The goal of this proyect is to write a software pipeline to identify the lane boundaries in a video.
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.
This lab requires:
The lab enviroment can be created with CarND Term1 Starter Kit. Click here for the details.
The images for camera calibration are stored in the folder called camera_cal. The images in test_images are for testing your pipeline on single frames. If you want to extract more test images from the videos, you can simply use an image writing method like cv2.imwrite(), i.e., you can read the video in frame by frame as usual, and for frames you want to save for later you can write to an image file.
This proyect is Copyright © 2016-2017 Lucas Gago. It is free software, and may be redistributed under the terms specified in the MIT Licence.