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Udacity Self Driving Car Nano Degree: Classify Traffic Signs using TensorFlow

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BenniRippel/P2_Traffic_Sign_Classifier

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Project: Build a Traffic Sign Recognition Program

Udacity - Self-Driving Car NanoDegree

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 a model so it can decode traffic signs from natural images by using the German Traffic Sign Dataset. After the model is trained, you will then test your model program on new images of traffic signs you find on the web, or, if you're feeling adventurous pictures of traffic signs you find locally!

Dependencies

This project requires Python 3.5 and the following Python libraries installed:

Dataset

Download the dataset. This is a pickled dataset in which we've already resized the images to 32x32.

Code

Please find the code in the Jupyter Notebbok fie 'P2.ipynb'

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Udacity Self Driving Car Nano Degree: Classify Traffic Signs using TensorFlow

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