Using an existing model Inception V3, that is a convolutional neural network (CNN) that was developed by Google in 2016. It was trained on the ImageNet dataset, which contains over 1.2 million images labeled with 1000 different object categories. It is also a popular choice for transfer learning, which is a technique for using a pre-trained model as a starting point for training a new model on a different task.
Added additional layers to the pretrained Inception Model to customise to this specific dataset.
The model performed decently well, averaging around high 80s to 90% accuracy.
