dvtlab/TagiFLY

Labeling Tool for Computer Vision

38
/ 100
Emerging

This tool helps computer vision practitioners efficiently label images and video frames for training AI models. You can load in a folder of images and use various annotation tools like bounding boxes, polygons, and keypoints to mark objects and features. The output is structured data in formats like YOLO, COCO, or Pascal VOC, ready for use in machine learning workflows. It's ideal for AI trainers, data annotators, and researchers working with visual data.

No commits in the last 6 months.

Use this if you need a desktop application to accurately draw various types of annotations on images and export them in standard computer vision dataset formats for AI model training.

Not ideal if you require cloud-based collaboration for large teams, automated pre-labeling features, or specialized annotations beyond standard object detection and segmentation tasks.

computer-vision data-labeling AI-training image-annotation object-detection
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 15 / 25
Community 15 / 25

How are scores calculated?

Stars

15

Forks

4

Language

JavaScript

License

MIT

Last pushed

Oct 09, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/dvtlab/TagiFLY"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.