Advanced Lane Finding
About this repository
This repository contains a project that shows how a lane detection based on the computer vision algorithms works. The algorithm works offline and not in real-time.
The goals / 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.
- Use color transforms, gradients, etc., to create a thresholded binary image.
- Apply a perspective transform to rectify binary image ("birds-eye view").
- Detect lane pixels and fit to find the lane boundary.
- Determine the curvature of the lane and vehicle position with respect to center.
- Warp the detected lane boundaries back onto the original image.
- Output visual display of the lane boundaries and numerical estimation of lane curvature and vehicle position.
Install the Udacity starting kit from https://github.com/udacity/CarND-Term1-Starter-Kit
git clone https://github.com/ywiyogo/CarND1-P4-AdvancedLaneFinding.git
Go to the repository folder and activate the virtualenvironment:
source activate carnd-term1
Start the program python main.py
Please read the writeup