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.
To complete the project, two files will be submitted: a file containing project code and a file containing a brief write up explaining your solution. We have included template files to be used both for the code and the writeup.The code file is called P1.ipynb and the writeup template is writeup_template.md
To meet specifications in the project, take a look at the requirements in the project rubric
Creating a Great Writeup
For this project, a great writeup should provide a detailed response to the "Reflection" section of the project rubric. There are three parts to the reflection:
Identify any shortcomings
- During the turns, the detection is not accurate. Need to find curves instead of lines may be!
- When the cars changing line, the solution may not work due to rapid change in slope - need to figure out a way
Suggest possible improvements
- The theorems can be explaned better during the lectures.