Implementation of a Convolutional Neural Network for classification of traffic signs using Keras.
Code can be accessed through the provided Jupyter Notebook file.
- Keras
- OpenCV
- Matplotlibb
- Numpy
- Tensorflow
- Pandas
- Seaborn
- imageio
- GTSRB dataset is used in this project.
- Download the dataset here and update dataset folder location in the notebook.
- Original dataset source: http://benchmark.ini.rub.de/?section=gtsrb&subsection=dataset
- The dataset consists of 43 different classes of images.
Following is the summary of the Convolutional Neural Network model used for this problem:
A random sample from the prediction results of the trained model is below:
- J. Stallkamp, M. Schlipsing, J. Salmen, and C. Igel. The German Traffic Sign Recognition Benchmark: A multi-class classification competition. In Proceedings of the IEEE International Joint Conference on Neural Networks, pages 1453–1460. 2011.
👤 Asad Bin Khalid
- Github: @asadbinkhalid
👤 Fatima Junaid
- Github: @faatimaajunaid