[mob][photos] First iteration of file selection

mobile/lib/services/search_service.dart

@@ -4,12 +4,14 @@ import "package:flutter/cupertino.dart";
 import "package:flutter/material.dart";
 import "package:intl/intl.dart";
 import 'package:logging/logging.dart';
+import "package:ml_linalg/linalg.dart";
 import "package:photos/core/constants.dart";
 import 'package:photos/core/event_bus.dart';
 import 'package:photos/data/holidays.dart';
 import 'package:photos/data/months.dart';
 import 'package:photos/data/years.dart';
 import 'package:photos/db/files_db.dart';
+import "package:photos/db/ml/clip_db.dart";
 import "package:photos/db/ml/db.dart";
 import 'package:photos/events/local_photos_updated_event.dart';
 import "package:photos/extensions/user_extension.dart";
@@ -40,6 +42,7 @@ import "package:photos/services/filter/db_filters.dart";
 import "package:photos/services/location_service.dart";
 import "package:photos/services/machine_learning/face_ml/face_filtering/face_filtering_constants.dart";
 import "package:photos/services/machine_learning/face_ml/person/person_service.dart";
+import "package:photos/services/machine_learning/ml_computer.dart";
 import 'package:photos/services/machine_learning/semantic_search/semantic_search_service.dart';
 import "package:photos/services/user_remote_flag_service.dart";
 import "package:photos/states/location_screen_state.dart";
@@ -1233,17 +1236,18 @@ class SearchService {
         final date =
             DateTime(currentTime.year, dayMonth ~/ 100, dayMonth % 100);
         final allPhotos = yearGroups.values.expand((x) => x).toList();
+        final photoSelection = await _bestSelection(allPhotos);
 
         searchResults.add(
           GenericSearchResult(
             ResultType.event,
             'Memories of ${DateFormat('MMMM d').format(date)}',
-            allPhotos,
+            photoSelection,
             hierarchicalSearchFilter: TopLevelGenericFilter(
               filterName: DateFormat('MMMM d').format(date),
               occurrence: kMostRelevantFilter,
               filterResultType: ResultType.event,
-              matchedUploadedIDs: filesToUploadedFileIDs(allPhotos),
+              matchedUploadedIDs: filesToUploadedFileIDs(photoSelection),
               filterIcon: Icons.event_outlined,
             ),
           ),
@@ -1253,6 +1257,7 @@ class SearchService {
         for (final year in significantYears) {
           final date = DateTime(year, dayMonth ~/ 100, dayMonth % 100);
           final files = yearGroups[year]!;
+          final photoSelection = await _bestSelection(files);
           String name =
               DateFormat.yMMMd(Localizations.localeOf(context).languageCode)
                   .format(date);
@@ -1264,12 +1269,12 @@ class SearchService {
             GenericSearchResult(
               ResultType.event,
               name,
-              files,
+              photoSelection,
               hierarchicalSearchFilter: TopLevelGenericFilter(
                 filterName: name,
                 occurrence: kMostRelevantFilter,
                 filterResultType: ResultType.event,
-                matchedUploadedIDs: filesToUploadedFileIDs(files),
+                matchedUploadedIDs: filesToUploadedFileIDs(photoSelection),
                 filterIcon: Icons.event_outlined,
               ),
             ),
@@ -1283,6 +1288,83 @@ class SearchService {
     return searchResults;
   }
 
+  /// Returns the best selection of files from the given list.
+  /// Makes sure that the selection is not more than 10 files,
+  /// and that each year of the original list is represented.
+  Future<List<EnteFile>> _bestSelection(List<EnteFile> files) async {
+    if (files.length <= 10) return files;
+    final fileIDs = files.map((e) => e.uploadedFileID!).toSet();
+    final fileIdToFace = await MLDataDB.instance.getFacesForFileIDs(fileIDs);
+    final fileIdToClip =
+        await MLDataDB.instance.getClipVectorsForFileIDs(fileIDs);
+    final allYears = files.map((e) {
+      final creationTime = DateTime.fromMicrosecondsSinceEpoch(e.creationTime!);
+      return creationTime.year;
+    }).toSet();
+    if (allYears.length <= 1) {
+      // sort first on clip embeddings TODO: lau: come up with a better prompt
+      const query = 'Beautiful photo of a nice memory';
+      // TODO: lau: optimize this later so we don't keep computing embedding
+      final textEmbedding = await MLComputer.instance.runClipText(query);
+      final textVector = Vector.fromList(textEmbedding);
+      final fileToScore = <int, double>{};
+      for (final file in files) {
+        final clip = fileIdToClip[file.uploadedFileID!];
+        if (clip == null) {
+          fileToScore[file.uploadedFileID!] = 0;
+          continue;
+        }
+        final score = clip.vector.dot(textVector);
+        fileToScore[file.uploadedFileID!] = score;
+      }
+      files.sort(
+        (a, b) => fileToScore[b.uploadedFileID!]!
+            .compareTo(fileToScore[a.uploadedFileID!]!),
+      );
+
+      // then sort on faces
+      final fileToFaceCount = <int, int>{};
+      for (final file in files) {
+        final faces = fileIdToFace[file.uploadedFileID!];
+        if (faces == null) {
+          fileToFaceCount[file.uploadedFileID!] = 0;
+          continue;
+        }
+        fileToFaceCount[file.uploadedFileID!] = faces.length;
+      }
+      files.sort(
+        (a, b) => fileToFaceCount[b.uploadedFileID!]!
+            .compareTo(fileToFaceCount[a.uploadedFileID!]!),
+      );
+
+      // then filter out similar images as much as possible
+      final filteredFiles = <EnteFile>[files.first];
+      final fileCount = files.length;
+      int skipped = 0;
+      filesLoop:
+      for (final file in files.sublist(1)) {
+        if (filteredFiles.length >= 10) break;
+        final clip = fileIdToClip[file.uploadedFileID!];
+        if (clip != null && (fileCount - skipped) > 10) {
+          for (final filteredFile in filteredFiles) {
+            final fClip = fileIdToClip[filteredFile.uploadedFileID!];
+            if (fClip == null) continue;
+            final similarity = clip.vector.dot(fClip.vector);
+            if (similarity > 0.15) {
+              skipped++;
+              continue filesLoop;
+            }
+          }
+        }
+        filteredFiles.add(file);
+      }
+      return filteredFiles;
+    } else {
+      // TODO: lau: add logic for multiple years. Main extra thing is getting distribution over the years right
+      return files;
+    }
+  }
+
   Future<GenericSearchResult?> getRandomDateResults(
     BuildContext context,
   ) async {