Topics / #annotation-tool

Annotation-tool projects on GitHub

Labeling and annotating images, text, and video for ML training.

As of , the most-starred Annotation-tool projects on GitHub are label-studio (28.5K stars), labelImg (25K stars) and screenity (18.8K stars). GitHub.Locker tracks 7 Annotation-tool repositories with 117.9K stars combined. The fastest-growing on October 18 was label-studio, with +10 stars in a day.

7Projects
117.9KStars in total
+32Stars in a day

Hot right now

Most stars gained in a day · Oct 18

The all-time top

7 projects · by stars

  1. #1 · HumanSignal/label-studio

    label-studio

    Label Studio is an open source data labeling and annotation tool: you label audio, text, images, videos, and time series in a browser UI and export the results in formats ready for ML training.

    28.5K
  2. #2 · HumanSignal/labelImg

    labelImg

    A graphical image annotation tool: you draw bounding boxes around objects in images to build labeled datasets for object detection. Created by Tzutalin, it now lives with the Label Studio community.

    25K
  3. #3 · alyssaxuu/screenity

    screenity

    A free, privacy-friendly screen recorder and annotation tool for Chrome: record your screen or camera, annotate and edit the video, and export it — with no time limits and no sign-up.

    18.8K
  1. 4

    cvat

    17Kcvat-ai/cvat · Python

    CVAT is an open-source, self-hosted data annotation platform for building labeled datasets from images, video, and 3D point clouds, used for computer vision and visual AI projects.

  2. 5

    labelme

    16.2Kwkentaro/labelme · Python

    Labelme is a graphical image annotation tool written in Python: you draw polygons, rectangles, circles, lines and points on images to build labeled datasets for computer vision work.

  3. 6

    doccano

    10.8Kdoccano/doccano · Python

    Doccano is an open-source text annotation tool that lets humans label data for machine learning tasks like text classification, sequence labeling, and sequence-to-sequence problems such as summarization or translation.

  4. 7

    evals-skills

    1.5Kai-evals-course/evals-skills

    A collection of agent skills that guide AI coding agents to build product-specific AI evals — not foundation-model benchmarks. It encodes mistakes the authors saw across 50+ companies and thousands of students in their AI Evals course.

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