Vehicle Detection

Project Overview

This project contains the results from completing Project 5 of the Udacity Self-Driving Car Engineer Nanodegree. The goal of the project is to build an object detector that detects and tracks cars in a video stream. I take advantage of a feature descriptor called a Histogram of Oriented Gradients (HOG), which is a handy way of simplifying and extracting useful features from an image, and combine it with a machine learning classifier, specifically the Multi-layer Perceptron Classifier.

Files in the repository

• The Project Notebook
• A Project Writeup
• The processed output video
• A diagnostic video with heatmaps overlaid atop the video frames

Running the code

This project was developed using Python 3.5. The project depends on the NumPy, OpenCV, Scikit Learn, Scikit Image, Matplotlib & MoviePy libraries.