453 lines
14 KiB
Dart
453 lines
14 KiB
Dart
import "dart:async" show StreamSubscription, unawaited;
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import "dart:math";
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import "dart:typed_data";
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import "package:flutter/foundation.dart" show kDebugMode;
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import "package:flutter/material.dart";
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import "package:photos/core/event_bus.dart";
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import "package:photos/events/people_changed_event.dart";
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import "package:photos/face/db.dart";
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import "package:photos/face/model/person.dart";
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import "package:photos/models/file/file.dart";
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import 'package:photos/services/machine_learning/face_ml/feedback/cluster_feedback.dart';
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import "package:photos/theme/ente_theme.dart";
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import "package:photos/ui/components/buttons/button_widget.dart";
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import "package:photos/ui/components/models/button_type.dart";
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// import "package:photos/ui/viewer/people/add_person_action_sheet.dart";
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import "package:photos/ui/viewer/people/cluster_page.dart";
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import "package:photos/ui/viewer/people/person_clusters_page.dart";
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import "package:photos/ui/viewer/search/result/person_face_widget.dart";
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class PersonReviewClusterSuggestion extends StatefulWidget {
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final PersonEntity person;
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const PersonReviewClusterSuggestion(
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this.person, {
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super.key,
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});
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@override
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State<PersonReviewClusterSuggestion> createState() => _PersonClustersState();
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}
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class _PersonClustersState extends State<PersonReviewClusterSuggestion> {
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int currentSuggestionIndex = 0;
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bool fetch = true;
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Key futureBuilderKeySuggestions = UniqueKey();
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Key futureBuilderKeyFaceThumbnails = UniqueKey();
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bool canGiveFeedback = true;
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// Declare a variable for the future
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late Future<List<ClusterSuggestion>> futureClusterSuggestions;
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late StreamSubscription<PeopleChangedEvent> _peopleChangedEvent;
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@override
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void initState() {
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super.initState();
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// Initialize the future in initState
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if (fetch) _fetchClusterSuggestions();
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fetch = true;
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}
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@override
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void dispose() {
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_peopleChangedEvent.cancel();
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super.dispose();
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}
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@override
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Widget build(BuildContext context) {
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return Scaffold(
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appBar: AppBar(
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title: const Text('Review suggestions'),
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actions: [
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IconButton(
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icon: const Icon(Icons.history_outlined),
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onPressed: () {
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Navigator.of(context).push(
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MaterialPageRoute(
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builder: (context) => PersonClustersPage(widget.person),
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),
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);
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},
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),
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],
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),
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body: FutureBuilder<List<ClusterSuggestion>>(
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key: futureBuilderKeySuggestions,
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future: futureClusterSuggestions,
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builder: (context, snapshot) {
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if (snapshot.hasData) {
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if (snapshot.data!.isEmpty) {
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return Center(
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child: Text(
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"No suggestions for ${widget.person.data.name}",
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style: getEnteTextTheme(context).largeMuted,
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),
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);
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}
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final allSuggestions = snapshot.data!;
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final numberOfDifferentSuggestions = allSuggestions.length;
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final currentSuggestion = allSuggestions[currentSuggestionIndex];
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final int clusterID = currentSuggestion.clusterIDToMerge;
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final double distance = currentSuggestion.distancePersonToCluster;
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final bool usingMean = currentSuggestion.usedOnlyMeanForSuggestion;
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final List<EnteFile> files = currentSuggestion.filesInCluster;
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final Future<Map<int, Uint8List?>> generateFacedThumbnails =
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_generateFaceThumbnails(
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files.sublist(0, min(files.length, 8)),
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clusterID,
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);
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_peopleChangedEvent =
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Bus.instance.on<PeopleChangedEvent>().listen((event) {
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if (event.type == PeopleEventType.removedFilesFromCluster &&
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(event.source == clusterID.toString())) {
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for (var updatedFile in event.relevantFiles!) {
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files.remove(updatedFile);
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}
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fetch = false;
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setState(() {});
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}
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});
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return InkWell(
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onTap: () {
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final List<EnteFile> sortedFiles =
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List<EnteFile>.from(currentSuggestion.filesInCluster);
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sortedFiles.sort(
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(a, b) => b.creationTime!.compareTo(a.creationTime!),
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);
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Navigator.of(context).push(
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MaterialPageRoute(
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builder: (context) => ClusterPage(
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sortedFiles,
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personID: widget.person,
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clusterID: clusterID,
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showNamingBanner: false,
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),
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),
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);
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},
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child: Container(
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padding: const EdgeInsets.symmetric(
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horizontal: 8.0,
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vertical: 20,
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),
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child: _buildSuggestionView(
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clusterID,
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distance,
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usingMean,
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files,
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numberOfDifferentSuggestions,
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allSuggestions,
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generateFacedThumbnails,
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),
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),
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);
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} else if (snapshot.hasError) {
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// log the error
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return const Center(child: Text("Error"));
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} else {
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return const Center(child: CircularProgressIndicator());
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}
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},
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),
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);
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}
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Future<void> _handleUserClusterChoice(
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int clusterID,
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bool yesOrNo,
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int numberOfSuggestions,
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) async {
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// Perform the action based on clusterID, e.g., assignClusterToPerson or captureNotPersonFeedback
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if (!canGiveFeedback) {
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return;
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}
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if (yesOrNo) {
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canGiveFeedback = false;
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await FaceMLDataDB.instance.assignClusterToPerson(
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personID: widget.person.remoteID,
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clusterID: clusterID,
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);
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Bus.instance.fire(PeopleChangedEvent());
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// Increment the suggestion index
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if (mounted) {
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setState(() => currentSuggestionIndex++);
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}
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// Check if we need to fetch new data
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if (currentSuggestionIndex >= (numberOfSuggestions)) {
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setState(() {
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currentSuggestionIndex = 0;
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futureBuilderKeySuggestions =
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UniqueKey(); // Reset to trigger FutureBuilder
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futureBuilderKeyFaceThumbnails = UniqueKey();
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_fetchClusterSuggestions();
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});
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} else {
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futureBuilderKeyFaceThumbnails = UniqueKey();
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fetch = false;
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setState(() {});
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}
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} else {
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await _rejectSuggestion(clusterID, numberOfSuggestions);
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}
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}
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Future<void> _rejectSuggestion(
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int clusterID,
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int numberOfSuggestions,
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) async {
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canGiveFeedback = false;
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await FaceMLDataDB.instance.captureNotPersonFeedback(
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personID: widget.person.remoteID,
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clusterID: clusterID,
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);
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// Recalculate the suggestions when a suggestion is rejected
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setState(() {
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currentSuggestionIndex = 0;
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futureBuilderKeySuggestions =
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UniqueKey(); // Reset to trigger FutureBuilder
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futureBuilderKeyFaceThumbnails = UniqueKey();
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_fetchClusterSuggestions();
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});
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}
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// Method to fetch cluster suggestions
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void _fetchClusterSuggestions() {
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futureClusterSuggestions =
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ClusterFeedbackService.instance.getSuggestionForPerson(widget.person);
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}
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Widget _buildSuggestionView(
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int clusterID,
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double distance,
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bool usingMean,
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List<EnteFile> files,
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int numberOfSuggestions,
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List<ClusterSuggestion> allSuggestions,
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Future<Map<int, Uint8List?>> generateFaceThumbnails,
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) {
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final widgetToReturn = Column(
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key: ValueKey("cluster_id-$clusterID-files-${files.length}"),
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children: <Widget>[
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if (kDebugMode)
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Text(
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"ClusterID: $clusterID, Distance: ${distance.toStringAsFixed(3)}, usingMean: $usingMean",
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style: getEnteTextTheme(context).smallMuted,
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),
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Text(
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// TODO: come up with a better copy for strings below!
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"${widget.person.data.name}?",
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style: getEnteTextTheme(context).largeMuted,
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),
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const SizedBox(height: 24),
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_buildThumbnailWidget(
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files,
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clusterID,
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generateFaceThumbnails,
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),
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const SizedBox(
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height: 24.0,
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),
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Padding(
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padding: const EdgeInsets.symmetric(horizontal: 24.0),
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child: Row(
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children: <Widget>[
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Expanded(
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child: ButtonWidget(
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buttonType: ButtonType.critical,
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labelText: 'No',
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buttonSize: ButtonSize.large,
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onTap: () async => {
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await _handleUserClusterChoice(
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clusterID,
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false,
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numberOfSuggestions,
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),
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},
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),
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),
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const SizedBox(width: 12.0),
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Expanded(
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child: ButtonWidget(
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buttonType: ButtonType.primary,
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labelText: 'Yes',
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buttonSize: ButtonSize.large,
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onTap: () async => {
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await _handleUserClusterChoice(
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clusterID,
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true,
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numberOfSuggestions,
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),
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},
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),
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),
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],
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),
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),
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// const SizedBox(
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// height: 24.0,
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// ),
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// ButtonWidget(
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// shouldSurfaceExecutionStates: false,
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// buttonType: ButtonType.neutral,
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// labelText: 'Assign different person',
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// buttonSize: ButtonSize.small,
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// onTap: () async {
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// final result = await showAssignPersonAction(
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// context,
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// clusterID: clusterID,
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// );
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// if (result != null &&
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// (result is (PersonEntity, EnteFile) ||
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// result is PersonEntity)) {
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// await _rejectSuggestion(clusterID, numberOfSuggestions);
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// }
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// },
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// ),
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],
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);
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// Precompute face thumbnails for next suggestions, in case there are
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const precomputeSuggestions = 8;
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const maxPrecomputations = 8;
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int compCount = 0;
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if (allSuggestions.length > currentSuggestionIndex + 1) {
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outerLoop:
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for (final suggestion in allSuggestions.sublist(
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currentSuggestionIndex + 1,
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min(
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allSuggestions.length,
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currentSuggestionIndex + precomputeSuggestions,
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),
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)) {
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final files = suggestion.filesInCluster;
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final clusterID = suggestion.clusterIDToMerge;
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for (final file in files.sublist(0, min(files.length, 8))) {
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unawaited(
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PersonFaceWidget.precomputeNextFaceCrops(
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file,
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clusterID,
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useFullFile: false,
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),
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);
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compCount++;
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if (compCount >= maxPrecomputations) {
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debugPrint(
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'Prefetching $compCount face thumbnails for suggestions',
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);
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break outerLoop;
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}
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}
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}
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}
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return widgetToReturn;
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}
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Widget _buildThumbnailWidget(
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List<EnteFile> files,
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int clusterID,
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Future<Map<int, Uint8List?>> generateFaceThumbnails,
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) {
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return SizedBox(
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height: MediaQuery.of(context).size.height * 0.4,
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child: FutureBuilder<Map<int, Uint8List?>>(
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key: futureBuilderKeyFaceThumbnails,
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future: generateFaceThumbnails,
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builder: (context, snapshot) {
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if (snapshot.hasData) {
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final faceThumbnails = snapshot.data!;
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canGiveFeedback = true;
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return Column(
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children: <Widget>[
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Row(
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mainAxisAlignment: MainAxisAlignment.center,
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children: _buildThumbnailWidgetsRow(
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files,
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clusterID,
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faceThumbnails,
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),
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),
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if (files.length > 4) const SizedBox(height: 24),
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if (files.length > 4)
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Row(
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mainAxisAlignment: MainAxisAlignment.center,
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children: _buildThumbnailWidgetsRow(
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files,
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clusterID,
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faceThumbnails,
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start: 4,
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),
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),
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const SizedBox(height: 24.0),
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Text(
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"${files.length} photos",
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style: getEnteTextTheme(context).body,
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),
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],
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);
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} else if (snapshot.hasError) {
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// log the error
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return const Center(child: Text("Error"));
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} else {
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canGiveFeedback = false;
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return const Center(child: CircularProgressIndicator());
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}
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},
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),
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);
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}
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List<Widget> _buildThumbnailWidgetsRow(
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List<EnteFile> files,
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int cluserId,
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Map<int, Uint8List?> faceThumbnails, {
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int start = 0,
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}) {
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return List<Widget>.generate(
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min(4, max(0, files.length - start)),
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(index) => Padding(
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padding: const EdgeInsets.all(8.0),
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child: SizedBox(
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width: 72,
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height: 72,
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child: ClipOval(
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child: PersonFaceWidget(
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files[start + index],
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clusterID: cluserId,
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useFullFile: false,
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thumbnailFallback: false,
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faceCrop: faceThumbnails[files[start + index].uploadedFileID!],
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),
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),
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),
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),
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);
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}
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Future<Map<int, Uint8List?>> _generateFaceThumbnails(
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List<EnteFile> files,
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int clusterID,
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) async {
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final futures = <Future<Uint8List?>>[];
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for (final file in files) {
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futures.add(
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PersonFaceWidget.precomputeNextFaceCrops(
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file,
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clusterID,
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useFullFile: false,
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),
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);
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}
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final faceCropsList = await Future.wait(futures);
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final faceCrops = <int, Uint8List?>{};
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for (var i = 0; i < faceCropsList.length; i++) {
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faceCrops[files[i].uploadedFileID!] = faceCropsList[i];
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}
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return faceCrops;
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}
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}
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