Face Recognition Backend - Railway Deployment

This is a standalone FastAPI backend for face recognition attendance system.

🚀 Quick Railway Deployment

1. Create GitHub Repository:

   • Upload all files from face-recognition-backend-deploy/ folder
   • Push to a new GitHub repository

2. Deploy to Railway:

   • Go to Railway.app
   • Click "New Project" → "Deploy from GitHub repo"
   • Select your repository
   • Railway auto-detects Python and deploys

3. Set Environment Variables in Railway:

   SUPABASE_URL=https://oxuimanrsmredzfdktxg.supabase.co
   SUPABASE_SERVICE_ROLE_KEY=your-actual-service-role-key-here
   SUPABASE_BUCKET=service-images
   MODEL_BUCKET=service-models
   CONFIDENCE_PASS=80
   

4. Get Your API URL:

   • Railway will give you a URL like: https://your-app.railway.app
   • Your API endpoints will be:
     • https://your-app.railway.app/health
     • https://your-app.railway.app/recognize
     • https://your-app.railway.app/train

🔧 Update Frontend

Update your frontend .env file:

VITE_API_FACE_RECOG=https://your-app.railway.app

📋 Files Included

• main.py - FastAPI application
• requirements.txt - Python dependencies
• app/ - Core application modules
• .env - Environment configuration (update with your values)
• README.md - This deployment guide

🧪 Test Deployment

After deployment, test with:

curl https://your-app.railway.app/health

Should return: {"status": "ok", "model_ready": false}

🎯 Next Steps

1. ✅ Deploy this backend
2. ✅ Update frontend with new API URL
3. ✅ Enroll employees using Face Recognition Setup
4. ✅ Train model and test recognition

That's it! Your face recognition backend is ready for deployment! 🚀