Project: Build a Traffic Sign Recognition Program
Overview
In this project I train and validate a model so it can classify traffic sign images using the German Traffic Sign Dataset. After the model is trained, I try out my model on images of German traffic signs that you find on the web.
- Ipython notebook with solution: Ipython notebook.
- Writeup: Traffic_Sign_Classifier.md.
The Project
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
Dependencies
This lab requires:
The lab environment can be created with CarND Term1 Starter Kit. Click here for the details.
Dataset and Repository
- 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.
- 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