International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
GENERATION OF HTML CODE AUTOMATICALLY USING MOCK-UP IMAGES WITH MACHINE LEARNING TECHNIQUE Mr. Pritish Dinesh Sathe1, Mr. Parth Archana Kapile2, Mr. Tarun Birjuchand Uike3, Ms. Tanisha Motiram Wankhade4,Prof. Neeraj Sahu5 1-4Student
of Computer Science of Engineering Department,G. H. Raisoni University of Amravati Maharashtra Dept. of Computer Science and Engineering, G. H. Raiosni University Amravati, Maharashtra, India ---------------------------------------------------------------------***---------------------------------------------------------------------
5Professor,
Abstract - The initial step in website design is to create
Key Words: HTML Code, Machine Learning, Deep Learning, Automatic HTML Generation, CNN
modified based on the user's response. As a result, altering the structure to meet the needs of the user is a challenging task. These requirements necessitate the inclusion of improved functionalities to a website format. The concept of arranging a webpage with automated code is an intriguing research topic. Automatic webpage generation saves the time, money and resources by reducing coding time, all the tedious processes and obviously the cost. As a result of this quick pattern, the ultimate product, a website, is created in a relatively short time. In this study, we used methods for autonomously generating hand drawn graphics by generating code. Its purpose is to decrypt the system in a website format and examine the element that creates the hand drawn graphics.
1. INTRODUCTION
2. PROPOSED MODEL
Everyone in today's world understands the value of the internet. The internet and websites have become an inextricable aspect of our lives. Data, as we all know, is the new oil in today's market. The most crucial component is the website. Websites are a highly popular and significant aspect in all types of businesses. Websites are used for a variety of purposes, including education, knowledge, entertainment, and social interaction. The designing phase of a website is the first step. The initial step in the building of a website is to design its appearance. It can be done by drafting the design by hand or using any software to create mock-up images. The team of web developers will then convert these mockups into HTML code. This process continues until the intended outcomes are achieved. Our major goal in this project is to build HTML code using these photographs (images). To accomplish this, we will employ convolutional neural networks, computer vision technology, and deep learning approaches. Any website's front end is concerned with the site's users. It's important to elicit a particular level of interest from the user. It is simple to use and contains sufficient sophisticated features. Creating a webpage that provides active responses expertly, on the other hand, necessitated a long and exhausting journey. Many web developers or software specialists collaborate throughout the development of a website or a specific page to create an accurate and appealing front end. On the basis of the draught, the developers create the code to design the webpage. The generated webpage, on the other hand, can be
The major purpose here is to transform the manually drawn mock-ups into an HTML code to make a template for a website or for a front end of the website according to as it is drawn. The mock-up which contains button, text field etc., we are aiming to convert them into an HTML code. In order to transform them into HTML code to frontend template we need to use CNN model, object recognition, cropping, dilution, erosion (computer vision techniques). The work is to use object detection algorithm to detect the component from the manually drawn images. The work is to use object cropping algorithm to crop an object like text field, radio button, button etc. The object recognition algorithm works on Convolution Neural Network (CNN) to train the purposed system by using data set and it works successfully. The next work is of HTML builder algorithm and that is to convert the item which is detected by object recognition algorithm using Convolution Neural Network (CNN) model to an HTML code using HTML code builder algorithm.
mock-up images for certain web pages, either by hand or with the use of mock-up development tools. It is effectively used by developers to move mock-ups of web pages to coding. It's developing the wireframe for the layout interfaces and generating the proposed system. Computer vision and deep systematic analysis are the two most commonly employed techniques. The use of automatic code creation saves time and money. We've organized and sketched out the design. This design is cost-effective and time saving in terms of development of any website.
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