Vehicle Damage Detection Tool

Overview

The Vehicle Damage Detection Tool is a web-based application for detecting and analyzing vehicle damage from images. It uses various image processing techniques to identify and assess damage severity. The tool supports the following processing techniques:

• Contour Detection
• Canny Edge Detection
• Sobel Edge Detection

Features

• Upload Image: Upload an image of the vehicle.
• Processing Techniques: Choose from contour detection, Canny edge detection, or Sobel edge detection.
• Object Masking: Mask non-damage areas to focus on damaged regions.
• Damage Scoring: Calculate damage severity and percentage.
• Damage Report: Download a PDF report with damage details.

Installation

1. Clone the Repository

   git clone https://github.com/yourusername/vehicle-damage-detection.git
   cd vehicle-damage-detection

2. Set Up the Environment

   Make sure you have Python 3.x installed. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install Dependencies

   Install the required Python packages:

   pip install -r requirements.txt

Usage

1. Run the Flask Application

   Start the Flask server:

   python app.py

2. Access the Web Interface

   Open your web browser and go to http://127.0.0.1:5000/ to access the tool.

3. Upload an Image

   • Click on "Choose Processing Technique" to select a method.
   • Upload the vehicle image and click "Analyze Damage".
   • View the processed image, damage severity, and download the damage report.

Configuration

• UPLOAD_FOLDER: Directory where uploaded images are stored.
• REPORT_FOLDER: Directory where PDF reports are saved.

Adjust these settings in app.py if needed.

Dependencies

• Flask
• OpenCV
• NumPy
• Werkzeug
• FPDF

Acknowledgements

• OpenCV for image processing capabilities.
• Flask for web application framework.
• FPDF for PDF report generation.