/**
 * QUIXZOOM Cloud Vision Integration
 * 
 * Använder Google Cloud Vision API för objektdetektering.
 * Fallback till mock om API-nyckel saknas.
 */

const { execSync } = require('child_process');
const fs = require('fs');
const path = require('path');

class CloudVisionDetector {
  constructor(config = {}) {
    this.config = {
      apiKey: config.apiKey || process.env.GOOGLE_VISION_API_KEY,
      maxResults: config.maxResults || 50,
      ...config,
    };
    
    this.available = !!this.config.apiKey;
    this.classMap = this.buildClassMap();
  }

  buildClassMap() {
    return {
      'Street light': 'street_lamp',
      'Traffic sign': 'traffic_sign',
      'Tree': 'tree',
      'Manhole cover': 'manhole',
      'Utility pole': 'utility_box',
      'Bench': 'bench',
      'Trash can': 'trash_can',
      'Bicycle rack': 'bicycle_rack',
      'Parking meter': 'utility_box',
      'Fire hydrant': 'utility_box',
      'Light': 'street_lamp',
      'Pole': 'street_lamp',
      'Sign': 'traffic_sign',
      'Plant': 'tree',
    };
  }

  async detect(imagePath) {
    if (!this.available) {
      console.log('[Cloud Vision] No API key, using mock');
      return this.mockDetect(imagePath);
    }

    try {
      const imageData = fs.readFileSync(imagePath);
      const base64Image = imageData.toString('base64');
      
      const requestBody = {
        requests: [{
          image: { content: base64Image },
          features: [
            { type: 'OBJECT_LOCALIZATION', maxResults: this.config.maxResults },
            { type: 'LABEL_DETECTION', maxResults: 20 },
          ],
        }],
      };
      
      const response = execSync('curl -s -X POST "https://vision.googleapis.com/v1/images:annotate?key=' + this.config.apiKey + '" -H "Content-Type: application/json" -d \'' + JSON.stringify(requestBody) + '\'', {
        encoding: 'utf-8',
        timeout: 30000,
      });
      
      const result = JSON.parse(response);
      return this.parseResult(result, imagePath);
      
    } catch (error) {
      console.warn(`[Cloud Vision] Error: ${error.message}`);
      return this.mockDetect(imagePath);
    }
  }

  parseResult(result, imagePath) {
    const objects = [];
    
    if (!result.responses || !result.responses[0]) {
      return objects;
    }
    
    const response = result.responses[0];
    
    // Object localization
    if (response.localizedObjectAnnotations) {
      for (const obj of response.localizedObjectAnnotations) {
        const quixType = this.classMap[obj.name];
        if (!quixType) continue;
        
        objects.push({
          type: quixType,
          confidence: obj.score,
          bbox: this.normalizeBoundingBox(obj.boundingPoly),
          name: obj.name,
        });
      }
    }
    
    // Label detection (fallback)
    if (objects.length === 0 && response.labelAnnotations) {
      for (const label of response.labelAnnotations) {
        const quixType = this.classMap[label.description];
        if (!quixType) continue;
        
        objects.push({
          type: quixType,
          confidence: label.score,
          name: label.description,
        });
      }
    }
    
    return objects;
  }

  normalizeBoundingBox(poly) {
    if (!poly || !poly.normalizedVertices) return null;
    
    const vertices = poly.normalizedVertices;
    const xs = vertices.map(v => v.x || 0);
    const ys = vertices.map(v => v.y || 0);
    
    return {
      x: Math.min(...xs),
      y: Math.min(...ys),
      width: Math.max(...xs) - Math.min(...xs),
      height: Math.max(...ys) - Math.min(...ys),
    };
  }

  mockDetect(imagePath) {
    // Samma mock som YOLO men med mer varierande confidence
    const frameNum = parseInt(path.basename(imagePath).match(/\d+/)?.[0] || '0');
    const objects = [];
    
    const templates = [
      { type: 'street_lamp', prob: 0.6, confRange: [0.65, 0.95] },
      { type: 'traffic_sign', prob: 0.3, confRange: [0.55, 0.85] },
      { type: 'tree', prob: 0.5, confRange: [0.60, 0.90] },
      { type: 'utility_box', prob: 0.2, confRange: [0.50, 0.80] },
      { type: 'manhole', prob: 0.25, confRange: [0.45, 0.75] },
    ];
    
    const numObjects = 1 + Math.floor(Math.random() * 3);
    
    for (let i = 0; i < numObjects; i++) {
      const template = templates[Math.floor(Math.random() * templates.length)];
      
      if (Math.random() < template.prob) {
        const confidence = template.confRange[0] + Math.random() * (template.confRange[1] - template.confRange[0]);
        
        objects.push({
          type: template.type,
          confidence: confidence,
          source: 'mock',
        });
      }
    }
    
    return objects;
  }

  async detectBatch(imagePaths) {
    const results = [];
    
    for (const path of imagePaths) {
      const detections = await this.detect(path);
      results.push({
        image: path,
        objects: detections,
      });
    }
    
    return results;
  }
}

module.exports = CloudVisionDetector;