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CarND-Term1-Project1-Lane-Finding

This is my first project in Term 1 of the Udacity Self-Driving Car Nanodegree.

I installed Docker and am using the Jupyter Notebook for this project (for Mac users I would recommend the former in the absence of a GPU), as future projects benefit from considerable speed-up when using Docker with Amazon Web Services Elastic Cloud Compute (AWS EC2). This is due to the fact that GPUs massively increase performance of neural networks, something I will be creating in the near future.

The code does the following:

  • Read an image from a video, convert to grayscale
  • Smoothen gray image using Gaussian kernel
  • Perform the Canny Function to detect edges
  • Mask a subset of the edges
  • Apply the Hough Transform to detect lines
  • Draw the lines
  • Display the result!

The Jupyter notebook (love it by the way!) you're looking for is P1 in 'submission'. Enjoy!

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My first project in the Udacity Self-Driving Car Nanodegree, where I use Canny Edge detection and the Hough Transform to detect lane lines

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