Pothole Detection using Machine Learning | Road Segmentation and Pothole using Yolo V8

Road Pothole Detection using Deep Learning

Pothole Detection and Road Segmentation using ML, aim of this project is to develop a deep learning-based system to detect and segment roads and potholes from images and videos. The project involves the use of semantic segmentation models trained on specific datasets to identify road areas and potholes, overlaying the results on input images, and processing video streams for real-time applications.

Road maintenance and pothole detection are critical for public safety and efficient transportation. Traditional methods of road inspection are time-consuming, costly, and labor-intensive. Automating the detection of roads and potholes can help authorities prioritize maintenance and improve road conditions efficiently.

Road Detection and Segmentation using OpenCV Python

Software Requirements :-

  • Coding Language : Python
  • Implementation: Software Framework.
  • Operating system : Windows 10 / 11.
  • Graphical User Interface : Tkinter

Hardware Requirement:-

  • Input Devices : Keyboard, Mouse.
  • System : Pentium i3 Processor.
  • Hard Disk : 500 GB.
  • RAM : 4 GB.

📲 Call/WhatsApp: +91-9460060699

🌎 Website: www.techieprojects.com

📺 Instagram: @pythonprojects_


💡 Checkout Related Projects:-

1. Android App:- Click Here

2. Java Projects:- Click Here

3. OpenCV Projects:- Click Here

4. Data Science Projects:- Click Here

5. Data Analytics Projects:- Click Here

5. Deep Learning Projects:- Click Here

6. Cyber Security Projects:- Click Here

7. Machine Learning Projects:- Click Here

8. Image Processing Projects:- Click Here

9. Web Development Projects:- Click Here

10. Game Development Projects:- Click Here

11. Artificial Intelligence Projects:- Click Here

12. Database Management System:- Click Here