An advanced lane detection system using Using OpenCV, canny edge detector and hough transform algorithms
The steps of this project are the following:
- Compute the camera calibration matrix and distortion coefficients given a set of chessboard images.
- Apply a distortion correction to raw images.
- Apply a perspective transform to rectify binary image ("birds-eye view").
- Use color transforms, gradients, etc., to create a thresholded binary image.
- Detect lane pixels and fit to find the lane boundary.
- Determine the curvature of the lane and vehicle position to the center.
- Warp the detected lane boundaries back onto the original image.
- Lane Width: Computes the width of the lane based on polynomial coefficients.
- Get Top Down View of the lane using "birds-eye view" technique
- Vehicles Detection with YOLO11 by Ultralytics
- Distance Estimation of each Vehicle from others based on the centroids of the bounding boxes
The images for camera calibration are stored in the folder called camera_cal.
pip install -r requirements.txtpy main.py --choice CHOICE --input INPUT_PATH