Customify: An AI-Powered Interior Design Platform for Photo-Based Room Redesign, Itemised Cost Estimation, and 2D Blueprint Generation

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

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-15
DOI
https://doi.org/10.5281/zenodo.23388588
Primary Topic
Architecture, Design, and Social History
Type
article
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article

Customify: An AI-Powered Interior Design Platform for Photo-Based Room Redesign, Itemised Cost Estimation, and 2D Blueprint Generation

N Sai Ganesh, Ch Koushik, K Surya Pavan, B Yuvaraj
Zenodo (CERN European Organization for Nuclear Research)
Architecture, Design, and Social History
article

Customify: An AI-Powered Interior Design Platform for Photo-Based Room Redesign, Itemised Cost Estimation, and 2D Blueprint Generation

N Sai Ganesh, Ch Koushik, K Surya Pavan, B Yuvaraj
article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 3%
Architecture, Design, and Social History
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