ultimate-ai-labeller 0.1.4

AI Labelling tool for computer vision

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)
• Model source selection:
  • Official bundled yolo26n.pt
  • Custom YOLO weights (.pt)
  • Custom RF-DETR weights (via Ultralytics interface)
• 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

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)

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-0.1.4-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 YOLO26n.pt (Bundled).
• The package includes yolo26n.pt, so first-run model download is not required.
• To use your own Tk app icon, put app_icon.png in src/ai_labeller/assets/.
• Session file: ~/.ai_labeller_session.json.