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[mob][photos] refactor

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This commit is contained in:
laurenspriem
2024-09-02 12:45:30 +02:00
parent ba083fff70
commit da316fdcfd
1 changed files with 59 additions and 53 deletions
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112
mobile/lib/services/machine_learning/ml_computer.dart
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@@ -1,5 +1,4 @@
import 'dart:async';
import "dart:collection" show Queue;
import "dart:io" show File;
import 'dart:isolate';
import 'dart:typed_data' show Uint8List;
@@ -75,56 +74,62 @@ class MLComputer {
final args = message[1] as Map<String, dynamic>;
final sendPort = message[2] as SendPort;
late final Object data;
try {
switch (function) {
case MLComputerOperation.generateFaceThumbnails:
final imagePath = args['imagePath'] as String;
final Uint8List imageData = await File(imagePath).readAsBytes();
final faceBoxesJson =
args['faceBoxesList'] as List<Map<String, dynamic>>;
final List<FaceBox> faceBoxes =
faceBoxesJson.map((json) => FaceBox.fromJson(json)).toList();
final List<Uint8List> results =
await generateFaceThumbnailsUsingCanvas(
imageData,
faceBoxes,
);
sendPort.send(List.from(results));
case MLComputerOperation.loadModel:
final modelName = args['modelName'] as String;
final modelPath = args['modelPath'] as String;
final int address = await MlModel.loadModel(
modelName,
modelPath,
);
sendPort.send(address);
break;
case MLComputerOperation.initializeClipTokenizer:
final vocabPath = args["vocabPath"] as String;
await ClipTextTokenizer.instance.init(vocabPath);
sendPort.send(true);
break;
case MLComputerOperation.runClipText:
//TODO:lau check logging here
final textEmbedding = await ClipTextEncoder.predict(args);
sendPort.send(List<double>.from(textEmbedding, growable: false));
break;
case MLComputerOperation.testLogging:
final logger = Logger('XXX MLComputerTestLogging');
logger.info("XXX logging from isolate is working!!!");
final Queue<String> logStrings =
isolateLogger.getLogStringsAndClear();
final logs = List<String>.from(logStrings);
sendPort.send({"data": true, "logs": logs});
break;
}
data = await cases(function, args);
} catch (e, stackTrace) {
sendPort
.send({'error': e.toString(), 'stackTrace': stackTrace.toString()});
data = {
'error': e.toString(),
'stackTrace': stackTrace.toString(),
};
}
final logs = List<String>.from(isolateLogger.getLogStringsAndClear());
sendPort.send({"data": data, "logs": logs});
});
}
/// WARNING: Only return primitives: https://api.flutter.dev/flutter/dart-isolate/SendPort/send.html
static Future<dynamic> cases(
MLComputerOperation function,
Map<String, dynamic> args,
) async {
switch (function) {
case MLComputerOperation.generateFaceThumbnails:
final imagePath = args['imagePath'] as String;
final Uint8List imageData = await File(imagePath).readAsBytes();
final faceBoxesJson =
args['faceBoxesList'] as List<Map<String, dynamic>>;
final List<FaceBox> faceBoxes =
faceBoxesJson.map((json) => FaceBox.fromJson(json)).toList();
final List<Uint8List> results = await generateFaceThumbnailsUsingCanvas(
imageData,
faceBoxes,
);
return List.from(results);
case MLComputerOperation.loadModel:
final modelName = args['modelName'] as String;
final modelPath = args['modelPath'] as String;
final int address = await MlModel.loadModel(
modelName,
modelPath,
);
return address;
case MLComputerOperation.initializeClipTokenizer:
final vocabPath = args["vocabPath"] as String;
await ClipTextTokenizer.instance.init(vocabPath);
return true;
case MLComputerOperation.runClipText:
//TODO:lau check logging here
final textEmbedding = await ClipTextEncoder.predict(args);
return List<double>.from(textEmbedding, growable: false);
case MLComputerOperation.testLogging:
final logger = Logger('XXX MLComputerTestLogging');
logger.info("XXX logging from isolate is working!!!");
throw Exception("XXX logging from isolate testing exception handling");
return true;
}
}
/// The common method to run any operation in the isolate. It sends the [message] to [_isolateMain] and waits for the result.
Future<dynamic> _runInIsolate(
(MLComputerOperation, Map<String, dynamic>) message,
@@ -137,15 +142,18 @@ class MLComputer {
_mainSendPort.send([message.$1.index, message.$2, answerPort.sendPort]);
answerPort.listen((receivedMessage) {
if (receivedMessage is Map && receivedMessage.containsKey('error')) {
final logs = receivedMessage['logs'] as List<String>;
IsolateLogger.handLogStringsToMainLogger(logs);
final data = receivedMessage['data'];
if (data is Map && data.containsKey('error')) {
// Handle the error
final errorMessage = receivedMessage['error'];
final errorStackTrace = receivedMessage['stackTrace'];
final errorMessage = data['error'];
final errorStackTrace = data['stackTrace'];
final exception = Exception(errorMessage);
final stackTrace = StackTrace.fromString(errorStackTrace);
completer.completeError(exception, stackTrace);
} else {
completer.complete(receivedMessage);
completer.complete(data);
}
});
@@ -240,10 +248,8 @@ class MLComputer {
MLComputerOperation.testLogging,
{},
),
) as Map<String, Object>;
final logs = result['logs'] as List<String>;
IsolateLogger.handLogStringsToMainLogger(logs);
return result['data'] as bool;
) as bool;
return result;
} catch (e, s) {
_logger.severe("XXX Could not test logging in isolate", e, s);
rethrow;