Automated Code Generation for User Interfaces on Embedded Devices

The project focuses on developing a machine learning model to automate the generation of code for embedded user interfaces. The primary goal is to streamline the workflow between design and development by predicting and producing code from input data, such as screenshots and API data extracted from design files. This initiative aims to bridge the gap between design and development, enhancing efficiency in creating embedded systems. By automating the code generation process, the project seeks to reduce manual coding efforts, minimize errors, and accelerate the development timeline. The project will provide learners with an opportunity to apply their knowledge of machine learning, embedded systems, and UI design in a practical setting. The tasks involved are closely related and can be completed by a team of learners specializing in computer science or software engineering.