The keras model is created by training SmallerVGGNet from scratch on around 2200 images (~1100 for each class) gathered from Google Images. It acheived around 95% training accuracy and ~85% validation accuracy. (20% of the dataset is used for validation)
- numpy
- opencv-python
- tensorflow
- keras
Install the required packages by executing the following command.
$ pip install -r requirements.txt

