Vehicle Detection

Overview

A self driving car needs to be able to navigate a road using computer vision. In this project we develop a vehicle detection system. Many aspects of OpenCV, python, numpy, and matplotlib are used to develop the vehicle detection system. The jupyter notebook can be found here VehicleDetection.ipynb

Installing and Running the Pipeline

The following steps are used to run the pipeline:

1. Install jupyter notebook environment and packages

   $ https://conda.io/miniconda.html
   

2. Clone the Vehicle Dectection git repository

   $ git clone https://github.com/jfoshea/Vehicle-Detection.git
   

3. enable cardnd-term1 virtualenv

   $ source activate carnd-term1
   

4. Run the Pipeline

   $ jupyter notebook VehicleDetection.ipynb
   

The output videos are: [output_test_video.mp4] (https://github.com/jfoshea/Vehicle-Detection/blob/master/output_test_video.mp4) [output_project_video.mp4] (https://github.com/jfoshea/Vehicle-Detection/blob/master/output_project_video.mp4)

Writeup

A detailed writeup are located here [writeup] (https://github.com/jfoshea/Vehicle-Detection/blob/master/writeup.md)