Udacity Self-Driving Car Nanodegree - Finding Lane Lines on the Road

This repo contains the code written to complete the first project on Udacity Self-Driving Car Nanodegree. This project consists of algorithms to identify lane lines on the road on a video. The video is taken from a camera at the center of a vehicle.


To run this project, you need Miniconda installed(please visit this link for quick installation instructions.)


To create an environment for this project use the following command:

conda env create -f environment.yml

After the environment is created, it needs to be activated with the command:

source activate carnd-term1

and open the project’s notebook P1.ipynb inside jupyter notebook:

jupyter notebook P1.ipynb


The repo contains the jupyter notebook P1.ipynb where the processing pipeline is implemented. The pipeline consists on six steps represented by six different functions:

First, the pipeline is tested agains the images contained at test_images. The output of each step is saved in a directory:

After that test, the pipeline is consolidated on a single function process_image to apply it on a video frame. The sample videos could be found here. The video after the transformation are saved on the [test_videos_output][test_videos_output] directory.

An html version of the output is here.


This project copyright is under MIT License.