In this Project, we will try to sort the German Traffic Signs using a Convolutional Neural Network.
In this Project, we will try to sort the German Traffic Signs from this database using a Convolutional Neural Network.
In order to open and interact with this algorithm you will need to follow the following steps:
Step 1: Set up the CarND Term1 Starter Kit if you haven't already.
Step 2: Open the code in a Jupyter Notebook
If you are unfamiliar with Jupyter Notebooks, you can check out Udacity's free course on Anaconda and Jupyter Notebooks to get started.
Jupyter is an Ipython notebook where you can run blocks of code and see results interactively. All the code for this project is contained in a Jupyter notebook. To start Jupyter in your browser, use terminal to navigate to your project directory and then run the following command at the terminal prompt (be sure you've activated your Python 3 carnd-term1 environment as described in the CarND Term1 Starter Kit installation instructions!):
> jupyter notebook
A browser window will appear showing the contents of the current directory. Click on the file called "P1.ipynb". Another browser window will appear displaying the notebook.
Follow the instruction in the Traffic_Sign_Classifier.ipynb notebook to watch and/or improve the visual recognition algorithm.
Check also the Report.md for explaination on the algorithm.