https://github.com/sshleifer/traffic-signs

Classifying Traffic Signs with Tensorflow
https://github.com/sshleifer/traffic-signs

Last synced: 4 months ago
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Classifying Traffic Signs with Tensorflow

• Host: GitHub
• URL: https://github.com/sshleifer/traffic-signs
• Owner: sshleifer
• Created: 2017-08-18T02:32:31.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2017-08-21T13:29:33.000Z (almost 9 years ago)
• Last Synced: 2025-10-28T08:38:44.653Z (8 months ago)
• Language: HTML
• Size: 80.5 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
## Project: Build a Traffic Sign Recognition Program

[![Udacity - Self-Driving Car NanoDegree](https://s3.amazonaws.com/udacity-sdc/github/shield-carnd.svg)](http://www.udacity.com/drive)

Overview

---

In this project, you will use what you've learned about deep neural networks and convolutional neural networks to classify traffic signs. You will train and validate a model so it can classify traffic sign images using the [German Traffic Sign Dataset](http://benchmark.ini.rub.de/?section=gtsrb&subsection=dataset). After the model is trained, you will then try out your model on images of German traffic signs that you find on the web.

We also want you to create a detailed writeup of the project. Check out the [writeup template](https://github.com/udacity/CarND-Traffic-Sign-Classifier-Project/blob/master/writeup_template.md) for this project and use it as a starting point for creating your own writeup. The writeup can be either a markdown file or a pdf document.

To meet specifications, the project will require submitting three files: 

* the Ipython notebook with the code

* the code exported as an html file

* a writeup report either as a markdown or pdf file