Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64642
Volume:
10 |
6 |
Jun 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Master of Computer Applications
Vivekanandha Institute of Information and Management Studies, Tamil Nadu, India
Department of Master of Computer Applications
Vivekanandha Institute of Information and Management Studies, Tamil Nadu, India
Department of Master of Computer Applications
Vivekanandha Institute of Information and Management Studies, Tamil Nadu, India
Current Integrated Development Environments (IDEs) primarily focus on manual coding and offer limited support for converting visual designs into executable code. This creates a significant gap between design creation and implementation. To overcome this limitation, this project proposes a designer-centric IDE capable of transforming hand-drawn web layouts into structured HTML and CSS code automatically. The system utilizes deep learning techniques to identify user interface elements from sketches and preserve their spatial arrangement. A combination of feature extraction and sequence-based modeling ensures that the generated code reflects the original design accurately. Additionally, the system provides real-time execution and visual feedback, enabling faster prototyping and reducing development effort. This approach improves productivity and bridges the gap between designers and developers in modern web development workflows.
KEYWORDS
The proposed Designer-Centric IDE helps convert hand-drawn web sketches into HTML and CSS code automatically. The system combines sketch recognition, code generation, and webpage preview in a single platform. Using deep learning techniques such as FPN, ResNet-50, and Seq2Seq with Attention, the system can identify UI components and generate webpage code while maintaining the layout structure. The results show that the proposed approach supports accurate and efficient webpage development. The system reduces development time and makes the design-to-code process easier for users. In the future, the project can be improved by adding responsive webpage generation and advanced UI recognition features.
[1] A. Deolekar, K. Dhanawade, R. Chavan and S. Bhambure, "UI Code Generation using Deep Learning", International Research Journal of Engineering and Technology, vol. 8, no. 05, 2021. [2] D. Soselia, K. Saifullah, and T. Zhou, "Learning UI-To-Code Reverse Generator Using Visual Critic Without Rendering," arXiv preprint, 2023. [3] G. Vitkare, R. Jejurkar, S. Kamble, Y. Thakare and A. P. Lahare, "Automated HTML Code Generation From Hand Drawn Images Using Machine Learning Methods", vol. 04, no. 01, Jan. 2022. [4] D. S. Baulé, C. G. von Wangenheim, A. von Wangenheim, J. C. R. Hauck, and E. C. Vargas Júnior, "Automatic Code Generation from Sketches of Mobile Applications in End-User Development Using Deep Learning," arXiv preprint arXiv:2103.05704, 2021. [5] S. Patil, R. Pawar, S. Punder and J. John, "Generation of HTML Code Using Machine Learning Techniques from Mock-Up Images", International Research Journal of Engineering and Technology, vol. 7, no. 03, 2020. [6] D. Yashaswini, Sneha, and N. Kumar, "HTML Code Generation from Website Images and Sketches using Deep Learning-Based Encoder-Decoder Model," in 2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA), 2022. [7] V. Kalbande, K. Meshram, S. Somnathe, R. Deshmukh and M. Mohod, "Automatic HTML Code Generation from Mock-Up Images Using Machine Learning Techniques", International Research Journal of Engineering and Technology, vol. 8, no. 06, 2021. [8] Yong Xu, Lili Bo, Xiaobing Sun, Bin Li, Jing Jiang and Wei Zhou, "Image2Emmet: Automatic Code Generation from Web User Interface Image", Journal of Software Evolution and Process, vol. 33, e2369, 2021. [9] B. Cai, J. Luo, and Z. Feng, "A Novel Code Generator for Graphical User Interfaces," Scientific Reports, vol. 13, Article 20329, 2023.
Publication Date
6/8/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
6
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...