Interactive lab for exploring gradient-domain image editing and simple synthetic-image detection. The Python backend handles gradient computation, Poisson-based reconstruction, and lightweight analysis; the Next.js frontend focuses on visualization and user interaction.

• backend/ — FastAPI service with gradient ops, Poisson solver, and analysis utilities
• frontend/ — Next.js App Router UI (lab, analyzer, about)
• Docs/ — architecture, frontend, and backend guides (English)

Requirements: Python 3.11+ recommended.

python -m venv .venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows
pip install -r backend/requirements.txt

Run the API (auto-creates static folders on startup):

uvicorn backend.main:app --reload --port 8000

The app mounts static assets at /static and exposes routes for image upload, gradient computation, reconstruction, and analysis.

Requirements: Node.js 18+ (Next.js 16) and npm.

cd frontend
npm install
npm run dev -- --port 3000

Configuration:

• API base URL: NEXT_PUBLIC_API_URL (defaults to http://localhost:8000). Set it in .env.local inside frontend/ if the backend runs elsewhere.

Main routes:

• / — intro and entry points
• /lab — gradient editing lab (upload, view dx/dy, edit, reconstruct)
• /analyzer — synthetic analyzer (compare gradients/heatmaps, show scores)
• /about — short backgrounder

• POST /api/images — upload an image, returns imageId and dimensions
• GET /api/gradients?imageId=... — compute dx/dy and visualizations
• POST /api/reconstruct — send edited gradients and receive reconstructed image URL
• POST /api/analyze — get simple gradient-based scores and optional heatmap

• Docs/Architecture.md — high-level system view
• Docs/Backend.md — backend design and API details
• Docs/Frontend.md — frontend routing, components, and UX guidance