In this project, deep neural networks and convolutional neural networks were used to classify traffic signs. Specifically, a model was trained to classify traffic signs from the German Traffic Sign Dataset.
This project requires Python 3.5 with the following libraries installed:
You will also need to have software installed to run and execute a Jupyter Notebook.
The completed code is provided in the notebook Traffic_Signs_Recognition.ipynb notebook file.
Another tutorial code is also provided in the notebook traffic-sign-classification-with-keras.ipynb notebook file. This code requires Keras library installed.
Make sure you are in the top-level project directory Udacity_SDCND_traffic-signs/ (that contains this README). Then run:
jupyter notebook Traffic_Signs_Recognition.ipynb
The contents of this repository are covered under the MIT License.