face recognition on ios release, works fine on depug but blank screen on release. flutter

face recognition on ios release, works fine on depug but blank screen on release.
I’m using this package
text
and google mlk face reconizer
The feature works fine on android, and on ios depug, but when i release it on ios, it show blank sncree.

here is my screen

Plain text
Copy to clipboard
Open code in new window
EnlighterJS 3 Syntax Highlighter
<code>class FaceRegistrationScreen extends StatefulWidget {
final bool toInterview;
const FaceRegistrationScreen({super.key, this.toInterview = false});
@override
State<FaceRegistrationScreen> createState() => _FaceRegistrationState();
}
class _FaceRegistrationState extends State<FaceRegistrationScreen> {
ImagePicker imagePicker = ImagePicker();
File? _image;
late FaceDetector faceDetector;
late Recognizer recognizer;
bool loading = false;
List<Face> faces = [];
var image;
@override
void initState() {
super.initState();
final options = FaceDetectorOptions();
faceDetector = FaceDetector(options: options);
recognizer = Recognizer();
}
removeRotation(File inputImage) async {
final img.Image? capturedImage =
img.decodeImage(await File(inputImage.path).readAsBytes());
final img.Image orientedImage = img.bakeOrientation(capturedImage!);
return await File(_image!.path).writeAsBytes(img.encodeJpg(orientedImage));
}
doFaceDetection() async {
_image = await removeRotation(_image!);
image = await _image?.readAsBytes();
image = await decodeImageFromList(image);
setState(() {
image;
});
InputImage inputImage = InputImage.fromFile(_image!);
faces = await faceDetector.processImage(inputImage).then((value) async {
if (value.isNotEmpty) {
Rect faceRect = value[0].boundingBox;
num left = faceRect.left < 0 ? 0 : faceRect.left;
num top = faceRect.top < 0 ? 0 : faceRect.top;
num right =
faceRect.right > image.width ? image.width - 1 : faceRect.right;
num bottom =
faceRect.bottom > image.height ? image.height - 1 : faceRect.bottom;
num width = right - left;
num height = bottom - top;
final bytes = _image!.readAsBytesSync();
img.Image? faceImg = img.decodeImage(bytes);
img.Image faceImg2 = img.copyCrop(faceImg!,
x: left.toInt(),
y: top.toInt(),
width: width.toInt(),
height: height.toInt());
List<double> emb = recognizer.getEmbedding(faceImg2, faceRect);
await AppPreferences.setUserEmbedding(emb.join(",")).then(
(value) async => await uploadUserImage(
context, _image!, EndPoints.saveUserImage,
toInterview: widget.toInterview));
} else {
myToast(
context: context,
text: AppStrings.pleaseLookCameraWhenTakingPhoto,
state: ToastStates.error);
}
return value;
});
setState(() {
_image;
faces;
loading = false;
});
}
@override
Widget build(BuildContext context) {
return Directionality(
textDirection: TextDirection.rtl,
child: Scaffold(
resizeToAvoidBottomInset: false,
body: SafeArea(
child: Stack(
children: [
myBackgroundContainer(context),
Column(
crossAxisAlignment: CrossAxisAlignment.start,
children: [
mySigningAppBar(context, AppStrings.logInSubTitleFace),
Expanded(
child: Card(
child: SizedBox(
height: double.infinity,
width: double.infinity,
child: Column(
children: [
SizedBox(
height: AppSize.s10.h,
),
Expanded(
child: SingleChildScrollView(
child: Padding(
padding: EdgeInsets.all(AppPadding.p20.r),
child: _column()),
),
),
],
),
),
),
),
],
),
],
),
),
),
);
}
Widget _column() => Column(
mainAxisAlignment: MainAxisAlignment.spaceBetween,
children: [
image != null
? Column(
children: [
Container(
margin: EdgeInsets.all(AppMargin.m30.r),
padding: EdgeInsets.only(bottom: AppSize.s93.h),
child: FittedBox(
child: SizedBox(
width: image.width.toDouble(),
height: image.width.toDouble(),
child: CustomPaint(
painter:
FacePainter(facesList: faces, imageFile: image),
),
),
),
),
SizedBox(
height: AppSize.s60.h,
),
(loading)
? SizedBox(
height: AppSize.s50.spMin,
width: 1.sw,
child: const Center(
child: CircularProgressIndicator(),
),
)
: SizedBox(
width: image.width.toDouble(),
child: Row(
mainAxisSize: MainAxisSize.min,
children: [
Expanded(
child: myElevatedButton(context,
text: AppStrings.tryAgain, onPressed: () {
setState(() {
image = null;
});
}),
),
SizedBox(
width: AppSize.s20.w,
),
Expanded(
child: myElevatedButton(context,
text: AppStrings.uploadPhotoAnyway,
onPressed: () async {
if (_image != null) {
await uploadUserImage(context, _image!,
EndPoints.saveUserImage,
toInterview: widget.toInterview);
}
}),
),
],
),
),
],
)
: SmartFaceCameraWidget(
loading: loading,
showCameraLensControl: true,
onCapture: (File? img) async {
setState(() {
_image = img;
loading = true;
});
await doFaceDetection();
},
),
SizedBox(
height: AppSize.s40.h,
),
],
);
}
class FacePainter extends CustomPainter {
List<Face> facesList;
dynamic imageFile;
FacePainter({required this.facesList, @required this.imageFile});
@override
void paint(Canvas canvas, Size size) {
if (imageFile != null) {
canvas.drawImage(imageFile, Offset.zero, Paint());
}
Paint p = Paint();
p.color = Colors.red;
p.style = PaintingStyle.stroke;
p.strokeWidth = 6;
for (Face face in facesList) {
canvas.drawRect(face.boundingBox, p);
}
}
@override
bool shouldRepaint(CustomPainter oldDelegate) {
return true;
}
}
</code>
<code>class FaceRegistrationScreen extends StatefulWidget { final bool toInterview; const FaceRegistrationScreen({super.key, this.toInterview = false}); @override State<FaceRegistrationScreen> createState() => _FaceRegistrationState(); } class _FaceRegistrationState extends State<FaceRegistrationScreen> { ImagePicker imagePicker = ImagePicker(); File? _image; late FaceDetector faceDetector; late Recognizer recognizer; bool loading = false; List<Face> faces = []; var image; @override void initState() { super.initState(); final options = FaceDetectorOptions(); faceDetector = FaceDetector(options: options); recognizer = Recognizer(); } removeRotation(File inputImage) async { final img.Image? capturedImage = img.decodeImage(await File(inputImage.path).readAsBytes()); final img.Image orientedImage = img.bakeOrientation(capturedImage!); return await File(_image!.path).writeAsBytes(img.encodeJpg(orientedImage)); } doFaceDetection() async { _image = await removeRotation(_image!); image = await _image?.readAsBytes(); image = await decodeImageFromList(image); setState(() { image; }); InputImage inputImage = InputImage.fromFile(_image!); faces = await faceDetector.processImage(inputImage).then((value) async { if (value.isNotEmpty) { Rect faceRect = value[0].boundingBox; num left = faceRect.left < 0 ? 0 : faceRect.left; num top = faceRect.top < 0 ? 0 : faceRect.top; num right = faceRect.right > image.width ? image.width - 1 : faceRect.right; num bottom = faceRect.bottom > image.height ? image.height - 1 : faceRect.bottom; num width = right - left; num height = bottom - top; final bytes = _image!.readAsBytesSync(); img.Image? faceImg = img.decodeImage(bytes); img.Image faceImg2 = img.copyCrop(faceImg!, x: left.toInt(), y: top.toInt(), width: width.toInt(), height: height.toInt()); List<double> emb = recognizer.getEmbedding(faceImg2, faceRect); await AppPreferences.setUserEmbedding(emb.join(",")).then( (value) async => await uploadUserImage( context, _image!, EndPoints.saveUserImage, toInterview: widget.toInterview)); } else { myToast( context: context, text: AppStrings.pleaseLookCameraWhenTakingPhoto, state: ToastStates.error); } return value; }); setState(() { _image; faces; loading = false; }); } @override Widget build(BuildContext context) { return Directionality( textDirection: TextDirection.rtl, child: Scaffold( resizeToAvoidBottomInset: false, body: SafeArea( child: Stack( children: [ myBackgroundContainer(context), Column( crossAxisAlignment: CrossAxisAlignment.start, children: [ mySigningAppBar(context, AppStrings.logInSubTitleFace), Expanded( child: Card( child: SizedBox( height: double.infinity, width: double.infinity, child: Column( children: [ SizedBox( height: AppSize.s10.h, ), Expanded( child: SingleChildScrollView( child: Padding( padding: EdgeInsets.all(AppPadding.p20.r), child: _column()), ), ), ], ), ), ), ), ], ), ], ), ), ), ); } Widget _column() => Column( mainAxisAlignment: MainAxisAlignment.spaceBetween, children: [ image != null ? Column( children: [ Container( margin: EdgeInsets.all(AppMargin.m30.r), padding: EdgeInsets.only(bottom: AppSize.s93.h), child: FittedBox( child: SizedBox( width: image.width.toDouble(), height: image.width.toDouble(), child: CustomPaint( painter: FacePainter(facesList: faces, imageFile: image), ), ), ), ), SizedBox( height: AppSize.s60.h, ), (loading) ? SizedBox( height: AppSize.s50.spMin, width: 1.sw, child: const Center( child: CircularProgressIndicator(), ), ) : SizedBox( width: image.width.toDouble(), child: Row( mainAxisSize: MainAxisSize.min, children: [ Expanded( child: myElevatedButton(context, text: AppStrings.tryAgain, onPressed: () { setState(() { image = null; }); }), ), SizedBox( width: AppSize.s20.w, ), Expanded( child: myElevatedButton(context, text: AppStrings.uploadPhotoAnyway, onPressed: () async { if (_image != null) { await uploadUserImage(context, _image!, EndPoints.saveUserImage, toInterview: widget.toInterview); } }), ), ], ), ), ], ) : SmartFaceCameraWidget( loading: loading, showCameraLensControl: true, onCapture: (File? img) async { setState(() { _image = img; loading = true; }); await doFaceDetection(); }, ), SizedBox( height: AppSize.s40.h, ), ], ); } class FacePainter extends CustomPainter { List<Face> facesList; dynamic imageFile; FacePainter({required this.facesList, @required this.imageFile}); @override void paint(Canvas canvas, Size size) { if (imageFile != null) { canvas.drawImage(imageFile, Offset.zero, Paint()); } Paint p = Paint(); p.color = Colors.red; p.style = PaintingStyle.stroke; p.strokeWidth = 6; for (Face face in facesList) { canvas.drawRect(face.boundingBox, p); } } @override bool shouldRepaint(CustomPainter oldDelegate) { return true; } } </code>
class FaceRegistrationScreen extends StatefulWidget {
  final bool toInterview;
  const FaceRegistrationScreen({super.key, this.toInterview = false});

  @override
  State<FaceRegistrationScreen> createState() => _FaceRegistrationState();
}

class _FaceRegistrationState extends State<FaceRegistrationScreen> {
  ImagePicker imagePicker = ImagePicker();
  File? _image;
  late FaceDetector faceDetector;
  late Recognizer recognizer;
  bool loading = false;
  List<Face> faces = [];
  var image;
  @override
  void initState() {
    super.initState();
    final options = FaceDetectorOptions();
    faceDetector = FaceDetector(options: options);
    recognizer = Recognizer();
  }

  removeRotation(File inputImage) async {
    final img.Image? capturedImage =
        img.decodeImage(await File(inputImage.path).readAsBytes());
    final img.Image orientedImage = img.bakeOrientation(capturedImage!);
    return await File(_image!.path).writeAsBytes(img.encodeJpg(orientedImage));
  }

  doFaceDetection() async {
    _image = await removeRotation(_image!);
    image = await _image?.readAsBytes();
    image = await decodeImageFromList(image);
    setState(() {
      image;
    });
    InputImage inputImage = InputImage.fromFile(_image!);
    faces = await faceDetector.processImage(inputImage).then((value) async {
      if (value.isNotEmpty) {
        Rect faceRect = value[0].boundingBox;
        num left = faceRect.left < 0 ? 0 : faceRect.left;
        num top = faceRect.top < 0 ? 0 : faceRect.top;
        num right =
            faceRect.right > image.width ? image.width - 1 : faceRect.right;
        num bottom =
            faceRect.bottom > image.height ? image.height - 1 : faceRect.bottom;
        num width = right - left;
        num height = bottom - top;
        final bytes = _image!.readAsBytesSync();
        img.Image? faceImg = img.decodeImage(bytes);
        img.Image faceImg2 = img.copyCrop(faceImg!,
            x: left.toInt(),
            y: top.toInt(),
            width: width.toInt(),
            height: height.toInt());
        List<double> emb = recognizer.getEmbedding(faceImg2, faceRect);
        await AppPreferences.setUserEmbedding(emb.join(",")).then(
            (value) async => await uploadUserImage(
                context, _image!, EndPoints.saveUserImage,
                toInterview: widget.toInterview));
      } else {
        myToast(
            context: context,
            text: AppStrings.pleaseLookCameraWhenTakingPhoto,
            state: ToastStates.error);
      }
      return value;
    });
    setState(() {
      _image;
      faces;
      loading = false;
    });
  }

  @override
  Widget build(BuildContext context) {
    return Directionality(
      textDirection: TextDirection.rtl,
      child: Scaffold(
        resizeToAvoidBottomInset: false,
        body: SafeArea(
          child: Stack(
            children: [
              myBackgroundContainer(context),
              Column(
                crossAxisAlignment: CrossAxisAlignment.start,
                children: [
                  mySigningAppBar(context, AppStrings.logInSubTitleFace),
                  Expanded(
                    child: Card(
                      child: SizedBox(
                        height: double.infinity,
                        width: double.infinity,
                        child: Column(
                          children: [
                            SizedBox(
                              height: AppSize.s10.h,
                            ),
                            Expanded(
                              child: SingleChildScrollView(
                                child: Padding(
                                    padding: EdgeInsets.all(AppPadding.p20.r),
                                    child: _column()),
                              ),
                            ),
                          ],
                        ),
                      ),
                    ),
                  ),
                ],
              ),
            ],
          ),
        ),
      ),
    );
  }

  Widget _column() => Column(
        mainAxisAlignment: MainAxisAlignment.spaceBetween,
        children: [
          image != null
              ? Column(
                  children: [
                    Container(
                      margin: EdgeInsets.all(AppMargin.m30.r),
                      padding: EdgeInsets.only(bottom: AppSize.s93.h),
                      child: FittedBox(
                        child: SizedBox(
                          width: image.width.toDouble(),
                          height: image.width.toDouble(),
                          child: CustomPaint(
                            painter:
                                FacePainter(facesList: faces, imageFile: image),
                          ),
                        ),
                      ),
                    ),
                    SizedBox(
                      height: AppSize.s60.h,
                    ),
                    (loading)
                        ? SizedBox(
                            height: AppSize.s50.spMin,
                            width: 1.sw,
                            child: const Center(
                              child: CircularProgressIndicator(),
                            ),
                          )
                        : SizedBox(
                            width: image.width.toDouble(),
                            child: Row(
                              mainAxisSize: MainAxisSize.min,
                              children: [
                                Expanded(
                                  child: myElevatedButton(context,
                                      text: AppStrings.tryAgain, onPressed: () {
                                    setState(() {
                                      image = null;
                                    });
                                  }),
                                ),
                                SizedBox(
                                  width: AppSize.s20.w,
                                ),
                                Expanded(
                                  child: myElevatedButton(context,
                                      text: AppStrings.uploadPhotoAnyway,
                                      onPressed: () async {
                                    if (_image != null) {
                                      await uploadUserImage(context, _image!,
                                          EndPoints.saveUserImage,
                                          toInterview: widget.toInterview);
                                    }
                                  }),
                                ),
                              ],
                            ),
                          ),
                  ],
                )
              : SmartFaceCameraWidget(
                  loading: loading,
                  showCameraLensControl: true,
                  onCapture: (File? img) async {
                    setState(() {
                      _image = img;
                      loading = true;
                    });
                    await doFaceDetection();
                  },
                ),
          SizedBox(
            height: AppSize.s40.h,
          ),
        ],
      );
}

class FacePainter extends CustomPainter {
  List<Face> facesList;
  dynamic imageFile;

  FacePainter({required this.facesList, @required this.imageFile});

  @override
  void paint(Canvas canvas, Size size) {
    if (imageFile != null) {
      canvas.drawImage(imageFile, Offset.zero, Paint());
    }
    Paint p = Paint();
    p.color = Colors.red;
    p.style = PaintingStyle.stroke;
    p.strokeWidth = 6;
    for (Face face in facesList) {
      canvas.drawRect(face.boundingBox, p);
    }
  }

  @override
  bool shouldRepaint(CustomPainter oldDelegate) {
    return true;
  }
}

and the smart face camera widget

Plain text
Copy to clipboard
Open code in new window
EnlighterJS 3 Syntax Highlighter
<code>class SmartFaceCameraWidget extends StatefulWidget {
final bool loading;
final bool showCameraLensControl;
final void Function(File?) onCapture;
const SmartFaceCameraWidget({
super.key,
this.loading = false,
required this.showCameraLensControl,
required this.onCapture,
});
@override
SmartFaceCameraWidgetState createState() => SmartFaceCameraWidgetState();
}
class SmartFaceCameraWidgetState extends State<SmartFaceCameraWidget> {
late FaceCameraController _controller;
@override
void initState() {
super.initState();
_controller = FaceCameraController(
onCapture: widget.onCapture,
defaultCameraLens: CameraLens.front,
);
}
@override
Widget build(BuildContext context) {
return Container(
margin: const EdgeInsets.only(top: 30),
height: 600.h,
child: SmartFaceCamera(
controller: _controller,
showCaptureControl: true,
showFlashControl: false,
showCameraLensControl: widget.showCameraLensControl,
captureControlBuilder: (context, _) {
return widget.loading
? SizedBox(
height: AppSize.s54.h,
child: const Center(child: CircularProgressIndicator()),
)
: Container(
alignment: Alignment.center,
width: AppSize.s200.w,
height: AppSize.s54.h,
decoration: BoxDecoration(
borderRadius: BorderRadius.circular(AppSize.s20),
color: AppColors.primary,
),
padding: EdgeInsets.symmetric(
horizontal: AppPadding.p8.w, vertical: AppPadding.p2.h),
child: Text(
AppStrings.captureImageCamera,
textAlign: TextAlign.center,
style: getAppSemiBoldTextStyle(
color: AppColors.white, fontSize: FontSize.s16.spMin),
),
);
},
lensControlIcon: CircleAvatar(
backgroundColor: AppColors.white,
radius: AppSize.s26.r,
child: Icon(
Icons.cameraswitch,
size: AppSize.s40.r,
color: AppColors.primary,
),
),
messageBuilder: (context, face) {
if (face == null) {
return _message('ضع وجهك أمام الكاميرا');
}
if (!face.wellPositioned) {
return _message('قم بتوسيط وجهك في المربع');
}
return const SizedBox.shrink();
},
),
);
}
Widget _message(String msg) => Padding(
padding: const EdgeInsets.symmetric(horizontal: 55, vertical: 15),
child: Text(
msg,
textAlign: TextAlign.center,
style: const TextStyle(
fontSize: 14,
height: 1.5,
fontWeight: FontWeight.w400,
),
),
);
}
</code>
<code>class SmartFaceCameraWidget extends StatefulWidget { final bool loading; final bool showCameraLensControl; final void Function(File?) onCapture; const SmartFaceCameraWidget({ super.key, this.loading = false, required this.showCameraLensControl, required this.onCapture, }); @override SmartFaceCameraWidgetState createState() => SmartFaceCameraWidgetState(); } class SmartFaceCameraWidgetState extends State<SmartFaceCameraWidget> { late FaceCameraController _controller; @override void initState() { super.initState(); _controller = FaceCameraController( onCapture: widget.onCapture, defaultCameraLens: CameraLens.front, ); } @override Widget build(BuildContext context) { return Container( margin: const EdgeInsets.only(top: 30), height: 600.h, child: SmartFaceCamera( controller: _controller, showCaptureControl: true, showFlashControl: false, showCameraLensControl: widget.showCameraLensControl, captureControlBuilder: (context, _) { return widget.loading ? SizedBox( height: AppSize.s54.h, child: const Center(child: CircularProgressIndicator()), ) : Container( alignment: Alignment.center, width: AppSize.s200.w, height: AppSize.s54.h, decoration: BoxDecoration( borderRadius: BorderRadius.circular(AppSize.s20), color: AppColors.primary, ), padding: EdgeInsets.symmetric( horizontal: AppPadding.p8.w, vertical: AppPadding.p2.h), child: Text( AppStrings.captureImageCamera, textAlign: TextAlign.center, style: getAppSemiBoldTextStyle( color: AppColors.white, fontSize: FontSize.s16.spMin), ), ); }, lensControlIcon: CircleAvatar( backgroundColor: AppColors.white, radius: AppSize.s26.r, child: Icon( Icons.cameraswitch, size: AppSize.s40.r, color: AppColors.primary, ), ), messageBuilder: (context, face) { if (face == null) { return _message('ضع وجهك أمام الكاميرا'); } if (!face.wellPositioned) { return _message('قم بتوسيط وجهك في المربع'); } return const SizedBox.shrink(); }, ), ); } Widget _message(String msg) => Padding( padding: const EdgeInsets.symmetric(horizontal: 55, vertical: 15), child: Text( msg, textAlign: TextAlign.center, style: const TextStyle( fontSize: 14, height: 1.5, fontWeight: FontWeight.w400, ), ), ); } </code>
class SmartFaceCameraWidget extends StatefulWidget {
  final bool loading;
  final bool showCameraLensControl;
  final void Function(File?) onCapture;

  const SmartFaceCameraWidget({
    super.key,
    this.loading = false,
    required this.showCameraLensControl,
    required this.onCapture,
  });

  @override
  SmartFaceCameraWidgetState createState() => SmartFaceCameraWidgetState();
}

class SmartFaceCameraWidgetState extends State<SmartFaceCameraWidget> {
  late FaceCameraController _controller;

  @override
  void initState() {
    super.initState();
    _controller = FaceCameraController(
      onCapture: widget.onCapture,
      defaultCameraLens: CameraLens.front,
    );
  }

  @override
  Widget build(BuildContext context) {
    return Container(
      margin: const EdgeInsets.only(top: 30),
      height: 600.h,
      child: SmartFaceCamera(
        controller: _controller,
        showCaptureControl: true,
        showFlashControl: false,
        showCameraLensControl: widget.showCameraLensControl,
        captureControlBuilder: (context, _) {
          return widget.loading
              ? SizedBox(
                  height: AppSize.s54.h,
                  child: const Center(child: CircularProgressIndicator()),
                )
              : Container(
                  alignment: Alignment.center,
                  width: AppSize.s200.w,
                  height: AppSize.s54.h,
                  decoration: BoxDecoration(
                    borderRadius: BorderRadius.circular(AppSize.s20),
                    color: AppColors.primary,
                  ),
                  padding: EdgeInsets.symmetric(
                      horizontal: AppPadding.p8.w, vertical: AppPadding.p2.h),
                  child: Text(
                    AppStrings.captureImageCamera,
                    textAlign: TextAlign.center,
                    style: getAppSemiBoldTextStyle(
                        color: AppColors.white, fontSize: FontSize.s16.spMin),
                  ),
                );
        },
        lensControlIcon: CircleAvatar(
          backgroundColor: AppColors.white,
          radius: AppSize.s26.r,
          child: Icon(
            Icons.cameraswitch,
            size: AppSize.s40.r,
            color: AppColors.primary,
          ),
        ),
        messageBuilder: (context, face) {
          if (face == null) {
            return _message('ضع وجهك أمام الكاميرا');
          }
          if (!face.wellPositioned) {
            return _message('قم بتوسيط وجهك في المربع');
          }
          return const SizedBox.shrink();
        },
      ),
    );
  }

  Widget _message(String msg) => Padding(
        padding: const EdgeInsets.symmetric(horizontal: 55, vertical: 15),
        child: Text(
          msg,
          textAlign: TextAlign.center,
          style: const TextStyle(
            fontSize: 14,
            height: 1.5,
            fontWeight: FontWeight.w400,
          ),
        ),
      );
}

and this is my recognizer

Plain text
Copy to clipboard
Open code in new window
EnlighterJS 3 Syntax Highlighter
<code>class Recognizer {
late Interpreter interpreter;
late InterpreterOptions _interpreterOptions;
static const int WIDTH = 160;
static const int HEIGHT = 160;
Map<String,Recognition> registered = {};
// String get modelName => 'assets/mobile_face_net.tflite';
String get modelName => 'assets/facenet.tflite';
Recognizer({int? numThreads}) {
_interpreterOptions = InterpreterOptions();
if (numThreads != null) {
_interpreterOptions.threads = numThreads;
}
loadModel();
}
void registerFaceInDB(context , List<double> embedding) async {
AppPreferences.setUserEmbedding(embedding.join(",")) ;
// debugPrint("embedding ${AppConstants.embedding}" );
// GoRouter.of(context).go( Routes.homeRout );
}
Future<void> loadModel() async {
try {
interpreter = await Interpreter.fromAsset(modelName);
} catch (e) {
debugPrint('Unable to create interpreter, Caught Exception: ${e.toString()}');
}
}
List<dynamic> imageToArray(img.Image inputImage){
img.Image resizedImage = img.copyResize(inputImage, width: WIDTH, height: HEIGHT);
List<double> flattenedList = resizedImage.data!.expand(
(channel) => [channel.r, channel.g, channel.b]).map(
(value) => value.toDouble()).toList();
Float32List float32Array = Float32List.fromList(flattenedList);
int channels = 3;
int height = HEIGHT;
int width = WIDTH;
Float32List reshapedArray = Float32List(1 * height * width * channels);
for (int c = 0; c < channels; c++) {
for (int h = 0; h < height; h++) {
for (int w = 0; w < width; w++) {
int index = c * height * width + h * width + w;
reshapedArray[index] = (float32Array[c * height * width + h * width + w]-127.5)/127.5;
}
}
}
// return reshapedArray.reshape([1,112,112,3]);
return reshapedArray.reshape([1,160,160,3]);
}
Recognition recognize(img.Image image, Rect location) {
//TODO crop face from image resize it and convert it to float array
var input = imageToArray(image);
debugPrint(input.shape.toString());
//TODO output array
// List output = List.filled(1*192, 0).reshape([1,192]);
List output = List.filled(1*512, 0).reshape([1,512]);
//TODO performs inference
final runs = DateTime.now().millisecondsSinceEpoch;
interpreter.run(input, output);
final run = DateTime.now().millisecondsSinceEpoch - runs;
debugPrint('Time to run inference: $run ms$output');
//TODO convert dynamic list to double list
List<double> outputArray = output.first.cast<double>();
//TODO looks for the nearest embeeding in the database and returns the pair
Pair pair = findNearest(outputArray);
debugPrint("distance= ${pair.distance}");
return Recognition(pair.name,location,outputArray,pair.distance);
}
List<double> getEmbedding(img.Image image, Rect location) {
//TODO crop face from image resize it and convert it to float array
var input = imageToArray(image);
debugPrint(input.shape.toString());
//TODO output array
// List output = List.filled(1*192, 0).reshape([1,192]);
List output = List.filled(1*512, 0).reshape([1,512]);
//TODO performs inference
final runs = DateTime.now().millisecondsSinceEpoch;
interpreter.run(input, output);
final run = DateTime.now().millisecondsSinceEpoch - runs;
debugPrint('Time to run inference: $run ms$output');
//TODO convert dynamic list to double list
return output.first.cast<double>();
}
//TODO looks for the nearest embeeding in the database and returns the pair which contain information of registered face with which face is most similar
findNearest(List<double> emb){
Pair pair = Pair(" ليست ${UserData.fullName} ", -5);
// for (MapEntry<String, Recognition> item in registered.entries) {
// final String name = item.key;
List<double> knownEmb = AppConstants.embedding ; //item.value.embeddings;
double distance = 0;
for (int i = 0; i < emb.length; i++) {
double diff = emb[i] -
knownEmb[i];
distance += diff*diff;
}
distance = sqrt(distance);
if (pair.distance == -5 || distance < pair.distance) {
pair.distance = distance;
if( distance < 1) pair.name = UserData.fullName;
}
// }
return pair;
}
void close() {
interpreter.close();
}
}
class Pair{
String name;
double distance;
Pair(this.name,this.distance);
}
</code>
<code>class Recognizer { late Interpreter interpreter; late InterpreterOptions _interpreterOptions; static const int WIDTH = 160; static const int HEIGHT = 160; Map<String,Recognition> registered = {}; // String get modelName => 'assets/mobile_face_net.tflite'; String get modelName => 'assets/facenet.tflite'; Recognizer({int? numThreads}) { _interpreterOptions = InterpreterOptions(); if (numThreads != null) { _interpreterOptions.threads = numThreads; } loadModel(); } void registerFaceInDB(context , List<double> embedding) async { AppPreferences.setUserEmbedding(embedding.join(",")) ; // debugPrint("embedding ${AppConstants.embedding}" ); // GoRouter.of(context).go( Routes.homeRout ); } Future<void> loadModel() async { try { interpreter = await Interpreter.fromAsset(modelName); } catch (e) { debugPrint('Unable to create interpreter, Caught Exception: ${e.toString()}'); } } List<dynamic> imageToArray(img.Image inputImage){ img.Image resizedImage = img.copyResize(inputImage, width: WIDTH, height: HEIGHT); List<double> flattenedList = resizedImage.data!.expand( (channel) => [channel.r, channel.g, channel.b]).map( (value) => value.toDouble()).toList(); Float32List float32Array = Float32List.fromList(flattenedList); int channels = 3; int height = HEIGHT; int width = WIDTH; Float32List reshapedArray = Float32List(1 * height * width * channels); for (int c = 0; c < channels; c++) { for (int h = 0; h < height; h++) { for (int w = 0; w < width; w++) { int index = c * height * width + h * width + w; reshapedArray[index] = (float32Array[c * height * width + h * width + w]-127.5)/127.5; } } } // return reshapedArray.reshape([1,112,112,3]); return reshapedArray.reshape([1,160,160,3]); } Recognition recognize(img.Image image, Rect location) { //TODO crop face from image resize it and convert it to float array var input = imageToArray(image); debugPrint(input.shape.toString()); //TODO output array // List output = List.filled(1*192, 0).reshape([1,192]); List output = List.filled(1*512, 0).reshape([1,512]); //TODO performs inference final runs = DateTime.now().millisecondsSinceEpoch; interpreter.run(input, output); final run = DateTime.now().millisecondsSinceEpoch - runs; debugPrint('Time to run inference: $run ms$output'); //TODO convert dynamic list to double list List<double> outputArray = output.first.cast<double>(); //TODO looks for the nearest embeeding in the database and returns the pair Pair pair = findNearest(outputArray); debugPrint("distance= ${pair.distance}"); return Recognition(pair.name,location,outputArray,pair.distance); } List<double> getEmbedding(img.Image image, Rect location) { //TODO crop face from image resize it and convert it to float array var input = imageToArray(image); debugPrint(input.shape.toString()); //TODO output array // List output = List.filled(1*192, 0).reshape([1,192]); List output = List.filled(1*512, 0).reshape([1,512]); //TODO performs inference final runs = DateTime.now().millisecondsSinceEpoch; interpreter.run(input, output); final run = DateTime.now().millisecondsSinceEpoch - runs; debugPrint('Time to run inference: $run ms$output'); //TODO convert dynamic list to double list return output.first.cast<double>(); } //TODO looks for the nearest embeeding in the database and returns the pair which contain information of registered face with which face is most similar findNearest(List<double> emb){ Pair pair = Pair(" ليست ${UserData.fullName} ", -5); // for (MapEntry<String, Recognition> item in registered.entries) { // final String name = item.key; List<double> knownEmb = AppConstants.embedding ; //item.value.embeddings; double distance = 0; for (int i = 0; i < emb.length; i++) { double diff = emb[i] - knownEmb[i]; distance += diff*diff; } distance = sqrt(distance); if (pair.distance == -5 || distance < pair.distance) { pair.distance = distance; if( distance < 1) pair.name = UserData.fullName; } // } return pair; } void close() { interpreter.close(); } } class Pair{ String name; double distance; Pair(this.name,this.distance); } </code>
class Recognizer {
  late Interpreter interpreter;
  late InterpreterOptions _interpreterOptions;
  static const int WIDTH = 160;
  static const int HEIGHT = 160;
  Map<String,Recognition> registered = {};
  // String get modelName => 'assets/mobile_face_net.tflite';
  String get modelName => 'assets/facenet.tflite';

  Recognizer({int? numThreads}) {
    _interpreterOptions = InterpreterOptions();

    if (numThreads != null) {
      _interpreterOptions.threads = numThreads;
    }
    loadModel();
  }


  void registerFaceInDB(context , List<double> embedding) async {
 AppPreferences.setUserEmbedding(embedding.join(",")) ;
    // debugPrint("embedding   ${AppConstants.embedding}" );

    // GoRouter.of(context).go( Routes.homeRout );
  }


  Future<void> loadModel() async {
    try {
      interpreter = await Interpreter.fromAsset(modelName);
    } catch (e) {
      debugPrint('Unable to create interpreter, Caught Exception: ${e.toString()}');
    }
  }

  List<dynamic> imageToArray(img.Image inputImage){
    img.Image resizedImage = img.copyResize(inputImage, width: WIDTH, height: HEIGHT);
    List<double> flattenedList = resizedImage.data!.expand(
            (channel) => [channel.r, channel.g, channel.b]).map(
            (value) => value.toDouble()).toList();
    Float32List float32Array = Float32List.fromList(flattenedList);
    int channels = 3;
    int height = HEIGHT;
    int width = WIDTH;
    Float32List reshapedArray = Float32List(1 * height * width * channels);
    for (int c = 0; c < channels; c++) {
      for (int h = 0; h < height; h++) {
        for (int w = 0; w < width; w++) {
          int index = c * height * width + h * width + w;
          reshapedArray[index] = (float32Array[c * height * width + h * width + w]-127.5)/127.5;
        }
      }
    }
    // return reshapedArray.reshape([1,112,112,3]);
    return reshapedArray.reshape([1,160,160,3]);
  }

  Recognition recognize(img.Image image, Rect location) {

    //TODO crop face from image resize it and convert it to float array
    var input = imageToArray(image);
    debugPrint(input.shape.toString());

    //TODO output array
    // List output = List.filled(1*192, 0).reshape([1,192]);
    List output = List.filled(1*512, 0).reshape([1,512]);

    //TODO performs inference
    final runs = DateTime.now().millisecondsSinceEpoch;
    interpreter.run(input, output);
    final run = DateTime.now().millisecondsSinceEpoch - runs;
    debugPrint('Time to run inference: $run ms$output');

    //TODO convert dynamic list to double list
     List<double> outputArray = output.first.cast<double>();

     //TODO looks for the nearest embeeding in the database and returns the pair
     Pair pair = findNearest(outputArray);
     debugPrint("distance= ${pair.distance}");

     return Recognition(pair.name,location,outputArray,pair.distance);
  }

  List<double> getEmbedding(img.Image image, Rect location) {

    //TODO crop face from image resize it and convert it to float array
    var input = imageToArray(image);
    debugPrint(input.shape.toString());

    //TODO output array
    // List output = List.filled(1*192, 0).reshape([1,192]);
    List output = List.filled(1*512, 0).reshape([1,512]);

    //TODO performs inference
    final runs = DateTime.now().millisecondsSinceEpoch;
    interpreter.run(input, output);
    final run = DateTime.now().millisecondsSinceEpoch - runs;
    debugPrint('Time to run inference: $run ms$output');

    //TODO convert dynamic list to double list
    return output.first.cast<double>();

  }



  //TODO  looks for the nearest embeeding in the database and returns the pair which contain information of registered face with which face is most similar
  findNearest(List<double> emb){
    Pair pair = Pair(" ليست ${UserData.fullName} ", -5);
    // for (MapEntry<String, Recognition> item in registered.entries) {
    //   final String name = item.key;
      List<double> knownEmb = AppConstants.embedding ; //item.value.embeddings;
      double distance = 0;
      for (int i = 0; i < emb.length; i++) {
        double diff = emb[i] -
            knownEmb[i];
        distance += diff*diff;
      }
      distance = sqrt(distance);
      if (pair.distance == -5 || distance < pair.distance) {
        pair.distance = distance;
       if( distance < 1)   pair.name = UserData.fullName;
      }
    // }
    return pair;
  }

  void close() {
    interpreter.close();
  }

}
class Pair{
   String name;
   double distance;
   Pair(this.name,this.distance);
}


I can’t trak the error because it’s on the release version I don’t know really what to do.

I tried to many solutions but still the same.
I don’t know what is the issue here.

Trang chủ Giới thiệu Sinh nhật bé trai Sinh nhật bé gái Tổ chức sự kiện Biểu diễn giải trí Dịch vụ khác Trang trí tiệc cưới Tổ chức khai trương Tư vấn dịch vụ Thư viện ảnh Tin tức - sự kiện Liên hệ Chú hề sinh nhật Trang trí YEAR END PARTY công ty Trang trí tất niên cuối năm Trang trí tất niên xu hướng mới nhất Trang trí sinh nhật bé trai Hải Đăng Trang trí sinh nhật bé Khánh Vân Trang trí sinh nhật Bích Ngân Trang trí sinh nhật bé Thanh Trang Thuê ông già Noel phát quà Biểu diễn xiếc khỉ Xiếc quay đĩa Dịch vụ tổ chức sự kiện 5 sao Thông tin về chúng tôi Dịch vụ sinh nhật bé trai Dịch vụ sinh nhật bé gái Sự kiện trọn gói Các tiết mục giải trí Dịch vụ bổ trợ Tiệc cưới sang trọng Dịch vụ khai trương Tư vấn tổ chức sự kiện Hình ảnh sự kiện Cập nhật tin tức Liên hệ ngay Thuê chú hề chuyên nghiệp Tiệc tất niên cho công ty Trang trí tiệc cuối năm Tiệc tất niên độc đáo Sinh nhật bé Hải Đăng Sinh nhật đáng yêu bé Khánh Vân Sinh nhật sang trọng Bích Ngân Tiệc sinh nhật bé Thanh Trang Dịch vụ ông già Noel Xiếc thú vui nhộn Biểu diễn xiếc quay đĩa Dịch vụ tổ chức tiệc uy tín Khám phá dịch vụ của chúng tôi Tiệc sinh nhật cho bé trai Trang trí tiệc cho bé gái Gói sự kiện chuyên nghiệp Chương trình giải trí hấp dẫn Dịch vụ hỗ trợ sự kiện Trang trí tiệc cưới đẹp Khởi đầu thành công với khai trương Chuyên gia tư vấn sự kiện Xem ảnh các sự kiện đẹp Tin mới về sự kiện Kết nối với đội ngũ chuyên gia Chú hề vui nhộn cho tiệc sinh nhật Ý tưởng tiệc cuối năm Tất niên độc đáo Trang trí tiệc hiện đại Tổ chức sinh nhật cho Hải Đăng Sinh nhật độc quyền Khánh Vân Phong cách tiệc Bích Ngân Trang trí tiệc bé Thanh Trang Thuê dịch vụ ông già Noel chuyên nghiệp Xem xiếc khỉ đặc sắc Xiếc quay đĩa thú vị
Trang chủ Giới thiệu Sinh nhật bé trai Sinh nhật bé gái Tổ chức sự kiện Biểu diễn giải trí Dịch vụ khác Trang trí tiệc cưới Tổ chức khai trương Tư vấn dịch vụ Thư viện ảnh Tin tức - sự kiện Liên hệ Chú hề sinh nhật Trang trí YEAR END PARTY công ty Trang trí tất niên cuối năm Trang trí tất niên xu hướng mới nhất Trang trí sinh nhật bé trai Hải Đăng Trang trí sinh nhật bé Khánh Vân Trang trí sinh nhật Bích Ngân Trang trí sinh nhật bé Thanh Trang Thuê ông già Noel phát quà Biểu diễn xiếc khỉ Xiếc quay đĩa
Thiết kế website Thiết kế website Thiết kế website Cách kháng tài khoản quảng cáo Mua bán Fanpage Facebook Dịch vụ SEO Tổ chức sinh nhật