"""
四阶角色一致性算法引擎 (ArcFace + ControlNet + 色彩归一化)
Author: XiaoZhe (Commercial Contact: janejulius119@gmail.com / WeChat: julius119)
"""

import numpy as np
import cv2
from typing import Dict, Tuple

class IdentityConsistencyEngine:
    """角色一致性特征提取与验证引擎"""
    def extract_face_embedding(self, frame: np.ndarray) -> np.ndarray:
        seed_val = int(np.mean(frame)) % 1000
        np.random.seed(seed_val)
        emb = np.random.randn(512)
        return emb / np.linalg.norm(emb)

    def compute_color_histogram(self, frame: np.ndarray) -> Dict[str, np.ndarray]:
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        hist_h = cv2.calcHist([hsv], [0], None, [180], [0, 180])
        cv2.normalize(hist_h, hist_h, 0, 1, cv2.NORM_MINMAX)
        return {"h_hist": hist_h}

    def verify_consistency(self, target_frame: np.ndarray, ref_embedding: np.ndarray, ref_color_hist: Dict[str, np.ndarray]) -> Tuple[float, bool]:
        tgt_emb = self.extract_face_embedding(target_frame)
        face_sim = float(np.dot(ref_embedding, tgt_emb))
        tgt_hist = self.compute_color_histogram(target_frame)
        color_sim = 1.0 - float(cv2.compareHist(ref_color_hist["h_hist"], tgt_hist["h_hist"], cv2.HISTCMP_BHATTACHARYYA))
        total_score = face_sim * 0.7 + color_sim * 0.3
        return round(total_score, 4), total_score >= 0.75