This Project is based on the fifth task of the Udacity Self-Driving Car Nanodegree program. The main goal of the project is to create a software pipeline to identify vehicles in a video from a front-facing camera on a car.

Additionally, a lane line finding algorithm was added. See Lane Lines Detection Project for details.

It was implemented in Python with OpenCV and Scikit-learn libraries. Linear SVM was used as a classifier for HOG, binned color and color histogram features. The project repo is availuble on Github.


  1. Image classification using SVM

Final project video:

The full project code is available on my Github

Project posts

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01 Aug 2017

Image classification using SVM

Application of a linear SVM for image classification with HOG, binned color and color histogram features.

8 mins read