This repository contains a project for a class at MEF University. The goal of the project is to develop a machine learning model for recognizing German traffic signs using TensorFlow, an end-to-end open source platform for machine learning.
The dataset used in this project is the "GTSRB - German Traffic Sign Recognition Benchmark" dataset, obtained from Kaggle (https://www.kaggle.com/datasets/meowmeowmeowmeowmeow/gtsrb-german-traffic-sign). This dataset has more than 50,000 images of 43 different traffic signs.
Detailed information about the dataset can be found here
The main requirements for this project are:
- Python 3.6 or higher
- TensorFlow 2.0 or higher
- Other dependencies (numpy, pandas, etc.)
This project makes use of the "GTSRB - German Traffic Sign Recognition Benchmark" dataset available on Kaggle. The dataset can be found here.
The implementation is based on the following paper: Multi-column Deep Neural Networks for Image Classification.
This project is licensed under the MIT License - see the LICENSE file for details.