Image Modeling Application

Azati developed a mobile and web application for an interior design agency that allows users to instantly change room wallpapers on photos taken with their smartphones. The application leverages AI and computer vision to perform semantic segmentation and realistic visualization of wallpaper replacements.

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All Technologies Used

Python
Python
OpenCV
OpenCV
Theano
Theano
Caffe
Caffe

Motivation

The client approached Azati to create an intuitive and fast application that empowers users to visualize new wallpaper designs in real-world interiors instantly, using only a smartphone photo and without the need for complex rendering tools.

Main Challenges

Challenge 1
Lengthy 3D rendering delays

Clients frequently request realistic previews of interior designs, particularly with new wallpapers, but traditional 3D rendering takes several days and is expensive. Azati proposed creating a lightweight AI-based application that could deliver results in seconds using a smartphone camera.

Challenge 2
Limited customization in design apps

Existing mobile apps only work with predefined interior images and lack customization, which fails to meet client expectations. Azati suggested implementing instant modeling through semantic segmentation and lighting-aware rendering to achieve photorealistic, user-specific results.

Key Features

  • Real-Time Visualization: Instantly changes wallpaper on user photos without manual editing.
  • AI-Powered Segmentation: Detects structural room elements like walls, niches, and arches to apply textures accurately.
  • Smart Lighting & Depth Detection: Ensures wallpapers blend naturally with existing lighting and wall geometry.
  • Multiple Wallpaper Options: Supports various colors, textures, and patterns for flexible interior design preview.

Our Approach

Cross-Platform Application Design
Designed a cross-platform application working on both smartphones and browsers for maximum accessibility.
Semantic Segmentation with AI
Used AI-driven semantic segmentation to analyze room structure, recognizing walls, ceiling, floor, and various decorations.
Lighting and Depth Optimization
Incorporated lighting and depth analysis to ensure that new wallpapers are applied naturally and realistically.
Real-Time Visualization Interface
Developed an intuitive interface allowing users to try multiple wallpaper options in real-time.
Instant Photo-Based Rendering
Enabled instant application of wallpaper patterns and textures to user-uploaded photos, significantly reducing time-to-visualization.

Project Impact

Time Efficiency: Reduced interior visualization time from days to seconds, streamlining the client approval process.

Enhanced Customer Experience: Enabled clients to interactively test design options and make decisions faster.

Digital Innovation in Design: Replaced traditional 3D rendering with accessible AI-based modeling, democratizing design visualization.

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