X-AnyLabeling and label-tool

The tools are competitors, as both offer web-based image labeling and segmentation, with X-AnyLabeling providing more advanced AI support and significantly higher adoption than label-tool.

X-AnyLabeling
72
Verified
label-tool
49
Emerging
Maintenance 17/25
Adoption 10/25
Maturity 25/25
Community 20/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 23/25
Stars: 8,375
Forks: 909
Downloads:
Commits (30d): 14
Language: Python
License: GPL-3.0
Stars: 352
Forks: 78
Downloads:
Commits (30d): 0
Language: JavaScript
License: MIT
No risk flags
Stale 6m No Package No Dependents

About X-AnyLabeling

CVHub520/X-AnyLabeling

Effortless data labeling with AI support from Segment Anything and other awesome models.

This tool helps data professionals quickly and accurately label images and videos for various computer vision tasks. You input raw visual data, and it assists you in marking objects, segments, or text, outputting structured annotations that can be used to train AI models. It's designed for data engineers and researchers who need to prepare large datasets for machine learning applications.

data-annotation computer-vision machine-learning-datasets image-processing AI-model-training

About label-tool

Slava/label-tool

Web application for image labeling and segmentation

This web application helps you precisely mark and categorize specific objects or regions within images, which is critical for training computer vision models. You upload images, then use a drawing interface to outline objects with bounding boxes or detailed polygons, and fill out forms to add descriptive labels. The output is structured data that describes your images and their marked features. This tool is ideal for data scientists, AI researchers, or anyone preparing image datasets for machine learning.

image-annotation data-labeling computer-vision dataset-preparation semantic-segmentation

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