"""
猫叫声检测器集成模块 - 将专用猫叫声检测器集成到主系统
"""

import os
import numpy as np
from typing import Dict, Any, Optional

from src.hybrid_feature_extractor import HybridFeatureExtractor
from src.cat_sound_detector import CatSoundDetector

class IntegratedCatDetector:
    """集成猫叫声检测器类，结合YAMNet和专用检测器"""
    
    def __init__(self, detector_model_path: Optional[str] = None, 
                threshold: float = 0.5, fallback_threshold: float = 0.1):
        """
        初始化集成猫叫声检测器
        
        参数:
            detector_model_path: 专用检测器模型路径，如果为None则仅使用YAMNet
            threshold: 专用检测器阈值
            fallback_threshold: YAMNet回退阈值
        """
        self.feature_extractor = HybridFeatureExtractor()
        self.detector = None
        self.threshold = threshold
        self.fallback_threshold = fallback_threshold
        
        # 如果提供了模型路径，加载专用检测器
        if detector_model_path and os.path.exists(detector_model_path):
            try:
                self.detector = CatSoundDetector(model_path=detector_model_path)
                print(f"已加载专用猫叫声检测器: {detector_model_path}")
            except Exception as e:
                print(f"加载专用猫叫声检测器失败: {e}")
                print("将使用YAMNet作为回退方案")
    
    def detect(self, audio_data: np.ndarray) -> Dict[str, Any]:
        """
        检测音频是否包含猫叫声
        
        参数:
            audio_data: 音频数据
            
        返回:
            result: 检测结果
        """
        # 提取YAMNet特征
        features = self.feature_extractor.process_audio(audio_data)
        
        # 获取YAMNet的猫叫声检测结果
        yamnet_detection = features["cat_detection"]
        
        # 如果有专用检测器，使用它进行检测
        if self.detector is not None:
            # 使用平均嵌入向量
            embedding_mean = np.mean(features["embeddings"], axis=0)
            
            # 使用专用检测器预测
            detector_result = self.detector.predict(embedding_mean)
            
            # 合并结果
            result = {
                'detected': detector_result['detected'] or (detector_result['confidence'] > self.threshold),
                'confidence': detector_result['confidence'],
                'yamnet_confidence': yamnet_detection['confidence'],
                'yamnet_detected': yamnet_detection['detected'],
                'using_specialized_detector': True
            }
        else:
            # 仅使用YAMNet结果
            result = {
                'detected': yamnet_detection['detected'] or (yamnet_detection['confidence'] > self.fallback_threshold),
                'confidence': yamnet_detection['confidence'],
                'yamnet_confidence': yamnet_detection['confidence'],
                'yamnet_detected': yamnet_detection['detected'],
                'using_specialized_detector': False
            }
        
        # 添加YAMNet检测到的类别
        result['top_categories'] = features["top_categories"]
        
        return result