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[mob][photos] Refactor getting file path

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This commit is contained in:
laurenspriem
2024-06-28 18:47:50 +05:30
parent 393ed91e86
commit 8381598944
2 changed files with 88 additions and 82 deletions
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82
mobile/lib/services/machine_learning/face_ml/face_ml_service.dart
View File

@@ -9,7 +9,6 @@ import "dart:ui" show Image;
import "package:computer/computer.dart";
import "package:dart_ui_isolate/dart_ui_isolate.dart";
import "package:flutter/foundation.dart" show debugPrint, kDebugMode;
import "package:flutter/services.dart";
import "package:logging/logging.dart";
import "package:onnxruntime/onnxruntime.dart";
import "package:package_info_plus/package_info_plus.dart";
@@ -42,15 +41,12 @@ import 'package:photos/services/machine_learning/file_ml/file_ml.dart';
import 'package:photos/services/machine_learning/file_ml/remote_fileml_service.dart';
import 'package:photos/services/machine_learning/ml_exceptions.dart';
import "package:photos/services/search_service.dart";
import "package:photos/utils/file_util.dart";
import "package:photos/utils/image_ml_util.dart";
import "package:photos/utils/local_settings.dart";
import "package:photos/utils/ml_util.dart";
import "package:photos/utils/network_util.dart";
import "package:photos/utils/thumbnail_util.dart";
import "package:synchronized/synchronized.dart";
enum FileDataForML { thumbnailData, fileData }
enum FaceMlOperation { analyzeImage }
/// This class is responsible for running the full face ml pipeline on images.
@@ -836,15 +832,8 @@ class FaceMlService {
Future<FaceMlResult?> _analyzeImageInSingleIsolate(EnteFile enteFile) async {
_checkEnteFileForID(enteFile);
final String? filePath =
await _getImagePathForML(enteFile, typeOfData: FileDataForML.fileData);
if (filePath == null) {
_logger.warning(
"Failed to get any data for enteFile with uploadedFileID ${enteFile.uploadedFileID} since its file path is null",
);
throw CouldNotRetrieveAnyFileData();
}
final String filePath =
await getImagePathForML(enteFile, typeOfData: FileDataForML.fileData);
final Stopwatch stopwatch = Stopwatch()..start();
late FaceMlResult result;
@@ -975,71 +964,6 @@ class FaceMlService {
}
}
Future<String?> _getImagePathForML(
EnteFile enteFile, {
FileDataForML typeOfData = FileDataForML.fileData,
}) async {
String? imagePath;
switch (typeOfData) {
case FileDataForML.fileData:
final stopwatch = Stopwatch()..start();
File? file;
if (enteFile.fileType == FileType.video) {
try {
file = await getThumbnailForUploadedFile(enteFile);
} on PlatformException catch (e, s) {
_logger.severe(
"Could not get thumbnail for $enteFile due to PlatformException",
e,
s,
);
throw ThumbnailRetrievalException(e.toString(), s);
}
} else {
try {
file = await getFile(enteFile, isOrigin: true);
} catch (e, s) {
_logger.severe(
"Could not get file for $enteFile",
e,
s,
);
}
}
if (file == null) {
_logger.warning(
"Could not get file for $enteFile of type ${enteFile.fileType.toString()}",
);
imagePath = null;
break;
}
imagePath = file.path;
stopwatch.stop();
_logger.info(
"Getting file data for uploadedFileID ${enteFile.uploadedFileID} took ${stopwatch.elapsedMilliseconds} ms",
);
break;
case FileDataForML.thumbnailData:
final stopwatch = Stopwatch()..start();
final File? thumbnail = await getThumbnailForUploadedFile(enteFile);
if (thumbnail == null) {
_logger.warning("Could not get thumbnail for $enteFile");
imagePath = null;
break;
}
imagePath = thumbnail.path;
stopwatch.stop();
_logger.info(
"Getting thumbnail data for uploadedFileID ${enteFile.uploadedFileID} took ${stopwatch.elapsedMilliseconds} ms",
);
break;
}
return imagePath;
}
/// Detects faces in the given image data.
///
/// `imageData`: The image data to analyze.

88
mobile/lib/utils/ml_util.dart
View File

@@ -1,7 +1,89 @@
import "dart:io" show File;
import "package:flutter/services.dart" show PlatformException;
import "package:logging/logging.dart";
import "package:photos/core/configuration.dart";
import "package:photos/db/files_db.dart";
import "package:photos/models/file/file.dart";
import "package:photos/models/file/file_type.dart";
import "package:photos/services/machine_learning/ml_exceptions.dart";
import "package:photos/utils/file_util.dart";
import "package:photos/utils/thumbnail_util.dart";
final _logger = Logger("MlUtil");
enum FileDataForML { thumbnailData, fileData }
Future<List<int>> getIndexableFileIDs() async {
return FilesDB.instance
.getOwnedFileIDs(Configuration.instance.getUserID()!);
}
return FilesDB.instance.getOwnedFileIDs(Configuration.instance.getUserID()!);
}
Future<String> getImagePathForML(
EnteFile enteFile, {
FileDataForML typeOfData = FileDataForML.fileData,
}) async {
String? imagePath;
switch (typeOfData) {
case FileDataForML.fileData:
final stopwatch = Stopwatch()..start();
File? file;
if (enteFile.fileType == FileType.video) {
try {
file = await getThumbnailForUploadedFile(enteFile);
} on PlatformException catch (e, s) {
_logger.severe(
"Could not get thumbnail for $enteFile due to PlatformException",
e,
s,
);
throw ThumbnailRetrievalException(e.toString(), s);
}
} else {
try {
file = await getFile(enteFile, isOrigin: true);
} catch (e, s) {
_logger.severe(
"Could not get file for $enteFile",
e,
s,
);
}
}
if (file == null) {
_logger.warning(
"Could not get file for $enteFile of type ${enteFile.fileType.toString()}",
);
break;
}
imagePath = file.path;
stopwatch.stop();
_logger.info(
"Getting file data for uploadedFileID ${enteFile.uploadedFileID} took ${stopwatch.elapsedMilliseconds} ms",
);
break;
case FileDataForML.thumbnailData:
final stopwatch = Stopwatch()..start();
final File? thumbnail = await getThumbnailForUploadedFile(enteFile);
if (thumbnail == null) {
_logger.warning("Could not get thumbnail for $enteFile");
break;
}
imagePath = thumbnail.path;
stopwatch.stop();
_logger.info(
"Getting thumbnail data for uploadedFileID ${enteFile.uploadedFileID} took ${stopwatch.elapsedMilliseconds} ms",
);
break;
}
if (imagePath == null) {
_logger.warning(
"Failed to get any data for enteFile with uploadedFileID ${enteFile.uploadedFileID} since its file path is null",
);
throw CouldNotRetrieveAnyFileData();
}
return imagePath;
}