For a full-stack web or app development, it requires a software firm or more
specifically a team of experienced developers to contribute a large portion of
their time and resources to design the website and then convert it to code. As
a result, the efficiency of the development team is significantly reduced when
it comes to converting UI wireframes and database schemas into an actual
working system. It would save valuable resources and fasten the overall
workflow if the clients or developers can automate this process of converting
the pre-made full-stack website design to get a partially working if not fully
working code. In this paper, we present a novel approach of generating the
skeleton code from sketched images using Deep Learning and Computer Vision
approaches. The dataset for training are first-hand sketched images of low
fidelity wireframes, database schemas and class diagrams. The approach consists
of three parts. First, the front-end or UI elements detection and extraction
from custom-made UI wireframes. Second, individual database table creation from
schema designs and lastly, creating a class file from class diagrams.

本篇论文探讨了使用深度学习和计算机视觉技术从手绘图像生成 Web 应用程序的骨架代码的新方法，以提高全栈网站开发的效率。