
Label Studio is a multi-type data labeling and annotation tool with standardized output format
wkentaro/labelme
Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted...
CVHub520/X-AnyLabeling
Effortless data labeling with AI support from Segment Anything and other awesome models.
doccano/doccano
Open source annotation tool for machine learning practitioners.