Project: Build a Traffic Sign Recognition Program

Overview

This project trains a deep neural networks model to recognize the traffic signs using the German Traffic Sign Dataset.

Dependencies

This lab requires:

• CarND Term1 Starter Kit

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

3. Follow the instructions in the Traffic_Sign_Recognition.ipynb notebook.

How to run the script

1. The script assumes that the downloaded image data is placed in ./traffic-signs-data/. Otherwise you have to change the value of image_dir in the two ipynb files.

2. Run Gereate_fake_data.ipynb first to generate the additional images.

3. Run Traffic_Sign_Classifier.ipynb. This is the main file that trains and tests the model.