Classification and Separation of Whatsapp Images Using Machine Learning

In this digital era, Internet has become an integral part of human lives. Internet and social networks have become very popular, allowing anyone to easily share pictures, text, audio and video files. Among all the applications, WhatsApp has become quite famous due to its ease of use and it has replaced almost all the other messaging apps. Apart from sending messages, images and videos over it, one more reason for the heavy usage of WhatsApp is the exchange of study notes and materials by the students during the time of the examination and end up with a lot of images to be deleted at the end of each semester. And also the notices and brochures in every semester gets mixed up with other images and these needs to be separated for easy reference. As the WhatsApp folder may have many other images, selecting the study material images, brochures, etc., one by one from the other images and then deleting them is a tedious process. Henceforth, this research work has utilized machine learning to build a model for detecting and extracting the images from the WhatsApp images folder. Further, the proposed model classifies the study notes images into printed and handwritten notes. Notices and brochures received on WhatsApp are separated into a new folder. And also, screenshots and photos are grouped into separate folders. The proposed model has been built by using a deep learning concept called the Convolutional Neural Network [CNN] and by using Python’s Keras library. It takes an image and decides its category and then the action is taken accordingly.