🚧 Pothole Detecting, Locating & Alert System Using Machine Learning

📌 Overview

Potholes on roads are a significant issue, leading to vehicle damage, accidents, and costly repairs. This project proposes an automated pothole detection system using Machine Learning (ML). The system analyzes road images/videos and detects potholes in real-time, leveraging state-of-the-art YOLOv5 object detection model.

📜 Features

✅ Real-time pothole detection

✅ High accuracy (up to 84%) in pothole identification

✅ Live camera feed support added

✅ Custom pothole dataset used for model training

✅ Image preprocessing & augmentation to enhance model performance

🚀 Technologies Used

💻 Software Requirements

Operating System: Windows 7/8/8.1/10/11 (or Linux/macOS)

Backend: Python (with ML libraries)

Frontend: HTML, CSS

IDE: Anaconda / Jupyter Notebook 📦 Machine Learning Tools YOLOv5 for real-time object detection OpenCV for image processing Pandas & NumPy for data handling Matplotlib for visualization

🔧 Installation & Setup 1️⃣ Clone the Repository git clone https://github.com/Stackherd/Pothole-Detecting-Locating-and-Alert-System-Using-Machine-Learning.git cd to the repo

2️⃣ Create & Activate Virtual Environment python -m venv venv

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Run the Pothole Detection Model

Get Support from Stackherd team

🤝 Contributing

Contributions are welcome! Feel free to open an Issue or submit a Pull Request.

📧 Contact

📌 Sanjay R P- [email protected]

📌 Isaac A - [email protected]

💡 Let's build safer roads with AI! 🚗💨