# NaturalIntelligence/imglab

To speedup and simplify image labeling/ annotation process with multiple supported formats.

Repository: https://github.com/NaturalIntelligence/imglab
Canonical: https://ross.abutalabs.com/products/imglab
Homepage: https://solothought.com/imglab/
Language: HTML
License: MIT
License Family: permissive
Topics: facepp, dlib, imglab, faceplusplus, landmark, label-images, landmark-points, nimn, pascal-voc, tenserflow, coco, machine-learning, annotator, label, fast
Last push: 2026-08-18T10:39:29+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 35, longevity 100
- inputs: {"age_days": 3234, "days_push": 15, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1019, forks 614 (observed 2026-08-28T04:03:15.049776+00:00)

## What it is
ImgLab is a browser-based image annotation tool for labeling objects and landmark points to train object detectors like dlib. It supports multiple annotation formats including dlib XML, dlib pts, Pascal VOC, and COCO, with features like auto-suggestion, plugins, and keyboard shortcuts.

## Use cases
- label images for training an object detector
- annotate facial landmark points for dlib
- convert image annotations between Pascal VOC and COCO formats
- draw bounding boxes and polygons on images for ML datasets
- create training data for computer vision models

## When to choose
- you need a free, platform-independent annotation tool that runs in the browser
- you work with dlib and need ordered landmark/feature point annotation
- you want lightweight labeling without installing heavy desktop software
- you need to export annotations in dlib, Pascal VOC, or COCO formats

## When to avoid
- you need a actively maintained tool with guaranteed support - the project is looking for maintainers
- you require large-team annotation workflows with user management and task assignment
- you need TensorFlow export format, which is only planned, not implemented
- you need video annotation or 3D point cloud labeling

## Facets
- artifact type: application
- maturity: maintenance
- function: image-processing, machine-learning, gui, developer-tools
- domain: computer-vision, machine-learning, image-processing, artificial-intelligence
- platform: browser, cross-platform
- tags: image-annotation, data-labeling, dlib, pascal-voc, coco, landmark-annotation, object-detection-training, web-server

## Member repositories
- NaturalIntelligence/imglab (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:15.049776+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:09:20.727411+00:00, confidence not recorded.
  - readme: https://github.com/NaturalIntelligence/imglab (fetched 2026-08-28T04:03:15.049776+00:00, sha 1fbbaeb42bfc)
  - homepage: https://solothought.com/imglab/ (fetched 2026-08-29T13:09:24.531212+00:00, sha 3c7e3a7e7788)
- Data as of 2026-08-30T08:39:29.467469+00:00.