Traffic Sign Recognition

  Udacity Self-Driving Car Engineer Nanodegree Project 2

Predicting the class of a traffic sign

Project Overview

This project contains the results from completing Project 2 of the Udacity Self-Driving Car Engineer Nanodegree. The goal of this project is to create a convolutional neural network capable of classifying a set of traffic signs, originally taken from the German Traffic Sign Dataset with an accuracy of at least 93%.

5x5 Patches from the weights applied to the first convolutional layer

Files in the repository

• Code for the pipeline is contained in the Traffic Sign Classifier Notebook
• A writeup detailing the results of the project and describing the procedure for creating a model capable of achieving those results

Running the code

This project was developed using Python 3.5. The IPython notebook can be run using Jupyter Notebooks. The project depends on the NumPY, OpenCV, Matplotlib & TensorFlow libraries.