Traffic Sign Classification

A convolutional neural network to classify traffic signs

INTRODUCTION

In this project, I design and implement a convolutional neural network in Python using TensorFlow. The model is based off of the LeNet-5 architecture. I train and validate the model using traffic sign images from the German Traffic Sign Dataset. The entire data pipeline is constructed in a Jupyter Notebook and a detailed writeup is also provided.

This project was undertaken as part of the Udacity Self-Driving Car NanoDegree.

HOW TO USE

Project dependencies

You can follow the guide explained here to setup a working environment.

• https://github.com/udacity/CarND-Term1-Starter-Kit

Jupyter Notebooks

• traffic_sign_classifier.ipynb

RELEVANT LINKS

Project writeup

• writeup.md

Original project repo

• https://github.com/udacity/CarND-Traffic-Sign-Classifier-Project