80 lines
1.8 KiB
Dart
80 lines
1.8 KiB
Dart
import "package:photos/face/model/detection.dart";
|
|
import 'package:photos/services/machine_learning/face_ml/face_filtering/face_filtering_constants.dart';
|
|
|
|
// FileInfo contains the image width and height of the image the face was detected in.
|
|
class FileInfo {
|
|
int? imageWidth;
|
|
int? imageHeight;
|
|
FileInfo({
|
|
this.imageWidth,
|
|
this.imageHeight,
|
|
});
|
|
}
|
|
|
|
class Face {
|
|
final int fileID;
|
|
final String faceID;
|
|
final List<double> embedding;
|
|
Detection detection;
|
|
final double score;
|
|
final double blur;
|
|
FileInfo? fileInfo;
|
|
|
|
bool get isBlurry => blur < kLaplacianThreshold;
|
|
|
|
bool get hasHighScore => score > kMinHighQualityFaceScore;
|
|
|
|
bool get isHighQuality => (!isBlurry) && hasHighScore;
|
|
|
|
int get visibility => detection.getVisibilityScore();
|
|
|
|
int area({int? w, int? h}) {
|
|
return detection.getFaceArea(
|
|
fileInfo?.imageWidth ?? w ?? 0,
|
|
fileInfo?.imageHeight ?? h ?? 0,
|
|
);
|
|
}
|
|
|
|
Face(
|
|
this.faceID,
|
|
this.fileID,
|
|
this.embedding,
|
|
this.score,
|
|
this.detection,
|
|
this.blur, {
|
|
this.fileInfo,
|
|
});
|
|
|
|
factory Face.empty(int fileID, {bool error = false}) {
|
|
return Face(
|
|
"$fileID-0",
|
|
fileID,
|
|
<double>[],
|
|
error ? -1.0 : 0.0,
|
|
Detection.empty(),
|
|
0.0,
|
|
);
|
|
}
|
|
|
|
factory Face.fromJson(Map<String, dynamic> json) {
|
|
return Face(
|
|
json['faceID'] as String,
|
|
json['fileID'] as int,
|
|
List<double>.from(json['embeddings'] as List),
|
|
json['score'] as double,
|
|
Detection.fromJson(json['detection'] as Map<String, dynamic>),
|
|
// high value means t
|
|
(json['blur'] ?? kLapacianDefault) as double,
|
|
);
|
|
}
|
|
|
|
Map<String, dynamic> toJson() => {
|
|
'faceID': faceID,
|
|
'fileID': fileID,
|
|
'embeddings': embedding,
|
|
'detection': detection.toJson(),
|
|
'score': score,
|
|
'blur': blur,
|
|
};
|
|
}
|