Skip to content

Latest commit

 

History

History
23 lines (17 loc) · 1.41 KB

README.md

File metadata and controls

23 lines (17 loc) · 1.41 KB

Project: Build a Traffic Sign Recognition Program

Udacity - Self-Driving Car NanoDegree

Overview

In this project, I am using deep neural networks and convolutional neural networks to classify traffic signs. I trained a model so it can decode traffic signs from natural images by using the German Traffic Sign Dataset. After the model is trained, I testes the model on new images of traffic signs that I found on the web.

Dependencies

This lab requires:

The lab enviroment can be created with CarND Term1 Starter Kit. Click here for the details.

Dataset

  1. Download the dataset. This is a pickled dataset in which we've already resized the images to 32x32.
  2. Clone the project and start the notebook.
git clone https://github.com/udacity/CarND-Traffic-Sign-Classifier-Project
cd CarND-Traffic-Sign-Classifier-Project
jupyter notebook Traffic_Sign_Classifier.ipynb
  1. Follow the Traffic_Sign_Recognition.ipynb notebook, to see the implementation and other details about the project.