When we drive, we use our eyes to decide where to go. The lines on the road that show us where the lanes are act as our constant reference for where to steer the vehicle. Naturally, one of the first things we would like to do in developing a self-driving car is to automatically detect lane lines using an algorithm.

In this project you will detect lane lines in images using Python and OpenCV. OpenCV means "Open-Source Computer Vision", which is a package that has many useful tools for analyzing images.

Two files are main in this project: a file containing project code and a file containing a brief write up explaining my solution. The code file is called P1.ipynb and the writeup is writeup.md

Step 1: Set up the CarND Term1 Starter Kit if you haven't already.

Step 2: Open the code in a Jupyter Notebook

If you are unfamiliar with Jupyter Notebooks, check out Cyrille Rossant's Basics of Jupyter Notebook and Python to get started.

All the code for this project is contained in a Jupyter notebook. To start Jupyter in your browser, use terminal to navigate to your project directory and then run the following command at the terminal prompt (be sure you've activated your Python 3 carnd-term1 environment as described in the CarND Term1 Starter Kit installation instructions!):

> jupyter notebook

A browser window will appear showing the contents of the current directory. Click on the file called "P1.ipynb". Another browser window will appear displaying the notebook. Follow the instructions in the notebook to launch the project.