Smart Camera Service - Creao Integration

Computer vision service for capturing produce weight from scale images.

🚀 Quick Start

1. Install dependencies:

pip install -r requirements.txt

2. Start the server:

python app.py

3. Test the weight capture:

http://localhost:8001/test_weight_capture.html

📋 What It Does

• Produce Detection: Detects produce items (apples, oranges, broccoli, etc.) using YOLOv8
• Weight Capture: Extracts weight from scale images via OCR
• Creao Integration: Ready to log captured weights to your Creao database

🎯 Endpoints

1. Weight Capture API

POST http://localhost:8001/api/v1/capture/weight

Request Body:

{
  "farmer_id": "farmer123",
  "produce_name": "apples",
  "image_base64": "<base64 encoded image>"
}

Response:

{
  "status": "success",
  "farmer_id": "farmer123",
  "produce_name": "apples",
  "weight_data": {
    "weight": 5.2,
    "unit": "kg",
    "confidence": 0.95
  },
  "message": "Weight 5.2 kg captured!",
  "creao_logged": false
}

2. Real-time Produce Detection (WebSocket)

ws://localhost:8001/ws/stream

3. Test Clients

• http://localhost:8001/test_weight_capture.html - Weight capture test
• http://localhost:8001/webcam_client.html - Produce detection demo

🔧 Next Steps for Creao Integration

Phase 1: Complete OCR Implementation (Current Step)

• Install EasyOCR or Tesseract
• Implement actual OCR for scale display
• Add scale display detection using edge detection

Phase 2: Creao API Integration

• Get Creao API endpoint documentation
• Implement log_to_creao() function
• Add authentication (API key/token)
• Test data flow: Camera → API → Creao DB

Phase 3: Mobile Integration

• Add "Capture Weight" button to Creao mobile app
• Implement camera capture on mobile
• Add real-time feedback to farmer

📁 Files

• app.py - FastAPI server with weight capture endpoint
• test_weight_capture.html - Weight capture test client
• webcam_client.html - Produce detection demo
• requirements.txt - Python dependencies