AI-Driven-Interior-Decor Tailwind Templates

Ai Driven Interior Decor

AI-Driven Interior Decor (DecoCraft) is a web app that generates personalized interior designs from room photos using Stable Diffusion, LoRA, and ControlNet. Built with Next.js, Tailwind CSS, Replicate API, and ByteScale.

DecorCraft Logo DecoCraft – AI-Driven Interior Decor Generator

DecorCraft is a web-based application that leverages Generative AI to help users visualize customized interior designs. By uploading a photo of a room and selecting a preferred style, users can generate culturally aware and aesthetically refined design layouts using Stable Diffusion models fine-tuned with LoRA and enhanced via ControlNet.


🚀 Features

  • Upload a room image and choose design preferences
  • Generate AI-based interior designs in seconds
  • View, compare, and download the output
  • Responsive UI built with modern web technologies
  • Hosted AI model on Replicate, image storage via ByteScale

🛠️ Tech Stack

Layer Technologies Used
Frontend TypeScript, Next.js (App Router), Tailwind CSS
AI Model Stable Diffusion, LoRA, ControlNet
Backend/API Replicate API (model inference), ByteScale API (uploads)
Tools Used Auto1111, ComfyUI, KhoyaSS (for training and testing)
Hosting Replicate (Model), ByteScale (Storage)

📦 Installation & Setup

1. Clone the repository

git clone https://github.com/vishwaah/AI-Driven-Interior-Decor.git
cd AI-Driven-Interior-Decor

2. Install dependencies

npm install

3. Configure environment variables

Create a .env.local file in the root directory and add:

REPLICATE_API_TOKEN=your_replicate_api_key
BYTESCALE_PUBLIC_KEY=your_bytescale_api_key

4. Run the development server

npm run dev

Visit http://localhost:3000 to use the app locally.


⚙️ Model Deployment

  • The LoRA fine-tuned Stable Diffusion model is hosted on Replicate.
  • ControlNet integration enhances structural consistency based on room layout.
  • Image uploads are securely handled via ByteScale.

✅ Functional Requirements

  • Upload image and receive AI-generated output
  • Choose room type and style
  • Compare input and output
  • Download final design image

🔐 Non-Functional Requirements

  • Responsive and accessible UI
  • Secure API key and data handling
  • Average generation time: < 20 seconds
  • Scalable for multi-user access

📃 License

This project is licensed under the MIT License.


💡 Acknowledgements


🌐 DecorCraft – Redefining interior design through AI ✨

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