Spatial Image Enhancer Pro

Production-grade public SPA for spatial-domain image enhancement using Django REST Framework, OpenCV, NumPy, React, Tailwind CSS, Celery, Redis, PostgreSQL, Docker Compose, and Caddy.

Local Development

Backend:

cd backend
python -m venv .venv
.venv\Scripts\activate
copy .env.sample .env
pip install -r requirements.txt
python manage.py migrate
python manage.py runserver

Frontend:

cd frontend
copy .env.sample .env
npm install
npm run dev

Open http://localhost:5173. The frontend .env uses VITE_API_BASE=http://localhost:8000, and the backend .env allows that origin via CORS/CSRF settings.

Docker

copy .env.example .env
copy backend\.env.sample backend\.env
docker compose up --build

Caddy serves the SPA and proxies /api/* and /media/*. Set CADDY_DOMAIN, DJANGO_ALLOWED_HOSTS, DJANGO_CSRF_TRUSTED_ORIGINS, CORS_ALLOWED_ORIGINS, and a strong DJANGO_SECRET_KEY before production deployment.

For production, use .env.sample as the root Compose template and backend/.env.production.sample as the backend-only template.

Backend Structure

The Django app follows the HackSoftware Django Styleguide pattern:

• API views validate request input and return responses.
• processing/services.py contains business workflows and writes.
• processing/selectors.py contains database fetch helpers.
• Settings are environment-driven through backend/.env.

API

• POST /api/images/
• POST /api/process/
• POST /api/batch/
• GET /api/jobs/{job_id}/

Images are stored as ephemeral sessions and removed by the cleanup task after the configured TTL.