import { EventEmitter } from 'events';

// TensorFlow.js imports - will be loaded dynamically
let tf: typeof import('@tensorflow/tfjs') | null = null;
let cocoSsd: typeof import('@tensorflow-models/coco-ssd') | null = null;

interface Detection {
  class: string;
  score: number;
  bbox: [number, number, number, number];
}

export class PresenceDetector extends EventEmitter {
  private model: Awaited<ReturnType<typeof import('@tensorflow-models/coco-ssd').load>> | null = null;
  private video: HTMLVideoElement | null = null;
  private canvas: HTMLCanvasElement | null = null;
  private context: CanvasRenderingContext2D | null = null;
  private stream: MediaStream | null = null;
  private detectionInterval: NodeJS.Timeout | null = null;
  private isRunning: boolean = false;
  private confidenceThreshold: number = 0.6;
  private personDetected: boolean = false;
  private noPersonCount: number = 0;
  private readonly NO_PERSON_THRESHOLD = 5; // Frames without person before clearing

  constructor(confidenceThreshold: number = 0.6) {
    super();
    this.confidenceThreshold = confidenceThreshold;
  }

  async start(): Promise<void> {
    if (this.isRunning) return;

    try {
      // Dynamically import TensorFlow.js
      tf = await import('@tensorflow/tfjs');
      cocoSsd = await import('@tensorflow-models/coco-ssd');

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

      // Load COCO-SSD model
      console.log('Loading COCO-SSD model...');
      this.model = await cocoSsd.load({
        base: 'lite_mobilenet_v2', // Faster, lighter model
      });
      console.log('Model loaded');

      // Set up video capture
      await this.setupCamera();

      // Start detection loop
      this.isRunning = true;
      this.startDetectionLoop();
    } catch (error) {
      console.error('Failed to start presence detection:', error);
      throw error;
    }
  }

  private async setupCamera(): Promise<void> {
    try {
      this.stream = await navigator.mediaDevices.getUserMedia({
        video: {
          width: { ideal: 640 },
          height: { ideal: 480 },
          facingMode: 'user',
        },
        audio: false,
      });

      // Create video element
      this.video = document.createElement('video');
      this.video.srcObject = this.stream;
      this.video.autoplay = true;
      this.video.playsInline = true;

      // Create canvas for processing
      this.canvas = document.createElement('canvas');
      this.canvas.width = 640;
      this.canvas.height = 480;
      this.context = this.canvas.getContext('2d');

      // Wait for video to be ready
      await new Promise<void>((resolve) => {
        if (this.video) {
          this.video.onloadedmetadata = () => {
            this.video?.play();
            resolve();
          };
        }
      });
    } catch (error) {
      console.error('Failed to setup camera:', error);
      throw error;
    }
  }

  private startDetectionLoop(): void {
    // Run detection every 500ms
    this.detectionInterval = setInterval(async () => {
      await this.detectPerson();
    }, 500);
  }

  private async detectPerson(): Promise<void> {
    if (!this.model || !this.video || !this.context || !this.canvas) return;

    try {
      // Draw current frame to canvas
      this.context.drawImage(this.video, 0, 0, this.canvas.width, this.canvas.height);

      // Run detection
      const predictions: Detection[] = await this.model.detect(this.canvas);

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

      if (personDetection) {
        this.noPersonCount = 0;
        if (!this.personDetected) {
          this.personDetected = true;
          this.emit('personDetected', personDetection);
        }
      } else {
        this.noPersonCount++;
        if (this.personDetected && this.noPersonCount >= this.NO_PERSON_THRESHOLD) {
          this.personDetected = false;
          this.emit('noPersonDetected');
        }
      }
    } catch (error) {
      console.error('Detection error:', error);
    }
  }

  async stop(): Promise<void> {
    this.isRunning = false;

    if (this.detectionInterval) {
      clearInterval(this.detectionInterval);
      this.detectionInterval = null;
    }

    if (this.stream) {
      this.stream.getTracks().forEach((track) => track.stop());
      this.stream = null;
    }

    if (this.video) {
      this.video.srcObject = null;
      this.video = null;
    }

    this.canvas = null;
    this.context = null;
    this.model = null;
  }

  isDetecting(): boolean {
    return this.isRunning;
  }

  hasPersonPresent(): boolean {
    return this.personDetected;
  }
}