This error pops out on clicking Sign up Button

It no longer detects face neither in Sign Up nor in Sign In.

After getting user not found in sign in page, the camera and face painter should get reset

I pulled the code then did a flutter pub update. Installed all the ndk requirements. Upgraded to Android 31 / update gradles/ update kotlin

I used a pixel 2 and a pixel 5. The code picks up my face in sign in but not in sigh up. I think its something to do with the camera dimensions but I would know where to look right now.

when I click sign up button getting below error :

Unhandled Exception: 'package:face_net_authentication/services/camera.service.dart': Failed assertion: line 66 pos 9: '_cameraController!.value.previewSize != null': Preview size is null

Thanks in advance for your help.

It will be continous loop of loading the screen but never renders.

Hello thank you so much for your code.

I been studying your code for almost 2 weeks already and I was able understand the flow of it. But sometimes this error occur when I click CAPTURE. Have you ever experience this error ?

CameraException(error, Attempt to invoke virtual method 'int android.hardware.camera2.CameraCaptureSession.capture(android.hardware.camera2.CaptureRequest, android.hardware.camera2.CameraCaptureSession$CaptureCallback, android.os.Handler)' on a null object reference)

When I want to access the sign up page, an exception is caught by the widgets library and the relevant error-causing widget was signup on the on the home page . Can anyone help me with this error.

Can you update the Image package from version 3.0.2 to 4.0.17? I tried to do it but without success.

The snippet in "image_converter.dart" is not working in new version

img.data[index] = hexFF | (b << 16) | (g << 8) | r;

Login is successful if the image is taken immediately after login.
But if you Sign up and rotate 180 degrees and take picture it wont sign up

I can't see the green square on face detection.

please help.

thanks m

i try to run in flutter 2.10.4 ,
got message no face detection, but the _faceDetectorService.faces is not empty

when you sign up with wall watch behind you, and then login and put the camera on the watch it will logs you in!!

Hi, thanks for putting together this repo and the accompanying Medium post, it's great work!

I want to use the face detection and face recognition code from your repo, and I realize I can do so under the BSD 3-clause license, but it seems like this functionality would be generally useful, and I'd rather depend on your repo rather than copy your code into mine.

Would you consider splitting out a separate library for just the services, and any supporting classes such as FacePainter, so that it's trivially easy for someone to embed a face recognition view into an app using your library?

please what is the function of the jniLibs in the project?
aside from that I would like to commend the amount of work put into this kudos

I/flutter (12759): Failed to load model.
I/flutter (12759): Invalid argument(s): Failed to lookup symbol (undefined symbol: TfLiteGpuDelegateV2Create)

I want to put this code in a separate project, I've matched the package versions, and did the following initial setup: https://pub.dev/packages/tflite_flutter#important-initial-setup--add-dynamic-libraries-to-your-app

But when i open sign in page, and only sign in page, it's throw an error : Interpreter is null from setCurrentPrediction method in ml_service.dart. In the sign up page, everything works very well.

Should there be another model for the back camera?

I tried to build the project and got a dozen errors...The above was one of them

Problem : https://ibb.co/3rn1DNX

I face this issue when run on iOS, is there any way to resolve it ?

I have an issue where it isn't exactly matching faces accurately at all. I've got one face registered and it lets nearly everyone sign in to that profile.

Hi, I'm having trouble with the model.

I compared the _euclideanDistance of array result from frames of my face, it yields the distance around .7-.9, which is below
the threshold, which is correct.

However, when I compare the array result of my face with my sister's face, it also yields the same distance, around .7-.9, which is still below the threshold, while it shouldn't be.

I tested it on both Android and iOS, it shows the same result

Hi Mr MCarlomagno, thanks for the code, it's very heplful. But, I have a problem in field faceDetected. Can you tell me, why? Here's the warning. Thank You. Have a great day.

════════ Exception caught by widgets library ═══════════════════════════════════
The following LateError was thrown building FutureBuilder(dirty, dependencies: [MediaQuery], state: _FutureBuilderState#14457):
LateInitializationError: Field 'faceDetected' has not been initialized.

Face is not recognizing in sign up page.
Facedetect is always null inside the app.

really I like your solution, but can we use anti spoof mode because when user show image image bypass auth?

Hi Marcos, Great work!

I just noticed that if you sign up your face and try to sign it up again, it doesn't recognize that your face is already registered and just go and register another face of yours. Could there be any possibility that you could implement a feature where it knows that the face is already registered.

Thank you.

https://developers.google.com/ml-kit/migration/android#new
Since we are not using Firebase's cloud component it is wiser to move to the ML kit.
I don't think there is a library yet.

Here are some of the print statements that I have used in the database.dart file:

jsonFile.writeAsStringSync(json.encode(_db)) is:{"Waqad:123456":null}
userAndPass is: Waqad:123456
I/flutter (22884): _db[userAndPass] is: null
I/flutter (22884): modelData is: null

this._db in loadDB() is: {Waqad:123456: null}
_db is: {Waqad:123456: null}

in loadModel() is:
I/SurfaceView(22884): updateWindow -- setFrame, this = io.flutter.embedding.android.FlutterSurfaceView{cec499 V.E...... ......I. 0,0-720,1192}
I/flutter (22884): Failed to load model.

and What I do not understand is that why "NoSuchMethodError: The method 'run' was called on null." is thrown when pre-process input and output is not empty:
[again some of the prints I used]

eglCreateImageKHR:539: [Crop] 0 0 0 0 img[960 540]
D/MALI (22884): eglCreateImageKHR:539: [Crop] 0 0 0 0 img[960 540]
I/flutter (22884): convertedBytes.buffer.asFloat32List() is: [-0.734375, -0.7109375, -0.765625, -0.734375, -0.7265625, -0.78125, -0.7109375, -0.734375, -0.78125, -0.8046875, -0.84375, -0.875, -0.8671875, -0.8984375, -0.9296875, -0.9296875, -0.9296875, -0.9375, -0.9375, -0.9609375, -0.9453125, -0.9375, -0.96875, -0.96875, -0.9765625, -0.9765625, -0.96875, -0.96875, -0.96875, -0.9609375, -0.9609375, -0.984375, -0.953125, -0.953125, -0.9765625, -0.9453125, -0.953125, -0.9765625, -0.9453125, -0.96875, -0.9765625, -0.9453125, -0.96875, -0.9765625, -0.9453125, -0.9609375, -0.984375, -0.953125, -0.96875, -0.9765625, -0.9453125, -0.953125, -0.9765625, -0.9765625, -0.9765625, -0.984375, -0.953125, -0.96875, -0.9765625, -0.9453125, -0.9609375, -0.96875, -0.9375, -0.9453125, -0.96875, -0.9375, -0.9453125, -0.9765625, -0.9765625, -0.953125, -0.9765625, -0.9609375, -0.953125, -0.9765625, -0.9609375, -0.9453125, -0.96875, -0.953125, -0.9453125, -0.96875, -0.953125, -0.9609375, -0.96875, -0.9375, -0.9453125, -0.96875, -0.9375, -0.96875, -0.9
I/flutter (22884): imageAsList = [-0.734375, -0.7109375, -0.765625, -0.734375, -0.7265625, -0.78125, -0.7109375, -0.734375, -0.78125, -0.8046875, -0.84375, -0.875, -0.8671875, -0.8984375, -0.9296875, -0.9296875, -0.9296875, -0.9375, -0.9375, -0.9609375, -0.9453125, -0.9375, -0.96875, -0.96875, -0.9765625, -0.9765625, -0.96875, -0.96875, -0.96875, -0.9609375, -0.9609375, -0.984375, -0.953125, -0.953125, -0.9765625, -0.9453125, -0.953125, -0.9765625, -0.9453125, -0.96875, -0.9765625, -0.9453125, -0.96875, -0.9765625, -0.9453125, -0.9609375, -0.984375, -0.953125, -0.96875, -0.9765625, -0.9453125, -0.953125, -0.9765625, -0.9765625, -0.9765625, -0.984375, -0.953125, -0.96875, -0.9765625, -0.9453125, -0.9609375, -0.96875, -0.9375, -0.9453125, -0.96875, -0.9375, -0.9453125, -0.9765625, -0.9765625, -0.953125, -0.9765625, -0.9609375, -0.953125, -0.9765625, -0.9609375, -0.9453125, -0.96875, -0.953125, -0.9453125, -0.96875, -0.953125, -0.9609375, -0.96875, -0.9375, -0.9453125, -0.96875, -0.9375, -0.96875, -0.9765625, -0.9453125, -0.95312
D/MALI (22884): eglCreateImageKHR:539: [Crop] 0 0 0 0 img[960 540]
I/flutter (22884): pre-process input is: [-0.734375, -0.7109375, -0.765625, -0.734375, -0.7265625, -0.78125, -0.7109375, -0.734375, -0.78125, -0.8046875, -0.84375, -0.875, -0.8671875, -0.8984375, -0.9296875, -0.9296875, -0.9296875, -0.9375, -0.9375, -0.9609375, -0.9453125, -0.9375, -0.96875, -0.96875, -0.9765625, -0.9765625, -0.96875, -0.96875, -0.96875, -0.9609375, -0.9609375, -0.984375, -0.953125, -0.953125, -0.9765625, -0.9453125, -0.953125, -0.9765625, -0.9453125, -0.96875, -0.9765625, -0.9453125, -0.96875, -0.9765625, -0.9453125, -0.9609375, -0.984375, -0.953125, -0.96875, -0.9765625, -0.9453125, -0.953125, -0.9765625, -0.9765625, -0.9765625, -0.984375, -0.953125, -0.96875, -0.9765625, -0.9453125, -0.9609375, -0.96875, -0.9375, -0.9453125, -0.96875, -0.9375, -0.9453125, -0.9765625, -0.9765625, -0.953125, -0.9765625, -0.9609375, -0.953125, -0.9765625, -0.9609375, -0.9453125, -0.96875, -0.953125, -0.9453125, -0.96875, -0.953125, -0.9609375, -0.96875, -0.9375, -0.9453125, -0.96875, -0.9375, -0.96875, -0.9765625, -0.9453125,
I/flutter (22884): pre-process reshaped input is: [[[[-0.734375, -0.7109375, -0.765625], [-0.734375, -0.7265625, -0.78125], [-0.7109375, -0.734375, -0.78125], [-0.8046875, -0.84375, -0.875], [-0.8671875, -0.8984375, -0.9296875], [-0.9296875, -0.9296875, -0.9375], [-0.9375, -0.9609375, -0.9453125], [-0.9375, -0.96875, -0.96875], [-0.9765625, -0.9765625, -0.96875], [-0.96875, -0.96875, -0.9609375], [-0.9609375, -0.984375, -0.953125], [-0.953125, -0.9765625, -0.9453125], [-0.953125, -0.9765625, -0.9453125], [-0.96875, -0.9765625, -0.9453125], [-0.96875, -0.9765625, -0.9453125], [-0.9609375, -0.984375, -0.953125], [-0.96875, -0.9765625, -0.9453125], [-0.953125, -0.9765625, -0.9765625], [-0.9765625, -0.984375, -0.953125], [-0.96875, -0.9765625, -0.9453125], [-0.9609375, -0.96875, -0.9375], [-0.9453125, -0.96875, -0.9375], [-0.9453125, -0.9765625, -0.9765625], [-0.953125, -0.9765625, -0.9609375], [-0.953125, -0.9765625, -0.9609375], [-0.9453125, -0.96875, -0.953125], [-0.9453125, -0.96875, -0.953125], [-0.9609375, -0.96875, -0.9375]
I/flutter (22884): pre-process output is: [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
I/flutter (22884): NoSuchMethodError: The method 'run' was called on null.
I/flutter (22884): Receiver: null
I/flutter (22884): Tried calling: run(Instance(length:1) of '_GrowableList', Instance(length:1) of '_GrowableList')
I/CameraFramework(22884): handleMessage: 2
I/CameraFramework(22884): handleMessage: 128
I/CameraFramework(22884): handleMessage: 256
I/RequestThread-1(22884): Received jpeg.
I/RequestThread-1(22884): Producing jpeg buffer...
D/Surface (22884): Surface::setBuffersUserDimensions(this=0x7f5aa6f600,w=496,h=496)

Thanks.

Sign Up screen issue
using camera preview, face in detected in the frame but the custom face painter is painting the box somewhere else

i had a problem using tflite_flutter on ios, and i encountered an error like this

flutter: Failed to load model.
flutter: Invalid argument(s): Failed to lookup symbol 'TFLGpuDelegateCreate': dlsym(RTLD_DEFAULT, TFLGpuDelegateCreate): symbol not found

Please help, thanks

--
tflite_flutter: ^0.9.0

I run this app on my Android device then everything works fine. But when running on IOS after I debug, the _convertCameraImage method does not return results. It seems that in that method there is too much computation so it doesn't work on iOS or something like that. Please give me a way to solve this problem. Thank you.

link- https://www.youtube.com/watch?v=0vkrISy4J_o

I'm having some errors when running this app on IOS as below:

Modules Issue (Xcode): Definition of 'MLKText' must be imported from module 'MLKitTextRecognitionCommon.MLKText' before it is required
/Users/dev.prog/.pub-cache/hosted/pub.dartlang.org/google_ml_kit-0.5.1/ios/Classes/vision/TextRecognizer.m:41:41

Modules Issue (Xcode): Definition of 'MLKTextBlock' must be imported from module 'MLKitTextRecognitionCommon.MLKTextBlock' before it is required
/Users/dev.prog/.pub-cache/hosted/pub.dartlang.org/google_ml_kit-0.5.1/ios/Classes/vision/TextRecognizer.m:48:32

Modules Issue (Xcode): Definition of 'MLKTextLine' must be imported from module 'MLKitTextRecognitionCommon.MLKTextLine' before it is required

using flutter version 3.5.0

Does anyone have any idea on how to migrate this code to flutter 2.10 because this code is in flutter 2.7 and there have many syntax changes since then. So can anyone please help? @peterlazar1993 @MCarlomagno

no green square or face detection

It will recognize any face as User 1, as long as it detected as human face. any face can be recognize and sign in as same user

Hi Mr MCarlomagno, can this app using online database like MYSQL, etc. using Rest API ?

Good job and good project.
But I tried it with 1 photo and the app still accepts. Is there any way to prevent this?

Hello @MCarlomagno , very nice work, thanks for you blog thats so enlightened me, but can i want ask something about mobilefacenet output size, is there any reason for using 192 as output size of mobilefacenet model

List output = [];
output = List(1 * 192).reshape([1, 192]);

what is ' List(1*192)' ?

when i clicekd capture button in sigin screen , getting Null check operator used on a null value.

please anyone assist to resolve this, Thanks in advanced,

When i using Android Emulstor build app and it going to the splash screen and ask permission after i click the app is Lost connection to device .
And maybe is my emulator has not enough memory capacity ?
The Error code:

My emulator equipment

Currently the project is on 2.12 and I tried to import it to 2.16 but I am getting runtime errors. @MCarlomagno can you help me out?

Hi @MCarlomagno thanks for share your job, is amazing.

I have a problem, I save my photo and the array resulting of predictedData on my back end database with a API REST, when I Sign In and Sign Up in a ios-ios or android-android no problem, but when i try authenticate cross platform the distance result different i see the array save on my back end and are different in this case. (can you see this more low)

I think the problem is in the function _convertCameraImage, because android and ios use different formats (android -> yuv and ios -> bgra), but i understand this function _convertCameraImage convert to the yuv -> bgra, so i don't understanding because the result on the predictedData is very different

this is my code adapted to the android and ios support

imglib.Image _convertCameraImage(CameraImage image, CameraLensDirection _dir) {
    print('_convertCameraImage');
    if( GetPlatform.isAndroid == true ){
      print(' Android');
      int width = image.width; print('11'); print(width);
      int height = image.height; print('12'); print(height);
      var img = imglib.Image(width, height); print('13');
      const int hexFF = 0xFF000000; print('14');
      print( 'image.planes.length=>' + image.planes.length.toString());
      print(image.planes[0].bytesPerRow);
      final int uvyButtonStride = image.planes[1].bytesPerRow; print('15');
      final int uvPixelStride = image.planes[1].bytesPerPixel; print('16');
      for (int x = 0; x < width; x++) {
        for (int y = 0; y < height; y++) {
          final int uvIndex = uvPixelStride * (x / 2).floor() + uvyButtonStride * (y / 2).floor();
          final int index = y * width + x;
          final yp = image.planes[0].bytes[index];
          final up = image.planes[1].bytes[uvIndex];
          final vp = image.planes[2].bytes[uvIndex];
          int r = (yp + vp * 1436 / 1024 - 179).round().clamp(0, 255);
          int g = (yp - up * 46549 / 131072 + 44 - vp * 93604 / 131072 + 91).round().clamp(0, 255);
          int b = (yp + up * 1814 / 1024 - 227).round().clamp(0, 255);
          img.data[index] = hexFF | (b << 16) | (g << 8) | r;
        }
      }
      print('17');
      var img1 = imglib.copyRotate(img, -90);
      print(img1.toString());
      return img1;
    }else{
      print(' IOS');
      imglib.Image img = imglib.Image.fromBytes(
        image.width,
        image.height,
        image.planes[0].bytes,
        format: imglib.Format.bgra,
      );
      var img1 = (_dir == CameraLensDirection.front)
          ? imglib.copyRotate(img, -90)
          : imglib.copyRotate(img, 90);
      print('retorno');
      print(img1.toString());
      return img1;
    }
    
  }

This is the result of my test

IOS SignUp-IOS Sign In [works fine]
ANDROID SignUp-ANDROID Sign In [works fine]
IOS SignUp-ANDROID Sign In [don't authenticate]
ANDROID SignUp-IOS Sign In [don't authenticate]

I log my results
IOS SignUp-IOS SignIn
// flutter: calculandoDistancia
// flutter: currDist=>0.7708154422560634
// flutter: threshold=>1.0
// flutter: minDist=>0.7708154422560634
// flutter: end setPredictedData
// flutter: authenticate OK

ANDROID SignUp-ANDROID SignIn
// flutter ( 8968): calculandoDistancia
// flutter ( 8968): currDist=>0.6422662304939313
// flutter ( 8968): threshold=>1.0
// flutter ( 8968): minDist=>0.6422662304939313
// flutter ( 8968): end setPredictedData
// flutter ( 8968): authenticate OK

IOS SignUp-ANDROID SignIn
// flutter (19459): calculandoDistancia
// flutter (19459): currDist=>1.4399978617184572
// flutter (19459): threshold=>1.0
// flutter (19459): minDist=>999.0
// flutter (19459): end setPredictedData
// flutter (19459): don't authenticate

ANDROID SignUp-IOS SignIn
// flutter: calculandoDistancia
// flutter: currDist=>1.4992889685122506
// flutter: threshold=>1.0
// flutter: minDist=>999.0
// flutter: end setPredictedData
// flutter: don't authenticate

The predictedData saved (for the same face) is here, and is very different in android and ios

With IOS
[-0.005366702564060688, 0.03501761332154274, 0.016875134781003, 0.0008109764894470572, -0.07175101339817047, 0.09405621886253357, -0.05950654298067093, 0.05654291436076164, -0.0009066364145837724, -0.030182218179106712, -0.029889754951000214, 0.0075845494866371155, -0.00888113770633936, 0.02600974030792713, 0.0004703785525634885, 0.00661942083388567, -0.025093356147408485, -0.015354325994849205, -0.00023305673676077276, 0.009817020036280155, -0.19247987866401672, 0.09031268209218979, -0.03433519974350929, 0.015412818640470505, -0.0217202790081501, 0.014701157808303833, -0.05307235196232796, 0.11292985081672668, 0.11714132130146027, -0.040593914687633514, -0.006721782963722944, 0.2812327742576599, 0.00556167820468545, 0.002247093478217721, -0.025229839608073235, 0.11261788755655289, 0.1094202920794487, -0.022480683401226997, 0.0022312516812235117, 0.03486163169145584, 0.013287585228681564, 0.00656580226495862, 0.01938057132065296, -0.017791520804166794, 0.009392947889864445, -0.06839743256568909, -0.11292985081672668, -0.035972993820905685, -0.01327783614397049, 0.07424669712781906, -0.04000898823142052, -0.008154853247106075, -0.18608468770980835, -0.0032780268229544163, -0.0868811160326004, 0.008096360601484776, 0.1081724464893341, 0.004223658237606287, -0.12166475504636765, 0.03511510044336319, 0.05743980407714844, -0.08188974112272263, -0.04991374537348747, -0.0866471454501152, -0.019146600738167763, -0.08508733659982681, -0.007964751683175564, 0.008457065559923649, 0.010167975910007954, 0.0048524546436965466, -0.038644157350063324, 0.09202846884727478, -0.05233144387602806, 0.010655415244400501, -0.09382224828004837, 0.01086988765746355, 0.003938506357371807, -0.002282432746142149, 0.2416137307882309, -0.019507305696606636, -0.012897633947432041, -0.027121102437376976, -0.014798645861446857, 0.1291518211364746, -0.11238391697406769, -0.0034656908828765154, -0.0029051359742879868, 0.011152602732181549, 0.05307235196232796, -0.1511450558900833, 0.0439474955201149, -0.0017815892351791263, 0.013560551218688488, -0.03493962064385414, -0.10770450532436371, -0.09124856442213058, -0.038215212523937225, 0.0656287744641304, 0.0009505058987997472, -0.0028832012321799994, 0.003543680999428034, -0.011874012649059296, -0.007121482864022255, -0.001653636572882533, -0.006395198870450258, 0.006283087655901909, -0.20339851081371307, 0.0008712970884516835, -0.005746904760599136, 0.015822267159819603, -0.02010198123753071, 0.010557927191257477, 0.004179788753390312, 0.27436962723731995, 0.014720655977725983, 0.14420393109321594, -0.00717022642493248, -0.03051367774605751, 0.00400918535888195, 0.10754852741956711, 0.26610267162323, -0.004287025425583124, -0.14404794573783875, -0.0010973468888550997, -0.0003805070009548217, -0.005079113412648439, 0.0077697765082120895, 0.002900261664763093, 0.005322833079844713, -0.03796174377202988, 0.01333632878959179, 0.028037486597895622, -0.003499811515212059, -0.02388450689613819, 0.06870938837528229, -0.014730404131114483, -0.1974712610244751, 0.011347577907145023, 0.0060296193696558475, 0.013950502499938011, -0.008208471350371838, 0.0019278209656476974, -0.0006574332364834845, -0.02831045351922512, -0.07572851330041885, 0.060676395893096924, -0.017918255180120468, -0.0022641539108008146, 0.01422346755862236, -0.014408694580197334, -0.009558677673339844, -0.029070857912302017, -0.05318933725357056, -0.031956497579813004, -0.009612295776605606, -0.0028417690191417933, 0.0025029988028109074, 0.013541053049266338, -0.07841917127370834, -0.0004280323046259582, -0.08391748368740082, 0.00179255660623312, -0.011825268156826496, 0.0017815892351791263, 0.005439818371087313, 0.02858341857790947, 0.016894632950425148, -0.13804270327091217, -0.0028637037612497807, 0.0006805866141803563, 0.23412667214870453, 0.11207196116447449, -0.0027832763735204935, -0.013433816842734814, 0.015968499705195427, 0.006487811915576458, -0.012429692782461643, -0.11277387291193008, -0.01536407507956028, 0.010450690984725952, -0.0436355322599411, 0.013316831551492214, -0.006326957140117884, -0.002563928719609976, 0.131959468126297, 0.10123131424188614, -0.13734079897403717, 0.0655507892370224, 0.10723656415939331, -0.08625718951225281, -0.07693736255168915, -0.008364452049136162]

With ANDROID
[0.017560526728630066, -0.0025206489954143763, -0.001565065118484199, -0.004763653036206961, -0.006009773351252079, 0.04073874652385712, 0.016540179029107094, 0.20969343185424805, 0.013223133981227875, 0.20780882239341736, 0.005943980999290943, -0.0026168033946305513, -0.006616274360567331, -0.01967291533946991, -0.004560244735330343, 0.0022333874367177486, -0.0006560852052643895, 0.006724789272993803, 0.007219155319035053, -0.006807046011090279, 0.059210970997810364, 0.008006574586033821, -0.0298028364777565, 0.0026111663319170475, -0.06040123477578163, -0.003707980504259467, 0.0029578227549791336, -0.03018888272345066, 0.1781667321920395, 0.011050385423004627, 0.005854886025190353, 0.017274057492613792, -0.09191303700208664, -0.006212593521922827, -0.2262837141752243, -0.15064898133277893, 0.1591326892375946, -0.006933901458978653, -0.001802279381081462, -0.10352537781000137, -0.0010443583596497774, 0.0018612570129334927, 0.006398417986929417, 0.0012554702116176486, 0.0074211121536791325, 0.010717593133449554, 0.049051254987716675, 0.24959337711334229, 0.006417354568839073, -0.057666826993227005, -0.0468457005918026, -0.002862254623323679, -0.00486677186563611, -0.002375381998717785, -0.01682371459901333, 0.009011342190206051, 0.12074223905801773, 0.001989581622183323, -0.009173679165542126, -0.013144731521606445, -0.015070175752043724, -0.04363885894417763, -0.0003053119871765375, -0.006338771432638168, 0.004932073410600424, -0.15332861244678497, -0.004816148895770311, -0.0023492116015404463, 0.016545282676815987, -0.001709619304165244, -0.013169904239475727, -0.11412511020898819, -0.202517569065094, 0.009383699856698513, 0.1297224462032318, 0.0056001124903559685, -0.01269744522869587, 0.0021330846939235926, -0.08546653389930725, -0.1334666609764099, -0.0027801108080893755, -0.07388244569301605, 0.00505793234333396, 0.07371390610933304, 0.03501145541667938, -0.0006730420864187181, -0.002135098446160555, 0.004249595105648041, -0.036232441663742065, 0.263942152261734, 0.0027228561230003834, -0.0020696944557130337, 0.0017612290102988482, -0.002822405658662319, 0.1190698966383934, 0.04764315485954285, 0.02588491700589657, -0.09784920513629913, -0.0023657327983528376, -0.02211504615843296, 0.004360306076705456, -0.0026493342593312263, -0.001022880314849317, 0.00408570934087038, -0.0034248982556164265, 0.003120097564533353, -0.07066097110509872, 0.003962109796702862, -0.020672880113124847, 0.002750005107372999, -0.10889820009469986, -0.0069341775961220264, 0.010038419626653194, 0.1742521971464157, 0.0003855641698464751, -0.0016570232110098004, 0.012623189948499203, 0.007401735056191683, 0.030959144234657288, -0.04500763118267059, -0.018015660345554352, -0.004637634847313166, 0.1341673582792282, -0.002675049938261509, 0.0010797850554808974, -0.004457265138626099, 0.0026313276030123234, 0.0004421667836140841, 0.02306954190135002, 0.21203938126564026, -0.0042820824310183525, 0.0033936691470444202, -0.004675364587455988, -0.006049075163900852, -0.08900583535432816, -0.002515271073207259, -0.06748009473085403, 0.02633572369813919, -0.007937341928482056, -0.0005898139788769186, -0.000987825682386756, -0.0029705087654292583, -0.0008315134327858686, -0.26069924235343933, 0.0367228239774704, 0.08291738480329514, -0.012987925671041012, -0.00524356821551919, 0.010866782627999783, -0.0017442327225580812, 0.0024614043068140745, -0.24548490345478058, -0.0642000138759613, 0.009642115794122219, 0.0014905520947650075, 0.004344462417066097, -0.001906131743453443, 0.008299516513943672, 0.05748245120048523, 0.0031748428009450436, 0.0020936853252351284, 0.0012538537848740816, 0.004880981519818306, -0.0021094498224556446, 0.0012627202086150646, -0.0025581330992281437, -0.0043145096860826015, 0.17136064171791077, -0.0027595553547143936, 0.0014381170039996505, 0.1392369121313095, 0.13462324440479279, -0.0060705929063260555, 0.023846164345741272, -0.041592974215745926, 0.0018410480115562677, 0.12148106843233109, -0.03168937936425209, -0.00026864526444114745, -0.005666567012667656, 0.0920085608959198, 0.026908613741397858, 0.0023466504644602537, 0.0051388428546488285, -0.11932720988988876, -0.19283035397529602, 0.024459129199385643, -0.06673143804073334, 0.08777308464050293, 0.01421852596104145, -0.005940374452620745, 0.007013058289885521]

I hope can you help me, thanks a lot

Suppose I have an attendance app where the user can give attendance with the face but someone can take her picture and give attendance every time, without being present there.

On Clicking sign up button, camera opens but no bounding box is shown. No face is detected.

Is it possible to upload user image from gallery then let the user auth based on this image ?