Customify: An AI-Powered Interior Design Platform for Photo-Based Room Redesign, Itemised Cost Estimation, and 2D Blueprint Generation
Year: 2026
Type: article
Abstract: Redecorating a home is costly, time-consuming and hard to follow for the average family: to preview a new look, the owner must engage a designer, and then separately price the furnishings and hunt for suitable products. We introduce Customify, a full stack web application that takes one photograph of a room and produces (i) a redesign preview conditioned on a chosen style, (ii) an item-by-item Indian Rupee cost estimate over three budget bands, (iii) hand-picked buying links on Indian online marketplaces, and (iv) a floor-plan blueprint that can be downloaded as a PDF. The system is split into a React.js 18 single-page front end, a FastAPI service layer protected by bcrypt-hashed passwords and JSON Web Tokens, a SQLAlchemy data layer (SQLite for development, PostgreSQL for production), and four domain modules covering image generation, costing, product recommendation and blueprint drawing. Images are produced with Stable Diffusion img2img via the Replicate API whenever a token is available; without one, a deterministic colour-grading routine takes over, so the application keeps working offline. Testing the implementation, we measured a mean end-to-end response time of 155 ms for 1080p uploads and 443 ms for 4K uploads, a mean blueprint rendering time of 36 ms for PDFs of roughly 3.6 KB, and correct behaviour in every authentication and validation check. The price engine holds exact entries for 35 of 35 furniture classes under seven style multipliers. Two shortcomings surfaced during testing; chiefly, the heuristic room-type detector returns "living room" in every case unless the user provides a hint.
Authors: Ch Koushik, K Surya Pavan, N Sai Ganesh, B Yuvaraj
Language: English
Subfield: Conservation
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7222127289
FWCI:
Cites:
Cited by:
Related to: