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[mob][photos] Small changes in suggestion calculation

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This commit is contained in:
laurenspriem 2024-05-02 12:35:52 +05:30
parent 74ae4ea74f
commit d650bac501
1 changed files with 17 additions and 8 deletions
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25
mobile/lib/services/machine_learning/face_ml/feedback/cluster_feedback.dart
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@ -784,24 +784,31 @@ class ClusterFeedbackService {
Map<int, int>? allClusterIdsToCountMap,
}) {
final Map<int, List<(int, double)>> suggestions = {};
const suggestionMax = 2000;
int suggestionCount = 0;
int comparisons = 0;
final w = (kDebugMode ? EnteWatch('getSuggestions') : null)?..start();
for (final otherClusterID in clusterAvg.keys) {
// ignore the cluster that belong to the person or is ignored
if (personClusters.contains(otherClusterID) ||
ignoredClusters.contains(otherClusterID)) {
// ignore the clusters that belong to the person or is ignored
Set<int> otherClusters = clusterAvg.keys.toSet().difference(personClusters);
otherClusters = otherClusters.difference(ignoredClusters);
for (final otherClusterID in otherClusters) {
final Vector? otherAvg = clusterAvg[otherClusterID];
if (otherAvg == null) {
_logger.warning('no avg for othercluster $otherClusterID');
continue;
}
final Vector otherAvg = clusterAvg[otherClusterID]!;
int? nearestPersonCluster;
double? minDistance;
for (final personCluster in personClusters) {
if (clusterAvg[personCluster] == null) {
_logger.info('no avg for cluster $personCluster');
_logger.warning('no avg for personcluster $personCluster');
continue;
}
final Vector avg = clusterAvg[personCluster]!;
final distance = cosineDistanceSIMD(avg, otherAvg);
comparisons++;
if (distance < maxClusterDistance) {
if (minDistance == null || distance < minDistance) {
minDistance = distance;
@ -815,11 +822,13 @@ class ClusterFeedbackService {
.add((otherClusterID, minDistance));
suggestionCount++;
}
if (suggestionCount >= 2000) {
if (suggestionCount >= suggestionMax) {
break;
}
}
w?.log('calculation inside calcSuggestionsMean');
w?.log(
'calculation inside calcSuggestionsMean for ${personClusters.length} person clusters and ${otherClusters.length} other clusters (so ${personClusters.length * otherClusters.length} combinations, $comparisons comparisons made resulted in $suggestionCount suggestions)',
);
if (suggestions.isNotEmpty) {
final List<(int, double)> suggestClusterIds = [];