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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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Usage

In order to run the project you have to start the Jupyter Notebook by running the following command:

jupyter notebook Advanced-Lane_Lines.ipynb

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Advanced Lane Line Finding Project for Self-Driving Car ND using OpenCV

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