An image classifier that can classify various traffic symbols present on the road , built by keeping in mind how automated vehicles can use these for more effortless user experience .
In this we will build a deep neural network model that can classify traffic signs present in the image into different categories. With this model, we are able to read and understand traffic signs which are a very important task for all autonomous vehicles.
https://www.kaggle.com/meowmeowmeowmeowmeow/gtsrb-german-traffic-sign
The dataset contains more than 50,000 images of different traffic signs. It is further classified into 43 different classes. The dataset is quite varying, some of the classes have many images while some classes have few images. The size of the dataset is around 300 MB. The dataset has a train folder which contains images inside each class and a test folder which we will use for testing our model.
- Get the dataset from here- https://www.kaggle.com/meowmeowmeowmeowmeow/gtsrb-german-traffic-sign
- Get the requirements installed.
- To run the pretrained model you can directly run GUI.py
- You can also train your own model following the notebook.
We have achieved an accuracy of 97% on the training dataset and 94% on the test dataset.