Clean/lib/handler/photo_scan_handler.dart

import 'dart:async';
import 'dart:io';

import 'package:classify_photo/classify_photo.dart';
import 'package:clean/widget/multi_segment_circle_indicator.dart';


import 'package:flutter/Material.dart';
import 'package:get/get.dart';
import 'package:permission_handler/permission_handler.dart';
import 'package:photo_classifier/models.dart';
import 'package:photo_classifier/photo_classifier.dart';
import 'package:wechat_assets_picker/wechat_assets_picker.dart';

import '../../module/image_picker/image_picker_util.dart';
import '../utils/file_size_calculator_util.dart';


class PhotoScanHandler {


  final classifier = PhotoClassifier();
  var hasPermission = false.obs;
  var isClassifying = false.obs;
  var errorMessage = ''.obs;

  static var progress = Rxn<ClassificationProgress>();


  StreamSubscription<ClassificationEvent?>? _subscription;

  static RxBool isSimilarScanned = false.obs;
  static RxBool isPeopleScanned = false.obs;
  static RxBool isScreenShotScanned = false.obs;
  static RxBool isBlurryScanned = false.obs;

  // 人物图片
  static RxList<AssetEntity> peoplePhotos = <AssetEntity>[].obs;

  // 地点图片
  static Rx<AssetEntity?> locationPhoto = Rx<AssetEntity?>(null);

  // 截图照片
  static Rx<AssetEntity?> screenshotPhoto = Rx<AssetEntity?>(null);

  // 模糊照片
  static Rx<AssetEntity?> blurryPhoto = Rx<AssetEntity?>(null);

  // 相似照片
  static RxList<AssetEntity> similarPhotos = <AssetEntity>[].obs;

  static Rx<double> totalSpace = 0.0.obs;
  static Rx<double> usedSpace = 0.0.obs;
  static Rx<double> photoSpace = 0.0.obs;
  static Rx<double> freeSpace = 0.0.obs;

  static Rx<String> totalSpaceStr = "0.0 GB".obs;
  static Rx<String> usedSpaceStr = "0.0 GB".obs;
  static Rx<String> photoSpaceStr = "0.0 GB".obs;
  static Rx<String> freeSpaceStr = "0.0 GB".obs;

  // 计算已用存储百分比
  static double get usedSpacePercentage =>
      (usedSpace.value / totalSpace.value) * 100;

  // 计算照片占用存储百分比
  static double get photoSpacePercentage =>
      (photoSpace.value / totalSpace.value) * 100;

  // 计算可用存储百分比
  static double get freeSpacePercentage =>
      (freeSpace.value / totalSpace.value) * 100;

  static List<PieData> get pieDataList => [
        PieData("PhotoSpace", photoSpacePercentage, Colors.blue),
        PieData("OtherUsed", usedSpacePercentage - photoSpacePercentage,
            Colors.red),
        PieData("totalSpace", totalSpace.value, Colors.grey.withOpacity(0.1)),
      ];

  // 存储是否扫描完成
  static RxBool isStorageScanned = false.obs;


  Future<void> getStorageInfo() async {


    final classifyPhoto = ClassifyPhoto();

    try {
      final storageInfo = await classifyPhoto.getStorageInfo();

      // 转换为 GB
      final totalSpaceGB = storageInfo['totalSpace']! / (1000 * 1000 * 1000);
      final freeSpaceGB = storageInfo['freeSpace']! / (1024 * 1024 * 1024);
      final usedSpaceGB = storageInfo['usedSpace']! / (1024 * 1024 * 1024);
      final photoSpaceGB = storageInfo['photoSpace']! / (1024 * 1024 * 1024);

      totalSpaceStr.value = ImagePickerUtil.formatFileSize(
          storageInfo['totalSpace']!,
          decimals: 1);
      freeSpaceStr.value = ImagePickerUtil.formatFileSize(
          storageInfo['freeSpace']!,
          decimals: 1);
      usedSpaceStr.value = ImagePickerUtil.formatFileSize(
          storageInfo['usedSpace']!,
          decimals: 1);
      photoSpaceStr.value = ImagePickerUtil.formatFileSize(
          storageInfo['photoSpace']!,
          decimals: 1);

      totalSpace.value = totalSpaceGB.round().toDouble();
      freeSpace.value = freeSpaceGB;
      usedSpace.value = usedSpaceGB;
      photoSpace.value = photoSpaceGB;

      print('总容量: $totalSpaceStr');
      print('可用空间: $freeSpaceStr');
      print('已用空间: $usedSpaceStr');
      print('照片占用: $photoSpaceStr');
      isStorageScanned.value = true;
    } catch (e) {
      print('获取存储信息失败: $e');
    }
  }

  /// 执行所有的照片处理操作
  Future<void> handleAllPhotos() async {
    var currentStatus = await Permission.photos.status;
    if (Platform.isAndroid) {
      currentStatus = await Permission.storage.status;
    }
    if (currentStatus.isGranted) {
      if (Platform.isAndroid) {
        await handleAndroidPhotos();
      }
      // 已有完全权限，直接扫描
      PhotoManager.clearFileCache();
      startClassification();
    } else if (currentStatus.isLimited) {
      // 已有有限权限，显示自定义弹窗
      PhotoManager.clearFileCache();
      startClassification();

    } else {
      // 未授权，请求权限
      var result = await Permission.photos.request();
      if (Platform.isAndroid) {
        result = await Permission.storage.request();
      }
      if (result.isGranted || result.isLimited) {
        PhotoManager.clearFileCache();
        getStorageInfo();
        startClassification();

        if (Platform.isAndroid) {
          await handleAndroidPhotos();
        }
      } else {
        isSimilarScanned.value = true;
        isPeopleScanned.value = true;
        isBlurryScanned.value = true;
        isScreenShotScanned.value = true;
      }
    }
  }


  /// Android平台处理方式
  Future<void> handleAndroidPhotos() async {
    final List<AssetEntity> result = await ImagePickerUtil.loadAssets();
    ImagePickerUtil.peoplePhotos.value = result ?? [];
    ImagePickerUtil.locationPhotos['location'] = result ?? [];
    ImagePickerUtil.screenshotPhotos.value = result ?? [];
    ImagePickerUtil.similarPhotos.add(result ?? []);
    ImagePickerUtil.blurryPhotos.value = result ?? [];
     FileSizeCalculatorUtil.calculateTotalSize(
        assetIds: ImagePickerUtil.blurryPhotos.map((e) => e.id).toSet(),
        updateValue: (double totalSize) {
          ImagePickerUtil.blurrySize.value = totalSize.toInt()*1024;
        });

    // result = await ImagePickerUtil.loadAssetsPaged(page: 1, pageSize: 9);
    // ImagePickerUtil.similarPhotos.add(result ?? []);
    // result = await ImagePickerUtil.loadAssetsPaged(page: 2, pageSize: 9);
    // ImagePickerUtil.similarPhotos.add(result ?? []);

    print("handleAndroidPhotos $result");
    print(
        "ImagePickerUtil.peoplePhotos.value ${ImagePickerUtil.peoplePhotos.length}");

    isSimilarScanned.value = true;
    isPeopleScanned.value = true;
    isBlurryScanned.value = true;
    isScreenShotScanned.value = true;

    similarPhotos.clear();
    if (ImagePickerUtil.similarPhotos.isNotEmpty) {
      for (var group in ImagePickerUtil.similarPhotos) {
        print(
            " ImagePickerUtil.similarPhotos ${ImagePickerUtil.similarPhotos.length}");
        for (var asset in group) {
          similarPhotos.add(asset);
          if (similarPhotos.length == 4) {
            break;
          }
        }
      }
    }

    peoplePhotos.clear();
    if (ImagePickerUtil.peoplePhotos.isNotEmpty) {
      for (var personPhoto in ImagePickerUtil.peoplePhotos) {
        peoplePhotos.add(personPhoto);
        if (peoplePhotos.length == 2) {
          break;
        }
      }
    }

    if (ImagePickerUtil.blurryPhotos.isNotEmpty) {
      var asset = ImagePickerUtil.blurryPhotos.first;
      blurryPhoto.value = asset;
    }

    if (ImagePickerUtil.screenshotPhotos.isNotEmpty) {
      var asset = ImagePickerUtil.screenshotPhotos.first;
      screenshotPhoto.value = asset;
    }
  }

  Future<void> startClassification() async {
    isClassifying.value = true;
    errorMessage.value = '';
    progress.value = null;
    ImagePickerUtil.similarResult.clear();
    ImagePickerUtil.peopleResult.clear();
    ImagePickerUtil.screenshotResult.clear();
    ImagePickerUtil.blurryResult.clear();
    try {
      await classifier.configureClassifier(
        batchSize: 200,
        maxConcurrentProcessing: 4,
        similarityThreshold: 0.75,
      );

      _subscription = classifier.startClassificationStream().listen(
        (event) async {
          if (event == null) return;
          progress.value = event.progress;
          final result = event.result;
          if (result != null) {
           await ImagePickerUtil.loadClassifiedPhotoData(result);
          }
          if (event.progress?.isCompleted == true) {
            isClassifying.value = false;
            _subscription?.cancel();
            _subscription = null;
            completeClassification();
          }
        },
        onError: (error) {
          errorMessage.value = '分类过程中出错: $error';
          isClassifying.value = false;
        },
        onDone: () {
          if (progress.value?.isCompleted != true) {
            errorMessage.value = '分类过程意外结束';
            isClassifying.value = false;
          }


        },
      );
    } catch (e) {
      errorMessage.value = '启动分类失败: $e';
      isClassifying.value = false;
    }
  }

  void cancelClassification() {
    _subscription?.cancel();
    _subscription = null;
    isClassifying.value = false;
    classifier.resetClassifier();
  }

  void resetAll() {
    progress.value = null;
    ImagePickerUtil.similarResult.clear();
    ImagePickerUtil.peopleResult.clear();
    ImagePickerUtil.screenshotResult.clear();
    ImagePickerUtil.blurryResult.clear();
    errorMessage.value = '';
    isClassifying.value = false;
  }

  void completeClassification() {

    isSimilarScanned.value = true;
    isPeopleScanned.value = true;
    isBlurryScanned.value = true;
    isScreenShotScanned.value = true;

  }



}