🎯 Multi-Gauge Detection

import cv2
import numpy as np
from gaugesnap import MultiGaugeDetector

# Initialize multi-gauge detector
detector = MultiGaugeDetector(
    max_gauges=50,
    min_confidence=0.85,
    enable_gpu=True
)

# Load and process image
image = cv2.imread('control_panel.jpg')
results = detector.detect_and_read(image)

# Process results
for gauge in results:
    print(f"Gauge ID: {gauge['id']}")
    print(f"Type: {gauge['type']}")
    print(f"Position: {gauge['bbox']}")
    print(f"Value: {gauge['value']}")
    print(f"Confidence: {gauge['confidence']:.2f}")
    print(f"Timestamp: {gauge['timestamp']}")
    print("---")

# Real-time monitoring
def monitor_gauges():
    cap = cv2.VideoCapture(0)
    while True:
        ret, frame = cap.read()
        if ret:
            results = detector.detect_and_read(frame)
            
            # Check for alerts
            for gauge in results:
                if gauge['alert_status']:
                    send_alert(gauge)
            
            # Update database
            update_database(results)
            
            time.sleep(1)  # Check every second