Fix suggestion not using previous negative feedback

mobile/lib/db/ml/base.dart

@@ -13,6 +13,7 @@ abstract class IMLDataDB<T> {
   Future<int> getFaceIndexedFileCount({int minimumMlVersion});
   Future<Map<String, int>> clusterIdToFaceCount();
   Future<Set<String>> getPersonIgnoredClusters(String personID);
+  Future<Map<String, Set<String>>> getPersonToRejectedSuggestions();
   Future<Set<String>> getPersonClusterIDs(String personID);
   Future<Set<String>> getPersonsClusterIDs(List<String> personID);
   Future<void> clearTable();

mobile/lib/db/ml/db.dart

@@ -212,6 +212,21 @@ class MLDataDB with SqlDbBase implements IMLDataDB<int> {
     return ignoredClusterIDs.union(rejectClusterIDs);
   }
 
+  @override
+  Future<Map<String, Set<String>>> getPersonToRejectedSuggestions() async {
+    final db = await instance.asyncDB;
+    final List<Map<String, dynamic>> rejectMaps = await db.getAll(
+      'SELECT $personIdColumn, $clusterIDColumn FROM $notPersonFeedback',
+    );
+    final Map<String, Set<String>> result = {};
+    for (final map in rejectMaps) {
+      final personID = map[personIdColumn] as String;
+      final clusterID = map[clusterIDColumn] as String;
+      result.putIfAbsent(personID, () => {}).add(clusterID);
+    }
+    return result;
+  }
+
   @override
   Future<Set<String>> getPersonClusterIDs(String personID) async {
     final db = await instance.asyncDB;

mobile/lib/services/machine_learning/face_ml/feedback/cluster_feedback.dart

@@ -357,11 +357,23 @@ class ClusterFeedbackService<T> {
         allOtherPersonClustersToIgnore,
         minClusterSize: kMinimumClusterSizeSearchResult,
       );
+
+      final Map<String, Set<String>> personClusterToIgnoredClusters = {};
+      final personToRejectedSuggestions =
+          await mlDataDB.getPersonToRejectedSuggestions();
+      for (final personID in personToRejectedSuggestions.keys) {
+        final personCluster = personIdToBiggestCluster[personID];
+        if (personCluster == null) continue;
+        final ignoredClusters = personToRejectedSuggestions[personID] ?? {};
+        personClusterToIgnoredClusters[personCluster] = ignoredClusters;
+      }
+
       final List<(String, double, String)> foundSuggestions =
           await calcSuggestionsMeanInComputer(
         clusterAvg,
         allPersonClusters,
         allOtherPersonClustersToIgnore,
+        personClusterToIgnoredClusters: personClusterToIgnoredClusters,
         0.55,
       );
 
@@ -1014,8 +1026,9 @@ class ClusterFeedbackService<T> {
     Map<String, Vector> clusterAvg,
     Set<String> personClusters,
     Set<String> ignoredClusters,
-    double maxClusterDistance,
-  ) async {
+    double maxClusterDistance, {
+    Map<String, Set<String>>? personClusterToIgnoredClusters,
+  }) async {
     return await _computer.compute(
       _calcSuggestionsMean,
       param: {
@@ -1023,6 +1036,7 @@ class ClusterFeedbackService<T> {
         'personClusters': personClusters,
         'ignoredClusters': ignoredClusters,
         'maxClusterDistance': maxClusterDistance,
+        'personClusterToIgnoredClusters': personClusterToIgnoredClusters,
       },
     );
   }
@@ -1341,6 +1355,9 @@ List<(String, double, String)> _calcSuggestionsMean(Map<String, dynamic> args) {
   final Set<String> personClusters = args['personClusters'];
   final Set<String> ignoredClusters = args['ignoredClusters'];
   final double maxClusterDistance = args['maxClusterDistance'];
+  final Map<String, Set<String>>? personClusterToIgnoredClusters =
+      args['personClusterToIgnoredClusters'];
+  final bool extraIgnoreCheck = personClusterToIgnoredClusters != null;
 
   final Map<String, List<(String, double)>> suggestions = {};
   const suggestionMax = 2000;
@@ -1366,6 +1383,12 @@ List<(String, double, String)> _calcSuggestionsMean(Map<String, dynamic> args) {
         dev.log('[WARNING] no avg for personcluster $personCluster');
         continue;
       }
+      if (extraIgnoreCheck &&
+          personClusterToIgnoredClusters[personCluster] != null &&
+          personClusterToIgnoredClusters[personCluster]!
+              .contains(otherClusterID)) {
+        continue;
+      }
       final Vector avg = clusterAvg[personCluster]!;
       final distance = 1 - avg.dot(otherAvg);
       comparisons++;