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