At our daughter company, idealo.de, we store and display millions of images. Our gallery contains pictures of all sorts. You’ll find there vacuum cleaners, bike helmets as well as hotel rooms. Working with huge volume of images brings some challenges: How to organize the galleries? What exactly is in there? Do we actually need all of it?
To tackle these problems you first need to label all the pictures. In 2018 our Data Science team completed four projects in the area of image classification. In 2019 there were many more to come. Therefore, we decided to automate this process by creating a software we called Image ATM (Automated Tagging Machine). With the help of transfer learning, Image ATM enables the user to train a Deep Learning model without knowledge or experience in the area of Machine Learning. All you need is data and spare couple of minutes!
In this talk we will discuss the state-of-art technologies available for image classification and present Image ATM in the context of these technologies. We will then give a crash course of our product where we will guide you through different ways of using it – in shell, on Jupyter Notebook and on the Cloud. We will also talk about our roadmap for Image ATM.
Key Takeaways:
- Learn how to use Image ATM e.g. which kind of input is needed, preprocessing, training and then evaluation
- Learn how you can contribute to it as well
- Learn about our image classification problems
Check out the below video to know more about the session.
