A single function to streamline image classification with Keras

Therefore, in this article, we focus on how to use a couple of utility methods from the Keras (TensorFlow) API to streamline the training of such models (specifically for a classification task) with a proper data pre-processing. In the end, we aim to write a single utility function, which can take just the name of your folder where training images are stored, and give you back a fully trained CNN model. We use a dataset consisting of 4000 images of flowers for this demo. The dataset can be downloaded from the Kaggle website here. The data collection is based on the data Flickr, Google images, Yandex images.