Udacity Self Driving Car Nano Degree Project 3: Traffic Sign Classification

In this project, I used deep neural networks and convolutional neural networks to classify traffic signs. I trained and validated a model so it can classify traffic sign images using the German Traffic Sign Dataset. After the model is trained, I tried out my model on images of German traffic signs that I find on the web.

We have included an Ipython notebook that contains further instructions and starter code. I downloaded the Ipython notebook.

A detailed writeup of the project was created named 'writeup_template.md'. I checked out the writeup template for this project and used it as a starting point for creating my own writeup.

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

A great writeup should include the rubric points as well as the description of how I addressed each point. It includes a detailed description of the code used in each step (with line-number references and code snippets where necessary), and links to other supporting documents or external references. I also include images in the writeup to demonstrate how my code works with examples.

The goals / steps of this project are the following:

• Load the data set
• Explore, summarize and visualize the data set
• Design, train and test a model architecture
• Use the model to make predictions on new images
• Analyze the softmax probabilities of the new images
• Summarize the results with a written report

This lab requires:

• CarND Term1 Starter Kit

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

1. Download the data set. The classroom has a link to the data set in the "Project Instructions" content. This is a pickled dataset in which we've already resized the images to 32x32. It contains a training, validation and test set.
2. Clone the project, which contains the Ipython notebook and the writeup template.

git clone https://github.com/udacity/CarND-Traffic-Sign-Classifier-Project
cd CarND-Traffic-Sign-Classifier-Project
jupyter notebook Traffic_Sign_Classifier.ipynb

Follow the instructions in the Traffic_Sign_Classifier.ipynb notebook and write the project report using the writeup template as a guide, writeup_template.md. Submit the project code and writeup document.

A well written README file can enhance your project and portfolio. Develop your abilities to create professional README files by completing this free course.