Abandoned Home Detector

This model is designed to detect abandoned homes from images by identifying high-confidence indicators, such as:

  • Damaged roofs
  • Surface damage
  • Boarded-up windows
  • Graffiti

The model is built using YOLOv8, optimized for detecting these indicators with polygon-based annotations, and supports PyTorch framework for deployment. It can assist in tasks such as urban area analysis, property risk assessment, and disaster recovery planning.

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