Generating Website Codes from Images

My Ha Lai Nguyen, Thien Ngoc Huynh

Abstract


Brainstorm website layout ideas usually start with everyone
giving out their mockups, and all the team members will discuss
to finalize the layout of the user interface. Once a vision of that
mockup is accepted, it is given to the designer to sketch it digitally
on computer software (i.e., Photoshop, Figma, Sketch). When
the designer completes, the developer based on the final design
to code the UI/UX of the website. As we can see, the process
requires three stages, which can be time-consuming. Therefore,
if anyone has an idea for the professional website layout, they can
visualize it by drawing on sketches. However, it can be impossible
for them to make a usable website without designers and website
developers. Due to that reason, our primary goal in this paper
is to help individuals transform their hand-drawn sketch images
into a website that can be deployed. To achieve that goal, we
present two approaches: classical computer vision techniques
and the other using a deep learning model to detect the sketch
and execute the conversion. Furthermore, our evaluation shows
that deep learning is the most promising direction. Still, classical
techniques also improve the model’s input data by applying it in
the pre-processing image.
Index Terms—Keywords: Computer vision, Hand-drawn
sketch, UI/UX, Deep learning


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DOI: http://dx.doi.org/10.21553/rev-jec.298

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