RichNass87/inspector-roofing-roof-damage-yolo: v1.0.0 - Initial Release: YOLO Roof Damage Detection Model

Overview

Initial release of the inspector-roofing-roof-damage-yolo model. This YOLO (You Only Look Once) based computer vision model is trained to automatically detect and classify common signs of roof damage from drone and high-resolution aerial imagery.

Key Features & Capabilities

• Damage Classification: Detects missing shingles, wind damage, and hail impacts on various roofing materials.
• High-Speed Inference: Optimized for rapid batch-processing of property inspection images.
• Integration-Ready: Designed to integrate seamlessly with the Inspector Roofing / InstantRoofView ecosystem for automated damage reports.

Model Performance (v1.0.0)

• Architecture: [Insert YOLO version, e.g., YOLOv8x]
• mAP50: [Insert Accuracy metric, e.g., 0.85]
• Dataset: Trained on a custom dataset of [Insert Number] annotated residential roof images.

Installation & Quick Start

To run inference using this model, clone the repository and install the requirements:

git clone [https://github.com/RichNass87/inspector-roofing-roof-damage-yolo.git](https://github.com/RichNass87/inspector-roofing-roof-damage-yolo.git)
cd inspector-roofing-roof-damage-yolo
pip install -r requirements.txt