ImageLabelerPyQT

A collection of PyQt5-based image labeling tools designed for image restoration tasks. Built to streamline quality assessment and hallucination detection in reconstructed images.

Features

Three specialized labeling interfaces:

🎯 Hallucination Labeler

Binary classification tool for marking hallucinated regions in image reconstructions.

• Click to toggle severity of hallucinations
• Displays ground truth and hallucination proxy mask for reference
• Automatic progress saving

✅ Quality-Check Labeler

Assess overall reconstruction quality across multiple variants.

• Side-by-side comparison with ground truth
• Binary accept/reject labeling
• Resume from last labeled image

📊 Ranking Labeler

Rank multiple reconstructions by quality or hallucination severity.

• Drag-and-drop or click-based ranking (1-3 scale)
• Compare normal, intrinsic, and extrinsic hallucinations
• Color-coded feedback (Green=best, Orange=medium, Red=worst)

Installation

pip install PyQt5 numpy