In this project, deep neural networks and convolutional neural networks are applied to classify traffic signs. The trained model should classify traffic sign images using the German Traffic Sign Dataset. After the model is trained, it is also tested on pictures found on internet.
To meet specifications, the project will require submitting three files:
- the Ipython notebook with the code Traffic_Sign_Classifier.ipynb
- the code exported as an html file Traffic_Sign_Classifier.html
- a writeup report either as a markdown or pdf file writeup.md
You're not required to use markdown for your writeup. If you use another method please just submit a pdf of your writeup.
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:
The lab environment can be created with CarND Term1 Starter Kit. Click here for the details.