import 'dart:math' as math;
import 'dart:typed_data';

import 'detection_result.dart';
import 'motion_aggregator.dart';

/// 静态场景背景建模：运行均值 + 方差，帧差高于自适应阈值的像素记为"新出现"，
/// 分块聚合为新颖区域（novelty）。
///
/// 固定机位下，常驻物体（键盘/石头/文字）永远属于背景、不产生新颖区域；
/// 走进画面的目标（野鸡移动/新出现）才会触发。比相邻帧差分更强的证据：
/// 风吹草动是持续的背景更新，不会长期标记为新颖。
class BackgroundModel {
  final int maxWidth;
  final int maxHeight;

  static const double learnRate = 0.05;
  static const double kSigma = 2.5;
  static const int minDiff = 15;
  static const int minPixels = 12;

  Float32List? _mean;
  Float32List? _var;
  int _tw = 0;

  BackgroundModel({this.maxWidth = 128, this.maxHeight = 128});

  /// 后台 isolate 用原始数据接口（与 MotionDetector 同源：直接取 planes[0]）。
  List<MotionRegion> updateRaw(
      Uint8List yPlane, int yStride, int width, int height) {
    final scale =
        maxWidth / width < maxHeight / height ? maxWidth / width : maxHeight / height;
    final tw = (width * scale).toInt().clamp(1, maxWidth);
    final th = (height * scale).toInt().clamp(1, maxHeight);
    if (tw == 0 || th == 0) return const [];

    final gray = Float32List(tw * th);
    for (var oy = 0; oy < th; oy++) {
      final sy = (oy / scale).toInt().clamp(0, height - 1);
      final idx = oy * tw;
      for (var ox = 0; ox < tw; ox++) {
        final sx = (ox / scale).toInt().clamp(0, width - 1);
        gray[idx + ox] = yPlane[sy * yStride + sx].toDouble();
      }
    }
    return update(gray, tw, th);
  }

  List<MotionRegion> update(Float32List gray, int tw, int th) {
    final n = gray.length;
    final mean = _mean;
    final variance = _var;
    if (mean == null || variance == null || mean.length != n || _tw != tw) {
      _mean = Float32List.fromList(gray);
      _var = Float32List(n);
      _tw = tw;
      return const [];
    }

    final diff = Uint8List(n);
    var fgCount = 0;
    for (var i = 0; i < n; i++) {
      final g = gray[i];
      final m = mean[i];
      final d = (g - m).abs();
      if (d > kSigma * math.sqrt(variance[i]) + minDiff) {
        diff[i] = 1;
        fgCount++;
        // 前景像素不更新背景，避免把移动目标吸收进背景
      } else {
        // 静态像素缓慢吸收进背景，适应光照漂移
        final nm = m + learnRate * (g - m);
        mean[i] = nm;
        variance[i] =
            variance[i] + learnRate * ((g - nm) * (g - nm) - variance[i]);
      }
    }

    // 全屏大变化 → 相机移动/场景切换，重建背景
    if (fgCount > n ~/ 2) {
      _mean = null;
      _var = null;
      return const [];
    }
    if (fgCount < minPixels) return const [];
    return MotionAggregator.aggregate(diff, tw, th);
  }

  /// 相机切换后重置，避免旧场景背景
  void reset() {
    _mean = null;
    _var = null;
  }
}