[mob] Read face embeddings using sqlite async

mobile/lib/face/db.dart

@@ -1,4 +1,5 @@
 import 'dart:async';
+import "dart:io" show Directory;
 import "dart:math";
 
 import "package:collection/collection.dart";
@@ -13,6 +14,7 @@ import "package:photos/face/model/face.dart";
 import "package:photos/models/file/file.dart";
 import 'package:photos/services/machine_learning/face_ml/face_filtering/face_filtering_constants.dart';
 import 'package:sqflite/sqflite.dart';
+import 'package:sqlite_async/sqlite_async.dart' as sqlite_async;
 
 /// Stores all data for the ML-related features. The database can be accessed by `MlDataDB.instance.database`.
 ///
@@ -29,13 +31,20 @@ class FaceMLDataDB {
 
   static final FaceMLDataDB instance = FaceMLDataDB._privateConstructor();
 
+  // only have a single app-wide reference to the database
   static Future<Database>? _dbFuture;
+  static Future<sqlite_async.SqliteDatabase>? _sqliteAsyncDBFuture;
 
   Future<Database> get database async {
     _dbFuture ??= _initDatabase();
     return _dbFuture!;
   }
 
+  Future<sqlite_async.SqliteDatabase> get sqliteAsyncDB async {
+    _sqliteAsyncDBFuture ??= _initSqliteAsyncDatabase();
+    return _sqliteAsyncDBFuture!;
+  }
+
   Future<Database> _initDatabase() async {
     final documentsDirectory = await getApplicationDocumentsDirectory();
     final String databaseDirectory =
@@ -47,6 +56,15 @@ class FaceMLDataDB {
     );
   }
 
+  Future<sqlite_async.SqliteDatabase> _initSqliteAsyncDatabase() async {
+    final Directory documentsDirectory =
+        await getApplicationDocumentsDirectory();
+    final String databaseDirectory =
+        join(documentsDirectory.path, _databaseName);
+    _logger.info("Opening sqlite_async access: DB path " + databaseDirectory);
+    return sqlite_async.SqliteDatabase(path: databaseDirectory);
+  }
+
   Future _onCreate(Database db, int version) async {
     await db.execute(createFacesTable);
     await db.execute(createFaceClustersTable);
@@ -398,18 +416,22 @@ class FaceMLDataDB {
     w.logAndReset(
       'reading as float offset: $offset, maxFaces: $maxFaces, batchSize: $batchSize',
     );
-    final db = await instance.database;
+    final db = await instance.sqliteAsyncDB;
 
     final Map<String, (int?, Uint8List)> result = {};
     while (true) {
       // Query a batch of rows
-      final List<Map<String, dynamic>> maps = await db.query(
-        facesTable,
-        columns: [faceIDColumn, faceEmbeddingBlob],
-        where: '$faceScore > $minScore and $faceBlur > $minClarity',
-        limit: batchSize,
-        offset: offset,
-        orderBy: '$faceIDColumn DESC',
+      final List<Map<String, dynamic>> maps = await db.getAll(
+        'SELECT $faceIDColumn, $faceEmbeddingBlob FROM $facesTable'
+        ' WHERE $faceScore > $minScore AND $faceBlur > $minClarity'
+        ' ORDER BY $faceIDColumn'
+        ' DESC LIMIT $batchSize OFFSET $offset',
+        // facesTable,
+        // columns: [faceIDColumn, faceEmbeddingBlob],
+        // where: '$faceScore > $minScore and $faceBlur > $minClarity',
+        // limit: batchSize,
+        // offset: offset,
+        // orderBy: '$faceIDColumn DESC',
       );
       // Break the loop if no more rows
       if (maps.isEmpty) {

mobile/lib/ui/settings/debug/face_debug_section_widget.dart

@@ -5,7 +5,6 @@ import 'package:flutter/material.dart';
 import "package:logging/logging.dart";
 import "package:photos/core/event_bus.dart";
 import "package:photos/events/people_changed_event.dart";
-import "package:photos/extensions/stop_watch.dart";
 import "package:photos/face/db.dart";
 import "package:photos/face/model/person.dart";
 import "package:photos/services/machine_learning/face_ml/face_filtering/face_filtering_constants.dart";
@@ -333,13 +332,25 @@ class _FaceDebugSectionWidgetState extends State<FaceDebugSectionWidget> {
             trailingIcon: Icons.chevron_right_outlined,
             trailingIconIsMuted: true,
             onTap: () async {
-              final EnteWatch watch = EnteWatch("read_embeddings")..start();
-              final result = await FaceMLDataDB.instance.getFaceEmbeddingMap();
-              watch.logAndReset('read embeddings ${result.length} ');
-              showShortToast(
-                context,
-                "Read ${result.length} face embeddings in ${watch.elapsed.inSeconds} secs",
-              );
+              final int totalFaces =
+                  await FaceMLDataDB.instance.getTotalFaceCount();
+              _logger.info('start reading embeddings for $totalFaces faces');
+              final time = DateTime.now();
+              try {
+                final result = await FaceMLDataDB.instance
+                    .getFaceEmbeddingMap(maxFaces: totalFaces);
+                final endTime = DateTime.now();
+                _logger.info(
+                  'Read embeddings of ${result.length} faces in ${time.difference(endTime).inSeconds} secs',
+                );
+                showShortToast(
+                  context,
+                  "Read embeddings of ${result.length} faces in ${time.difference(endTime).inSeconds} secs",
+                );
+              } catch (e, s) {
+                _logger.warning('read embeddings failed ', e, s);
+                await showGenericErrorDialog(context: context, error: e);
+              }
             },
           ),
       ],