metadata
title: Idd
emoji: 🌍
colorFrom: purple
colorTo: indigo
sdk: docker
pinned: false
EL HELAL Studio - FastAPI Backend
A headless, production-ready FastAPI backend for AI-powered ID card photo processing.
Quick Start
pip install -r requirements.txt
uvicorn main:app --reload
Open http://localhost:8000/docs for the interactive Swagger UI.
Endpoints
| Method | Path | Description |
|---|---|---|
| GET | /status | Check if AI models are loaded |
| POST | /upload | Upload an image, returns thumbnail |
| POST | /process/{file_id} | Run full AI pipeline |
| GET | /settings | Get pipeline settings |
| POST | /settings | Update settings |
| GET | /frames | List frame overlays |
| POST | /frames | Upload a frame |
| DELETE | /frames/{filename} | Delete a frame |
| POST | /clear-all | Purge all uploads/results |
| POST | /backup/export | Export config+assets as ZIP |
| POST | /backup/import | Import a backup ZIP |
Full endpoint reference: see API_REFERENCE.md.
Docker
docker-compose up --build
API will be available at http://localhost:8000.
Testing
The project includes both a mocked unit test suite (runs instantly without loading deep learning models) and a full end-to-end integration test suite.
1. Mocked Unit & API Tests
Runs without GPU or external model weight downloads:
venv\Scripts\python.exe -m unittest discover -s tests -p "test_*.py"
2. End-to-End Integration Tests
Requires the local Uvicorn server to be running on port 9000:
venv\Scripts\python.exe test_api.py
i d - m a k e r - 2
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference # ID-pushed-to-hg