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