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Detecting and Tracking Vehicles with Computer Vision + a Machine Learning Classifier

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Vehicle Detection

Udacity - Self-Driving Car NanoDegree

Detected Cars

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.

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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.

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Detecting and Tracking Vehicles with Computer Vision + a Machine Learning Classifier

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