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This repository contains work on Second Project of Udacity's Self Driving Car Nano Degree program, (Finding the Lane lines in a given video stream, using camera calibration, perspective change and curvature calculation)

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mohan-barathi/SD_Car_ND_Advanced_Lane_lines_P2

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Project 2 : Advanced Lane Finding

Udacity - Self-Driving Car NanoDegree

The Project

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.

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The images used for camera calibration are in the folder called camera_cal. The images in test_images are used for testing the pipeline on single frames.

The output_images folder contains all the intermediate outputs of the pipeline, that were used for writeup

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This repository contains work on Second Project of Udacity's Self Driving Car Nano Degree program, (Finding the Lane lines in a given video stream, using camera calibration, perspective change and curvature calculation)

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