Project: Traffic Sign Classifier

Overview

This Project is a part of Udacity Self Driving Car nanodegree program. This project consists of a trained and validated model, that can classify traffic sign images using the German Traffic Sign Dataset.

This project repository consists of:

• the Ipython notebook with the code
• the code exported as an html file
• a writeup report (markdown)

The Project

The goals / steps of this project are the following:

• Load the data set
• Explore, summarize and visualize the data set
• Design, train and test a model architecture
• Use the model to make predictions on new images
• Analyze the softmax probabilities of the new images
• Summarize the results with a written report

Dependencies

To try this project in any machine, the Udacity Term1 starter kit can be used, to set up the environment:

• CarND Term1 Starter Kit

Dataset and Repository

1. Download the data set. This is a pickled dataset in which we've already resized the images to 32x32. It contains a training, validation and test set.