diff --git a/mobile/lib/services/machine_learning/face_ml/feedback/cluster_feedback.dart b/mobile/lib/services/machine_learning/face_ml/feedback/cluster_feedback.dart index c328104b75..021e09f672 100644 --- a/mobile/lib/services/machine_learning/face_ml/feedback/cluster_feedback.dart +++ b/mobile/lib/services/machine_learning/face_ml/feedback/cluster_feedback.dart @@ -40,7 +40,8 @@ class ClusterFeedbackService { final _computer = Computer.shared(); ClusterFeedbackService._privateConstructor(); - static final ClusterFeedbackService instance = ClusterFeedbackService._privateConstructor(); + static final ClusterFeedbackService instance = + ClusterFeedbackService._privateConstructor(); static int lastViewedClusterID = -1; static setLastViewedClusterID(int clusterID) { @@ -686,7 +687,7 @@ class ClusterFeedbackService { clusterAvgBigClusters, personClusters, ignoredClusters, - (minimumSize == 100) ? goodMeanDistance + 0.15 : goodMeanDistance, + goodMeanDistance, ); w?.log( 'Calculate suggestions using mean for ${clusterAvgBigClusters.length} clusters of min size $minimumSize', @@ -1165,7 +1166,9 @@ List<(int, double)> _calcSuggestionsMean(Map args) { } } if (nearestPersonCluster != null && minDistance != null) { - suggestions.putIfAbsent(nearestPersonCluster, () => []).add((otherClusterID, minDistance)); + suggestions + .putIfAbsent(nearestPersonCluster, () => []) + .add((otherClusterID, minDistance)); suggestionCount++; } if (suggestionCount >= suggestionMax) { @@ -1195,7 +1198,8 @@ List<(int, double)> _calcSuggestionsMean(Map args) { } } -Future<(Map, Set, int, int, int)> checkAndSerializeCurrentClusterMeans( +Future<(Map, Set, int, int, int)> + checkAndSerializeCurrentClusterMeans( Map args, ) async { final Map allClusterIdsToCountMap = args['allClusterIdsToCountMap'];