技术架构

import numpy as np
from openface import FaceAlignment
from models import WindowBlockLSTM

class DepressionRiskAssessor:
    def __init__(self):
        self.au_extractor = FaceAlignment(device='cuda')
        self.lstm_model = WindowBlockLSTM.load_pretrained(
            'whispercare_v3.pth'
        )
    
    def assess(self, face_frames):
        # 提取 40 维 AU 特征序列
        au_sequence = self.au_extractor.extract_batch(face_frames)
        
        # 关键 AU 加权（基于论文5 IG 排序）
        risk_weights = {'AU26': 0.32, 'AU20': 0.28, 'AU07': 0.21}
        protective_weights = {'AU06': 0.18, 'AU12': 0.15}
        
        # LSTM 时序建模 + 概率融合
        risk_prob = self.lstm_model.predict(au_sequence)
        return {'risk_level': int(risk_prob * 3), 'probability': risk_prob}