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AI Labelling tool for computer vision

Project description

Ultimate AI Labeller

Desktop image annotation tool for object detection datasets (Tkinter + Ultralytics).

Features

  • Bounding-box annotation with drag, move, and resize handles
  • Undo/redo history (Ctrl+Z, Ctrl+Y)
  • Image navigation (F next/save, D previous)
  • Auto red-region proposal (A)
  • YOLO detection from UI (Run Detection)
  • Startup source selection:
    • Open Images Folder
    • Open YOLO Dataset
    • Open RF-DETR Dataset
  • Detection model management:
    • Official model mode (yolo26m.pt path by default)
    • Import custom models (.pt, .onnx) via Browse Model
    • Select model from dropdown library
  • Auto-detect and propagate options
  • Scrollable right settings panel
  • Remove/restore bad frames from split
  • Image dropdown jump
  • Session resume (last project/split/image/model settings)
  • English/Chinese UI switch and light/dark theme
  • Export all annotations by format:
    • YOLO (.txt) full dataset export
    • JSON full dataset export (per-image annotation json)

Dataset Structure

your_project/
  images/
    train/
    val/
    test/
  labels/
    train/
    val/
    test/
  • Image extensions: .png, .jpg, .jpeg
  • Label format: YOLO txt (class cx cy w h, normalized)
  • Full guide (ZH): docs/dataset-structure-guide.md

Removed frames are moved to:

your_project/
  removed/
    train|val|test/
      images/
      labels/

Install

From PyPI:

pip install ultimate_ai_labeller

From local wheel:

pip install dist/ultimate_ai_labeller-0.1.5-py3-none-any.whl

From source:

pip install .

For development:

pip install -e .

Run

ai-labeller

Or:

python src/ai_labeller/main.py

Shortcuts

  • F: save and next image
  • D: previous image
  • A: auto red detection
  • Ctrl+Z: undo
  • Ctrl+Y: redo
  • Delete: delete selected box

Notes

  • Default detection model mode is Official YOLO26m.pt (Bundled).
  • If the official model file is unavailable locally, import a custom .pt/.onnx model from the UI.
  • To use your own Tk app icon, put app_icon.png in src/ai_labeller/assets/.
  • Session file: ~/.ai_labeller_session.json.

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