🏠 Virtual Architect: AI-Powered Floorplan Analysis & Recommendations

A cutting-edge AI tool that analyzes floorplans, detects architectural elements, and provides intelligent recommendations using computer vision and LLMs.

🚀 Overview

Virtual Architect is an AI-driven floorplan analysis tool that leverages FastAPI, React, Tailwind, and OpenCV to provide real-time architectural insights. Users can upload floorplans, interact with the AI assistant via chat and voice, and receive actionable design recommendations.

✨ Features

• ✅ Upload & Analyze Floorplans – Detect walls, rooms, and extract architectural elements.
• ✅ AI Chatbot – Get expert architectural advice through natural language interaction.
• ✅ Voice Mode – AI-generated responses converted to speech for better accessibility.
• ✅ Image Processing – Uses OpenCV and Tesseract OCR for feature extraction.
• ✅ Real-Time Recommendations – Optimized room layouts, traffic flow suggestions, and lighting guidance.
• ✅ Interactive UI – Built with React + TailwindCSS for a seamless user experience.

🛠 Tech Stack

Frontend

• ⚛️ React (Cursor-based)
• 🎨 TailwindCSS
• 📦 Axios for API Requests

Backend

• 🚀 FastAPI (Python)
• 🖥️ OpenCV & Pytesseract (Computer Vision & OCR)
• 🗣 gTTS (Google Text-to-Speech)
• 🧠 Groq LLaMA-3 (LLM for AI-driven recommendations)

Deployment

• 🖥 Frontend: Netlify
• 🔗 Backend: Railway (Future), Localhost (Current)

🔧 Setup & Installation

1️⃣ Clone the Repository

git clone https://github.com/yourusername/VirtualArchitect.git
cd VirtualArchitect

1️⃣ Clone the Repository
```bash
sh
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git clone https://github.com/yourusername/VirtualArchitect.git
cd VirtualArchitect

2️⃣ Backend Setup (FastAPI)

sh
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cd backend
python -m venv venv  # Create a virtual environment
source venv/bin/activate  # (Mac/Linux) Activate venv
venv\Scripts\activate  # (Windows) Activate venv
pip install -r requirements.txt  # Install dependencies

3️⃣ Frontend Setup (React)

sh
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cd ../frontend
npm install  # Install dependencies
npm run dev  # Start frontend server

4️⃣ Run Backend Server

sh
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cd backend
uvicorn app:app --reload
Backend will be available at http://localhost:8000
Frontend will be available at http://localhost:3000

🚀 Deployment

1️⃣ Deploy Backend (Railway)

• Sign up on Railway.app
• Create a new project and upload your FastAPI backend
• Add environment variables (.env file for API keys)
• Deploy & get the API URL

2️⃣ Deploy Frontend (Netlify)

• Sign up on Netlify
• Drag and drop the frontend folder in Netlify
• Set the REACT_APP_API_URL environment variable to your backend URL
• Deploy & get the website URL

📈 Future Improvements

✅ Use GPT-4V, DeepSeek, or Claude for enhanced AI reasoning.
✅ Train a custom YOLOv8 model for better room and furniture detection.
✅ Improve UI with real-time 3D modeling and drag-and-drop layout features.
✅ Optimize API response times and integrate scalable cloud hosting.

🎯 Why the FastAPI Version Was Not Deployed?

While the Gradio version was deployed on Hugging Face for quick feature validation, the FastAPI + React version requires dedicated cloud hosting for full functionality. Due to higher infrastructure requirements and costs, it is currently running locally, as shown in the documentation and demo video.

📜 License

This project is open-source and available under the MIT License.

📩 Contact

👤 Rajat
📧 Email: [email protected]
🔗 LinkedIn: linkedin.com/in/rajat-rajat12
🔗 Deployed Demo (Gradio): Virtual Architect on Hugging Face