imperial-command-center/src/hooks/useLocalPresence.ts

import { useEffect, useRef, useState, useCallback } from 'react';
import { useSettingsStore } from '@/stores/settingsStore';

interface UseLocalPresenceOptions {
  enabled?: boolean;
  confidenceThreshold?: number;
  checkIntervalMs?: number;
  onPersonDetected?: () => void;
  onPersonCleared?: () => void;
}

/**
 * Hook for local presence detection using TensorFlow.js COCO-SSD model.
 * Uses the Kitchen_Panel go2rtc stream instead of direct webcam access
 * (since mediamtx uses the webcam for streaming).
 */
export function useLocalPresence({
  enabled = true,
  confidenceThreshold = 0.5,
  checkIntervalMs = 2000,
  onPersonDetected,
  onPersonCleared,
}: UseLocalPresenceOptions = {}) {
  const [isDetecting, setIsDetecting] = useState(false);
  const [hasPersonPresent, setHasPersonPresent] = useState(false);
  const [error, setError] = useState<string | null>(null);

  const canvasRef = useRef<HTMLCanvasElement | null>(null);
  const imgRef = useRef<HTMLImageElement | null>(null);
  const modelRef = useRef<any>(null);
  const intervalRef = useRef<ReturnType<typeof setInterval> | null>(null);
  const noPersonCountRef = useRef(0);
  const wasPersonPresentRef = useRef(false);

  const go2rtcUrl = useSettingsStore((state) => state.config.go2rtcUrl);

  const NO_PERSON_THRESHOLD = 3; // Frames without person before clearing

  const detectPerson = useCallback(async () => {
    if (!modelRef.current || !canvasRef.current || !imgRef.current) return;

    const ctx = canvasRef.current.getContext('2d');
    if (!ctx) return;

    try {
      // Fetch a frame from go2rtc MJPEG snapshot
      const snapshotUrl = `${go2rtcUrl}/api/frame.jpeg?src=Kitchen_Panel&t=${Date.now()}`;

      // Load image
      await new Promise<void>((resolve, reject) => {
        if (!imgRef.current) return reject('No image element');
        imgRef.current.crossOrigin = 'anonymous';
        imgRef.current.onload = () => resolve();
        imgRef.current.onerror = () => reject('Failed to load frame');
        imgRef.current.src = snapshotUrl;
      });

      // Draw to canvas
      ctx.drawImage(imgRef.current, 0, 0, 320, 240);

      // Run detection
      const predictions = await modelRef.current.detect(canvasRef.current);

      // Check for person with sufficient confidence
      const personDetection = predictions.find(
        (p: any) => p.class === 'person' && p.score >= confidenceThreshold
      );

      if (personDetection) {
        noPersonCountRef.current = 0;
        if (!wasPersonPresentRef.current) {
          wasPersonPresentRef.current = true;
          setHasPersonPresent(true);
          console.log('Local presence: Person detected via go2rtc stream');
          onPersonDetected?.();
        }
      } else {
        noPersonCountRef.current++;
        if (wasPersonPresentRef.current && noPersonCountRef.current >= NO_PERSON_THRESHOLD) {
          wasPersonPresentRef.current = false;
          setHasPersonPresent(false);
          console.log('Local presence: Person cleared');
          onPersonCleared?.();
        }
      }
    } catch (err) {
      // Silently fail on individual frame errors - stream might be briefly unavailable
      console.debug('Detection frame error:', err);
    }
  }, [go2rtcUrl, confidenceThreshold, onPersonDetected, onPersonCleared]);

  const startDetection = useCallback(async () => {
    if (isDetecting) return;

    try {
      setError(null);

      // Dynamically import TensorFlow.js and COCO-SSD
      const tf = await import('@tensorflow/tfjs');
      const cocoSsd = await import('@tensorflow-models/coco-ssd');

      // Set backend
      await tf.setBackend('webgl');
      await tf.ready();

      // Load model (lite version for speed)
      console.log('Loading COCO-SSD model for presence detection...');
      modelRef.current = await cocoSsd.load({
        base: 'lite_mobilenet_v2',
      });
      console.log('Model loaded');

      // Create hidden image element for loading frames
      imgRef.current = document.createElement('img');

      // Create canvas for processing
      canvasRef.current = document.createElement('canvas');
      canvasRef.current.width = 320;
      canvasRef.current.height = 240;

      // Start detection loop
      setIsDetecting(true);
      intervalRef.current = setInterval(detectPerson, checkIntervalMs);

      console.log('Local presence detection started (using go2rtc Kitchen_Panel stream)');
    } catch (err) {
      const message = err instanceof Error ? err.message : 'Failed to start presence detection';
      console.error('Presence detection error:', message);
      setError(message);
    }
  }, [isDetecting, checkIntervalMs, detectPerson]);

  const stopDetection = useCallback(() => {
    if (intervalRef.current) {
      clearInterval(intervalRef.current);
      intervalRef.current = null;
    }

    canvasRef.current = null;
    imgRef.current = null;
    modelRef.current = null;
    setIsDetecting(false);
    setHasPersonPresent(false);
    wasPersonPresentRef.current = false;
    noPersonCountRef.current = 0;

    console.log('Local presence detection stopped');
  }, []);

  // Start/stop based on enabled prop
  useEffect(() => {
    if (enabled) {
      startDetection();
    } else {
      stopDetection();
    }

    return () => {
      stopDetection();
    };
  }, [enabled, startDetection, stopDetection]);

  return {
    isDetecting,
    hasPersonPresent,
    error,
    startDetection,
    stopDetection,
  };
}