import numpy as np

class DistributionChangeDetector:
    def __init__(self, baseline_windows: list[np.ndarray]):
        """
        参数 baseline_windows: List of arrays，代表初始稳定期的多个窗口
        """
        self.baseline = self._compute_baseline(baseline_windows)

    def _compute_stats(self, window: np.ndarray) -> tuple[float, float, float]:
        """返回 (P_under30, std, mode)"""
        p_under30 = np.mean(window < 30)
        std = np.std(window, ddof=1)
        
        # 快速估计众数：最大 bin 的中心
        hist, bin_edges = np.histogram(window, bins=50)
        max_bin_index = np.argmax(hist)
        mode_est = (bin_edges[max_bin_index] + bin_edges[max_bin_index + 1]) / 2
        return p_under30, std, mode_est

    def _compute_baseline(self, windows: list[np.ndarray]) -> tuple[np.ndarray, np.ndarray]:
        """
        返回 baseline 向量 (P0, σ0, mode0) 和对应标准差（用于归一化）
        """
        stats = np.array([self._compute_stats(w) for w in windows])
        mean = stats.mean(axis=0)
        std = stats.std(axis=0) + 1e-6  # 防止除0
        return mean, std

    def update(self, window: np.ndarray) -> float:
        """
        输入：当前窗口数据（长度 = 窗口大小）
        输出：变化分数（越大表示分布越偏离基准）
        """
        x = np.array(self._compute_stats(window))
        mean, std = self.baseline
        norm_diff = (x - mean) / std
        change_score = np.linalg.norm(norm_diff)
        return float(change_score)


import cv2
def gen_data():
    cap = cv2.VideoCapture()
    cap.open(1)
    while True:
        ret, frame = cap.read()
        cv2.imshow("Camera Feed", frame)
        if not ret:
            break
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        s = hsv[:, :, 1]  # 直接提取饱和度通道
        s = s[s > 0]  # 只保留非零饱和度值，减少噪声
        yield s
        if cv2.waitKey(1) & 0xFF == ord('a'):
            break


gen = gen_data()
baseline_data = [gen.__next__() for _ in range(5)]  # 获取10个窗口作为基线

det = DistributionChangeDetector(baseline_data)



results = []
for x in gen:
    out = det.update(x)
    if out is not None:
        results.append(out)


# 作图查看
import matplotlib.pyplot as plt
plt.plot(results, label="ChangeScore")
plt.xlabel("Window index")
plt.ylabel("Score")
plt.title("Streaming Change Detection")
plt.legend()
plt.show()