Raspberry Pi ALPR: Heavy Docker Images vs. Lightweight API Calls

import requests
import base64
import time

# Simulating a captured frame from the Pi Camera
# In production, this could be a direct buffer stream
def capture_and_recognize(image_path):
    try:
        print("Reading image from SD card...")
        with open(image_path, "rb") as image_file:
            base64_image = base64.b64encode(image_file.read()).decode('utf-8')

        url = "https://api.structocr.com/v1/license-plate"
        headers = {
            "x-api-key": "YOUR_API_KEY",
            "Content-Type": "application/json"
        }
        payload = {
            "img": base64_image
        }

        print("Sending to StructOCR API...")
        start_time = time.time()
        response = requests.post(url, headers=headers, json=payload)
        result = response.json()
        
        print(f"API Latency: {time.time() - start_time:.2f} seconds")

        if result.get('success'):
            plates = result['data'].get('plates', [])
            if plates:
                plate = plates[0]
                print(f"✅ Plate Found: {plate.get('plate_number')} (Normalized: {plate.get('plate_number_normalized')}) | Color: {plate.get('plate_color')}")
                print(f"Country Guess: {result['data'].get('country_guess')} | Confidence: {result['data'].get('confidence_score')}")
                # Trigger GPIO pin for gate here
            else:
                print("No plates detected in frame.")
        else:
            print(f"❌ Error: {result.get('error') or result.get('message')}")

    except Exception as e:
        print(f"System error: {e}")

# Execute
capture_and_recognize("driveway_capture.jpg")