LaneDetection is a Python application developed as part of a fourth-year project for the AI course at the Faculty of Electrical Engineering in East Sarajevo. It is designed to detect and highlight lanes on a road from a video source. This project utilizes OpenCV for computer vision tasks and Tkinter for the graphical user interface.
- Real-time lane detection from a video source.
- Region of interest (ROI) masking for better lane detection.
- Average slope intercept calculation for lane lines.
- Display of detected lanes on the original video frame.
- User-friendly GUI for selecting and displaying videos.
To run the LaneDetection project you can run the command: docker-compose up
make install- installs a project with dependeciesmake install-test- installs dev version with dependecies to validation and testmake run-test- Runs all tests fromtestsmake validate- Runsmypy,flake8,isortandsafetychecksmake coverage- Generates coverage HTML reportmake run-test-full- Runs tests + validationsmake run-docker-validate- Runs validation and tests inside the docker container
- Vesna Bjeloglav (https://github.com/vbjeloglav)
- Radmilo Borovina (https://github.com/rborovina)
- Stefan Jokic
This application was created for educational purposes and is available under an open license. Feel free to use and adapt it to your needs.
For any additional information or questions, you can contact the authors.