Potholes Detection Computer Vision Project

Potholes Detection Project

The Potholes Detection Project aims to develop an intelligent system capable of identifying and classifying potholes on road surfaces using computer vision techniques. The goal is to enhance road maintenance processes by providing accurate and real-time information about pothole locations.

Class Types:

1. Pothole Class:
   • Images containing potholes in various shapes and sizes.
   • Annotations should highlight the boundaries and characteristics of the potholes.
   • Differentiate between freshly formed and well-established potholes.

Current Status and Timeline:

• Current Status:

  • Data Collection: Ongoing
  • Model Development: In Progress
  • Testing and Validation: In Progress

• Timeline:

  • Data Collection (Phase 1): January 2024
  • Model Development: January 2024
  • Testing and Validation: January 2024

Contribution and Labeling Guidelines:

• Contribution Guidelines:

  • Fork the repository and create a new branch for your contributions.
  • Follow the coding and documentation standards outlined in the project.

• Labeling Guidelines:

  • Use specific tools for annotation, such as bounding boxes.
  • Clearly label potholes and non-pothole areas in images.

How to Contribute:

1. Data Contribution:

   • Ensure data adheres to the labeling guidelines.
   • Submit pull requests with additional annotated images.

2. Code Contribution:

   • Address open issues or propose new features.
   • Submit pull requests following the contribution guidelines.

3. Documentation Contribution:

   • Improve existing documentation or create new documentation where needed.
   • Submit pull requests with documentation enhancements.

The project welcomes contributions from the community to improve the accuracy and robustness of the pothole detection system.