Only a few decades ago it seemed impossible to automatically classify bird species in images, let computers translate texts from German to English in a way that doesn’t insult readers, or ask voice assistants for tomorrow’s weather. All these applications were enabled by the rise of Deep Learning. When it comes to state-of-the-art results in analyzing unstructured data – the kind you find in images, audio or text – deep neural networks are the way to go. Fortunately, together with progress in research, frameworks like Tensorflow and PyTorch emerged to ease development. It is now possible to download pre-trained models from the internet, fit them to one’s need or just use them.

Tensorflow Lite is an inference framework that makes it possible to run such models on embedded hardware and mobile devices. Its C++ API makes it easy to integrate use-cases like computer vision or keyphrase detection into applications written with Qt.

In the talk we explain the use of Tensorflow Lite with Qt and QML, and demonstrate how everything works fluently on low-level hardware such as the Raspberry Pi.

OpenAPI (aka Swagger) is a widely used technology to implement APIs in a cloud context. It provides a structured, integrated and language-agnostic way to design, test and maintain HTTP APIs based on an interface definition language (IDL). One of the main selling points of OpenAPI is the ability to generate server-/client-side code for various languages and frameworks based on a common IDL. Typical use-cases from a Qt perspective are desktop or mobile applications that interact with a cloud-based service.

This tutorial will provide an overview of OpenAPI in general, its root in the Swagger project, the tools of the ecosystem, and how to best work with it in the context of a Qt application. In a hands-on session we will review an existing API using Swagger-UI, generate Qt-specific client code, and wrap everything up into a working Qt Quick HMI. We will also present our ongoing work on improving the Qt support within the OpenAPI ecosystem.