Automatic HTML Code Generation from Hand Drawn Images using Machine Learning Methods
Author(s):
M Keerthana, Vishwanath R, Monisha B, Bhavanashree R, Dr. Malatesh S H, Dr. Aruna M G
Keywords:
HTML Code Generation from Hand Drawn Images using Machine Learning
Abstract
The production of individual web page mock-ups, which can be done by hand or with the aid of graphic design and professional mock-up creation tools, is the first stage in the website design process. The mock-ups are then converted into structured HTML or similar mark-up code by software engineers. Typically, this method is performed multiple times until the required template is achieved. The purpose of this review is to make the process of developing code from hand-drawn mock-ups more automated. Hand drawn mock-ups are processed using computer vision techniques, and the recommended system is built using deep learning techniques. The building of a preliminary drawing of each web page, which can be done using design tools or by hand. After that, corresponding code for the web page draught is written. This procedure is difficult, expensive, and time-consuming. Consequently, the suggested system will automate this operation. A hand-drawn drawing of a form is provided as input, which is analysed, and several components revealed. After the components have been discovered, deep learning CNN techniques are used to crop and recognize them. When the matching component is identified.
Article Details
Unique Paper ID: 160241

Publication Volume & Issue: Volume 10, Issue 1

Page(s): 235 - 240
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