Traffic Sign Classification

In this project, i have used Convolutional Neural Network to build, train and test a traffic sign classification model

I have bhuild this model this mode using Tensorflow and keras. It is a multiclass classification problem. This model can be used to make smarter cars

Steps to build the model

1. Finding data on kaggle and loading into colab. Download Dataset Size 314MB
2. Preprocessing the image and visualizing them.
3. Finding out mean of the dimenional and resizing all images accordingly.
4. Converting the image into a numpy array and normalize them.
5. Checking class imbalance.
6. Splitting the data and performing ONE-HOT encoding
7. Creating the model architcture, compiling the model and then fitting it.
8. Plotting the accuracy and loss against each epoch.
9. Preprocessing the test data and make prediction on it.
10. Visualizing the original and predictied labels for the test image.

NOTE: Do this project on google colab because it needs more computer power