blinkid android
v6.12.0
O Blinkid Android SDK permite criar uma experiência fantástica de integração no seu aplicativo Android.
Com uma varredura rápida, seus usuários poderão extrair informações de seus cartões de identidade, passaportes, licenças de motorista e praticamente qualquer outro ID emitido pelo governo que existe.
Blinkid é:
Para ver todos esses recursos no trabalho, faça o download do nosso aplicativo de demonstração gratuito:
Sentindo -se pronto para rachar com a integração? Primeiro, certifique -se de apoiarmos o seu tipo de documento ➡️ Lista completa. E depois siga as diretrizes abaixo.
UISettings )RecognizerRunnerFragment )RecognizerRunnerViewString (análise)BlinkIdUISettings e BlinkIdOverlayControllerDocumentUISettingsLegacyDocumentVerificationUISettingsRecognizerRunner e RecognizerRunnerViewRecognizer e RecognizerBundleRecognizerRecognizerBundleRecognizer entre atividadeslibc++_shared.soYes . RecognizerRunnerFragment No seu build.gradle , adicione o repositório Blinkid Maven ao Repositórios
repositories {
maven { url 'https://maven.microblink.com' }
}
Adicione o Blinkid como uma dependência e verifique se transitive está definido como true
dependencies {
implementation('com.microblink:blinkid:6.12.0@aar') {
transitive = true
}
}
O Android Studio deve importar automaticamente o JAVADOC da dependência do Maven. Se isso não acontecer, você pode fazer isso manualmente seguindo estas etapas:
External Libraries (geralmente esta é a última entrada na visualização do projeto)blinkid-6.12.0 , clique com o botão direito do mouse e selecione Library Properties...Library Properties aparecerá+ no canto inferior esquerdo da janela (aquele que contém + com Little Globe)https://blinkid.github.io/blinkid-android/OK Uma chave de licença válida é necessária para inicializar a digitalização. Você pode solicitar uma chave de licença de teste gratuita, depois de se registrar, no MicroBlink Developer Hub. A licença deve ser o nome do pacote do seu aplicativo; portanto, digite o nome correto do pacote quando solicitado.
Faça o download do seu arquivo de licença e coloque -o na pasta de ativos do seu aplicativo. Certifique -se de definir a chave de licença antes de usar outras classes do SDK; caso contrário, você receberá uma exceção de tempo de execução.
Recomendamos que você estenda a classe de aplicativo do Android e defina a licença no retorno de chamada onCreate como este:
public class MyApplication extends Application {
@ Override
public void onCreate () {
MicroblinkSDK . setLicenseFile ( "path/to/license/file/within/assets/dir" , this );
}
} public class MyApplication : Application () {
override fun onCreate () {
MicroblinkSDK .setLicenseFile( " path/to/license/file/within/assets/dir " , this )
}
} Em sua atividade principal, defina e crie o objeto ActivityResultLauncher , substituindo o método onActivityResult . Os OneSideDocumentScan e TwoSideDocumentScan podem ser usados de forma intercambiável, sem diferença na implementação. A única diferença funcional é que OneSideDocumentScan pode examinar apenas um lado do documento e que TwoSideDocumentScan podem digitalizar mais de um lado do documento.
ActivityResultLauncher < Void > resultLauncher = registerForActivityResult (
new TwoSideDocumentScan (),
twoSideScanResult -> {
ResultStatus resultScanStatus = twoSideScanResult . getResultStatus ();
if ( resultScanStatus == ResultStatus . FINISHED ) {
// code after a successful scan
// use result.getResult() for fetching results, for example:
String firstName = twoSideScanResult . getResult (). getFirstName (). value ();
} else if ( resultScanStatus == ResultStatus . CANCELLED ) {
// code after a cancelled scan
} else if ( resultScanStatus == ResultStatus . EXCEPTION ) {
// code after a failed scan
}
}
); private val resultLauncher =
registerForActivityResult( TwoSideDocumentScan ()) { twoSideScanResult : TwoSideScanResult ->
when (twoSideScanResult.resultStatus) {
ResultStatus . FINISHED -> {
// code after a successful scan
// use twoSideScanResult.result for fetching results, for example:
val firstName = twoSideScanResult.result?.firstName?.value()
}
ResultStatus . CANCELLED -> {
// code after a cancelled scan
}
ResultStatus . EXCEPTION -> {
// code after a failed scan
}
else -> {}
}
}@Composable
fun createLauncher (): ActivityResultLauncher < Void ?> {
return rememberLauncherForActivityResult( TwoSideDocumentScan ()) { twoSideScanResult : TwoSideScanResult ->
when (twoSideScanResult.resultStatus) {
ResultStatus . FINISHED -> {
// code after a successful scan
// use twoSideScanResult.result for fetching results, for example:
val firstName = twoSideScanResult.result?.firstName?.value()
}
ResultStatus . CANCELLED -> {
// code after a cancelled scan
}
ResultStatus . EXCEPTION -> {
// code after a failed scan
}
else -> {}
}
}
} Após uma varredura, o result , que é a instância do objeto de OneSideScanResult ou TwoSideScanResult , será atualizado. Você pode definir o que acontece com os dados na substituição da função onActivityResult (o código Kotlin também substitui essa função, mas está implícito). Os resultados são acessíveis no método twoSideScanResult.getResult() ( twoSideScanResult.result em kotlin).
Inicie o processo de digitalização ligando para ActivityResultObject e chamando ActivityResultLauncher.launch :
// method within MyActivity from previous step
public void startScanning () {
// Start scanning
resultLauncher . launch ( null );
} // method within MyActivity from previous step
public fun startScanning () {
// Start scanning
resultLauncher.launch()
} // within @Composable function or setContent block
val resultLauncher = createLauncher()
resultLauncher.launch() Os resultados estarão disponíveis em um retorno de chamada, que são definidos no ActivityResultObject , que foi definido na etapa anterior.
O BlinkId requer o nível 21 ou mais recente do Android API.
A resolução de visualização em vídeo da câmera também é importante. Para realizar varreduras bem -sucedidas, a resolução de visualização da câmera deve ser de pelo menos 720p. Observe que a resolução da visualização da câmera não é a mesma que a resolução de gravação de vídeo.
O BlinkId é distribuído com binários da Biblioteca Nativa do ARMV7 e do ARM64 .
O Blinkid é uma biblioteca nativa, escrita em C ++ e disponível para várias plataformas. Por esse motivo, o Blinkid não pode funcionar em dispositivos com arquiteturas obscuras de hardware. Compilamos o código nativo Blinkid apenas para o Android Abis mais popular.
Mesmo antes de definir a chave da licença, verifique se o BlinkId é suportado no dispositivo atual (consulte a próxima seção: Verificação de compatibilidade ). Tentar chamar qualquer método do SDK que depende do código nativo, como a verificação da licença, em um dispositivo com a arquitetura da CPU não suportada travará seu aplicativo.
Se você estiver combinando biblioteca Blinkid com outras bibliotecas que contêm código nativo em seu aplicativo, corresponda às arquiteturas de todas as bibliotecas nativas.
Para obter mais informações, consulte a seção Considerações de Arquitetura do Processador.
Veja como você pode verificar se o BlinkId é suportado no dispositivo:
// check if BlinkID is supported on the device,
RecognizerCompatibilityStatus status = RecognizerCompatibility . getRecognizerCompatibilityStatus ( this );
if ( status == RecognizerCompatibilityStatus . RECOGNIZER_SUPPORTED ) {
Toast . makeText ( this , "BlinkID is supported!" , Toast . LENGTH_LONG ). show ();
} else if ( status == RecognizerCompatibilityStatus . NO_CAMERA ) {
Toast . makeText ( this , "BlinkID is supported only via Direct API!" , Toast . LENGTH_LONG ). show ();
} else if ( status == RecognizerCompatibilityStatus . PROCESSOR_ARCHITECTURE_NOT_SUPPORTED ) {
Toast . makeText ( this , "BlinkID is not supported on current processor architecture!" , Toast . LENGTH_LONG ). show ();
} else {
Toast . makeText ( this , "BlinkID is not supported! Reason: " + status . name (), Toast . LENGTH_LONG ). show ();
} // check if _BlinkID_ is supported on the device,
when ( val status = RecognizerCompatibility .getRecognizerCompatibilityStatus( this )) {
RecognizerCompatibilityStatus . RECOGNIZER_SUPPORTED -> {
Toast .makeText( this , " BlinkID is supported! " , Toast . LENGTH_LONG ).show()
}
RecognizerCompatibilityStatus . NO_CAMERA -> {
Toast .makeText( this , " BlinkID is supported only via Direct API! " , Toast . LENGTH_LONG ).show()
}
RecognizerCompatibilityStatus . PROCESSOR_ARCHITECTURE_NOT_SUPPORTED -> {
Toast .makeText( this , " BlinkID is not supported on current processor architecture! " , Toast . LENGTH_LONG ).show()
}
else -> {
Toast .makeText( this , " BlinkID is not supported! Reason: " + status.name, Toast . LENGTH_LONG ).show()
}
}Alguns reconhecidos exigem câmera com foco automático. Se você tentar usá -los em um dispositivo que não suporta foco automático, você receberá um erro. Para evitar isso, você pode verificar se um reconhecedor requer foco automático chamando seu método requersaUToToFocus.
Se você já possui uma variedade de reconhecedores, pode filtrar facilmente os reconhecedores que exigem foco automático da matriz usando o seguinte snippet de código:
Recognizer [] recArray = ...;
if (! RecognizerCompatibility . cameraHasAutofocus ( CameraType . CAMERA_BACKFACE , this )) {
recArray = RecognizerUtils . filterOutRecognizersThatRequireAutofocus ( recArray );
} var recArray : Array < Recognizer > = .. .
if ( ! RecognizerCompatibility .cameraHasAutofocus( CameraType . CAMERA_BACKFACE , this )) {
recArray = RecognizerUtils .filterOutRecognizersThatRequireAutofocus(recArray)
}Você pode integrar o BlinkID ao seu aplicativo de cinco maneiras diferentes, dependendo do seu caso de uso e das necessidades de personalização:
OneSideDocumentScan pode e TwoSideDocumentScan ) - SDK lida com tudo e você só precisa iniciar nossa atividade interna e lidar com o resultado, sem opções de personalizaçãoUISettings )-O SDK lida com a maior parte do trabalho, você só precisa definir um reconhecimento, configurações, iniciar nossa atividade interna e resultado, as opções de personalização são limitadasRecognizerRunnerFragment )-Reutilização de reutilização UX de nossas atividades internas em sua própria atividadeRecognizerRunnerView ) - O SDK lida com o gerenciamento da câmera enquanto você precisa implementar a digitalização completamente personalizada UXRecognizerRunner ) - SKD apenas lida com o reconhecimento enquanto você precisa fornecer as imagens, da câmera ou de um arquivo OneSideDocumentScan Gan e TwoSideDocumentScan ) OneSideDocumentScan e TwoSideDocumentScan são classes que contêm todas as definições de configuração necessárias para iniciar rapidamente as atividades de digitalização interna do SDK. Ele permite que o usuário pule todas as etapas de configuração, como UISettings e RecognizerBundle e vá diretamente para a digitalização.
Como mostrado na execução da sua primeira varredura, é necessário apenas a definição de um ouvinte de resultado, para definir o que vai acontecer com os resultados da verificação e chamando a função de varredura real.
UISettings ) UISettings é uma classe que contém todas as configurações necessárias para as atividades de digitalização interna do SDK. Ele configura o comportamento da atividade de varredura, cordas, ícones e outros elementos da interface do usuário. Você deve usar ActivityRunner para iniciar a atividade de varredura configurada pelas UISettings , mostrada no exemplo abaixo.
Fornecemos várias aulas UISettings especializadas para diferentes cenários de varredura. Cada objeto UISettings possui propriedades que podem ser alteradas por meio de métodos de setter apropriados. Por exemplo, você pode personalizar as configurações da câmera com o Metod setCameraSettings .
Todas as aulas UISettings disponíveis estão listadas aqui.
Na sua atividade principal, crie objetos de reconhecimento que executem reconhecimento de imagem, os configurem e os colocarão no objeto ReconhecerBundle. Você pode ver mais informações sobre os reconhecedores disponíveis e RecognizerBundle aqui.
Por exemplo, para digitalizar o documento suportado, configure seu reconhecedor como este:
public class MyActivity extends Activity {
private BlinkIdMultiSideRecognizer mRecognizer ;
private RecognizerBundle mRecognizerBundle ;
@ Override
protected void onCreate ( Bundle bundle ) {
super . onCreate ( bundle );
// setup views, as you would normally do in onCreate callback
// create BlinkIdMultiSideRecognizer
mRecognizer = new BlinkIdMultiSideRecognizer ();
// bundle recognizers into RecognizerBundle
mRecognizerBundle = new RecognizerBundle ( mRecognizer );
}
} public class MyActivity : Activity () {
private lateinit var mRecognizer : BlinkIdMultiSideRecognizer
private lateinit var mRecognizerBundle : RecognizerBundle
override fun onCreate ( bundle : Bundle ) {
// setup views, as you would normally do in onCreate callback
// create BlinkIdMultiSideRecognizer
mRecognizer = BlinkIdMultiSideRecognizer ()
// build recognizers into RecognizerBundle
mRecognizerBundle = RecognizerBundle (mRecognizer)
}
} Inicie o processo de reconhecimento, criando BlinkIdUISettings e chamando ActivityRunner.startActivityForResult :
// method within MyActivity from previous step
public void startScanning () {
// Settings for BlinkIdActivity
BlinkIdUISettings settings = new BlinkIdUISettings ( mRecognizerBundle );
// tweak settings as you wish
// Start activity
ActivityRunner . startActivityForResult ( this , MY_REQUEST_CODE , settings );
} // method within MyActivity from previous step
public fun startScanning () {
// Settings for BlinkIdActivity
val settings = BlinkIdUISettings (mRecognizerBundle)
// tweak settings as you wish
// Start activity
ActivityRunner .startActivityForResult( this , MY_REQUEST_CODE , settings)
} onActivityResult será chamado em sua atividade após o término da digitalização, aqui você pode obter os resultados da digitalização.
@ Override
protected void onActivityResult ( int requestCode , int resultCode , Intent data ) {
super . onActivityResult ( requestCode , resultCode , data );
if ( requestCode == MY_REQUEST_CODE ) {
if ( resultCode == Activity . RESULT_OK && data != null ) {
// load the data into all recognizers bundled within your RecognizerBundle
mRecognizerBundle . loadFromIntent ( data );
// now every recognizer object that was bundled within RecognizerBundle
// has been updated with results obtained during scanning session
// you can get the result by invoking getResult on recognizer
BlinkIdMultiSideRecognizer . Result result = mRecognizer . getResult ();
if ( result . getResultState () == Recognizer . Result . State . Valid ) {
// result is valid, you can use it however you wish
}
}
}
} override protected fun onActivityResult ( requestCode : Int , resultCode : Int , data : Intent ) {
super .onActivityResult(requestCode, resultCode, data);
if (requestCode == MY_REQUEST_CODE ) {
if (resultCode == Activity . RESULT_OK && data != null ) {
// load the data into all recognizers bundled within your RecognizerBundle
mRecognizerBundle.loadFromIntent(data)
// now every recognizer object that was bundled within RecognizerBundle
// has been updated with results obtained during scanning session
// you can get the result by invoking getResult on recognizer
val result = mRecognizer.result
if (result.resultState == Recognizer . Result . State . Valid ) {
// result is valid, you can use it however you wish
}
}
}
} Para obter mais informações sobre os reconhecedores e RecognizerBundle disponíveis, consulte ReconhecerBundle e reconhecedores disponíveis.
RecognizerRunnerFragment ) Se você deseja reutilizar nossa atividade embutida UX dentro de sua própria atividade, use RecognizerRunnerFragment . A atividade que hospedará RecognizerRunnerFragment deve implementar a interface ScanningOverlayBinder . Tentar adicionar RecognizerRunnerFragment à atividade que não implementa essa interface resultará em ClassCastException .
O ScanningOverlayBinder é responsável por retornar a implementação non-null da classe ScanningOverlay - que gerenciará a interface do usuário em cima do RecognizerRunnerFragment . Não é recomendável criar sua própria implementação ScanningOverlay , use uma de nossas implementações listadas aqui.
Aqui está o exemplo mínimo de atividade que hospeda o reconhecimento do RecognizerRunnerFragment :
public class MyActivity extends AppCompatActivity implements RecognizerRunnerFragment . ScanningOverlayBinder {
private BlinkIdMultiSideRecognizer mRecognizer ;
private RecognizerBundle mRecognizerBundle ;
private BlinkIdOverlayController mScanOverlay ;
private RecognizerRunnerFragment mRecognizerRunnerFragment ;
@ Override
protected void onCreate ( Bundle savedInstanceState ) {
super . onCreate ();
setContentView ( R . layout . activity_my_activity );
mScanOverlay = createOverlay ();
if ( null == savedInstanceState ) {
// create fragment transaction to replace R.id.recognizer_runner_view_container with RecognizerRunnerFragment
mRecognizerRunnerFragment = new RecognizerRunnerFragment ();
FragmentTransaction fragmentTransaction = getSupportFragmentManager (). beginTransaction ();
fragmentTransaction . replace ( R . id . recognizer_runner_view_container , mRecognizerRunnerFragment );
fragmentTransaction . commit ();
} else {
// obtain reference to fragment restored by Android within super.onCreate() call
mRecognizerRunnerFragment = ( RecognizerRunnerFragment ) getSupportFragmentManager (). findFragmentById ( R . id . recognizer_runner_view_container );
}
}
@ Override
@ NonNull
public ScanningOverlay getScanningOverlay () {
return mScanOverlay ;
}
private BlinkIdOverlayController createOverlay () {
// create BlinkIdMultiSideRecognizer
mRecognizer = new BlinkIdMultiSideRecognizer ();
// bundle recognizers into RecognizerBundle
mRecognizerBundle = new RecognizerBundle ( mRecognizer );
BlinkIdUISettings settings = new BlinkIdUISettings ( mRecognizerBundle );
return settings . createOverlayController ( this , mScanResultListener );
}
private final ScanResultListener mScanResultListener = new ScanResultListener () {
@ Override
public void onScanningDone ( @ NonNull RecognitionSuccessType recognitionSuccessType ) {
// pause scanning to prevent new results while fragment is being removed
mRecognizerRunnerFragment . getRecognizerRunnerView (). pauseScanning ();
// now you can remove the RecognizerRunnerFragment with new fragment transaction
// and use result within mRecognizer safely without the need for making a copy of it
// if not paused, as soon as this method ends, RecognizerRunnerFragments continues
// scanning. Note that this can happen even if you created fragment transaction for
// removal of RecognizerRunnerFragment - in the time between end of this method
// and beginning of execution of the transaction. So to ensure result within mRecognizer
// does not get mutated, ensure calling pauseScanning() as shown above.
}
@ Override
public void onUnrecoverableError ( @ NonNull Throwable throwable ) {
}
};
} package com.microblink.blinkid
class MainActivity : AppCompatActivity (), RecognizerRunnerFragment.ScanningOverlayBinder {
private lateinit var mRecognizer : BlinkIdMultiSideRecognizer
private lateinit var mRecognizerRunnerFragment : RecognizerRunnerFragment
private lateinit var mRecognizerBundle : RecognizerBundle
private lateinit var mScanOverlay : BlinkIdOverlayController
override fun onCreate ( savedInstanceState : Bundle ? ) {
super .onCreate(savedInstanceState)
if ( ! ::mScanOverlay.isInitialized) {
mScanOverlay = createOverlayController()
}
setContent {
this . run {
// viewBinding has to be set to 'true' in buildFeatures block of the build.gradle file
AndroidViewBinding ( RecognizerRunnerLayoutBinding ::inflate) {
mRecognizerRunnerFragment =
fragmentContainerView.getFragment< RecognizerRunnerFragment >()
}
}
}
}
override fun getScanningOverlay (): ScanningOverlay {
return mScanOverlay
}
private fun createOverlay (): BlinkIdOverlayController {
// create BlinkIdMultiSideRecognizer
val mRecognizer = BlinkIdMultiSideRecognizer ()
// bundle recognizers into RecognizerBundle
mRecognizerBundle = RecognizerBundle (mRecognizer)
val settings = BlinkIdUISettings (mRecognizerBundle)
return settings.createOverlayController( this , mScanResultListener)
}
private val mScanResultListener : ScanResultListener = object : ScanResultListener {
override fun onScanningDone ( p0 : RecognitionSuccessType ) {
// pause scanning to prevent new results while fragment is being removed
mRecognizerRunnerFragment !! .recognizerRunnerView !! .pauseScanning()
// now you can remove the RecognizerRunnerFragment with new fragment transaction
// and use result within mRecognizer safely without the need for making a copy of it
// if not paused, as soon as this method ends, RecognizerRunnerFragments continues
// scanning. Note that this can happen even if you created fragment transaction for
// removal of RecognizerRunnerFragment - in the time between end of this method
// and beginning of execution of the transaction. So to ensure result within mRecognizer
// does not get mutated, ensure calling pauseScanning() as shown above.
}
override fun onUnrecoverableError ( p0 : Throwable ) {
}
}
} Consulte os aplicativos de exemplo fornecidos com o SDK para obter um exemplo mais detalhado e verifique se a orientação da sua atividade do host está definida como nosensor ou possui alteração de configuração ativada (ou seja, não é reiniciado quando a mudança de configuração acontecer). Para mais informações, verifique a seção de orientação da verificação.
RecognizerRunnerViewEsta seção discute como incorporar o reconhecimento ReconhecerunnerView em sua atividade de digitalização e executar a digitalização.
RecognizerRunnerView seja um campo membro em sua atividade. Isso é necessário, porque você precisará passar por todos os eventos do ciclo de vida da atividade para RecognizerRunnerView .portrait ou landscape . A configuração sensor como a orientação da atividade de varredura acionará a reinicialização completa da atividade sempre que a orientação do dispositivo mudar. Isso proporcionará uma experiência muito ruim do usuário, porque a câmera e a biblioteca nativa Blinkid precisarão ser reiniciadas todas as vezes. Existem medidas contra esse comportamento que são discutidas mais adiante.onCreate da sua atividade, crie um novo RecognizerRunnerView , defina o reconhecimento do reconhecimento que contém reconhecedores que serão usados pela visualização, defina o CameraventsListener que lidará com eventos obrigatórios da câmera, defina o scanResultListener que receberá chamada quando o reconhecimento tiver sido concluído e depois chamará seu método create . Depois disso, adicione suas visualizações que devem ser encerradas sobre a visualização da câmera.setLifecycle para permitir o manuseio automático de eventos de vida. Aqui está o exemplo mínimo de integração do RecognizerRunnerView como a única visão em sua atividade:
public class MyScanActivity extends AppCompatActivity {
private static final int PERMISSION_CAMERA_REQUEST_CODE = 42 ;
private RecognizerRunnerView mRecognizerRunnerView ;
private BlinkIdMultiSideRecognizer mRecognizer ;
private RecognizerBundle mRecognizerBundle ;
@ Override
protected void onCreate ( Bundle savedInstanceState ) {
super . onCreate ( savedInstanceState );
// create BlinkIdMultiSideRecognizer
mRecognizer = new BlinkIdMultiSideRecognizer ();
// bundle recognizers into RecognizerBundle
mRecognizerBundle = new RecognizerBundle ( mRecognizer );
// create RecognizerRunnerView
mRecognizerRunnerView = new RecognizerRunnerView ( this );
// set lifecycle to automatically call recognizer runner view lifecycle methods
mRecognizerRunnerView . setLifecycle ( getLifecycle ());
// associate RecognizerBundle with RecognizerRunnerView
mRecognizerRunnerView . setRecognizerBundle ( mRecognizerBundle );
// scan result listener will be notified when scanning is complete
mRecognizerRunnerView . setScanResultListener ( mScanResultListener );
// camera events listener will be notified about camera lifecycle and errors
mRecognizerRunnerView . setCameraEventsListener ( mCameraEventsListener );
setContentView ( mRecognizerRunnerView );
}
@ Override
public void onConfigurationChanged ( Configuration newConfig ) {
super . onConfigurationChanged ( newConfig );
// changeConfiguration is not handled by lifecycle events so call it manually
mRecognizerRunnerView . changeConfiguration ( newConfig );
}
private final CameraEventsListener mCameraEventsListener = new CameraEventsListener () {
@ Override
public void onCameraPreviewStarted () {
// this method is from CameraEventsListener and will be called when camera preview starts
}
@ Override
public void onCameraPreviewStopped () {
// this method is from CameraEventsListener and will be called when camera preview stops
}
@ Override
public void onError ( Throwable exc ) {
/**
* This method is from CameraEventsListener and will be called when
* opening of camera resulted in exception or recognition process
* encountered an error. The error details will be given in exc
* parameter.
*/
}
@ Override
@ TargetApi ( 23 )
public void onCameraPermissionDenied () {
/**
* Called in Android 6.0 and newer if camera permission is not given
* by user. You should request permission from user to access camera.
*/
requestPermissions ( new String []{ Manifest . permission . CAMERA }, PERMISSION_CAMERA_REQUEST_CODE );
/**
* Please note that user might have not given permission to use
* camera. In that case, you have to explain to user that without
* camera permissions scanning will not work.
* For more information about requesting permissions at runtime, check
* this article:
* https://developer.android.com/training/permissions/requesting.html
*/
}
@ Override
public void onAutofocusFailed () {
/**
* This method is from CameraEventsListener will be called when camera focusing has failed.
* Camera manager usually tries different focusing strategies and this method is called when all
* those strategies fail to indicate that either object on which camera is being focused is too
* close or ambient light conditions are poor.
*/
}
@ Override
public void onAutofocusStarted ( Rect [] areas ) {
/**
* This method is from CameraEventsListener and will be called when camera focusing has started.
* You can utilize this method to draw focusing animation on UI.
* Areas parameter is array of rectangles where focus is being measured.
* It can be null on devices that do not support fine-grained camera control.
*/
}
@ Override
public void onAutofocusStopped ( Rect [] areas ) {
/**
* This method is from CameraEventsListener and will be called when camera focusing has stopped.
* You can utilize this method to remove focusing animation on UI.
* Areas parameter is array of rectangles where focus is being measured.
* It can be null on devices that do not support fine-grained camera control.
*/
}
};
private final ScanResultListener mScanResultListener = new ScanResultListener () {
@ Override
public void onScanningDone ( @ NonNull RecognitionSuccessType recognitionSuccessType ) {
// this method is from ScanResultListener and will be called when scanning completes
// you can obtain scanning result by calling getResult on each
// recognizer that you bundled into RecognizerBundle.
// for example:
BlinkIdMultiSideRecognizer . Result result = mRecognizer . getResult ();
if ( result . getResultState () == Recognizer . Result . State . Valid ) {
// result is valid, you can use it however you wish
}
// Note that mRecognizer is stateful object and that as soon as
// scanning either resumes or its state is reset
// the result object within mRecognizer will be changed. If you
// need to create a immutable copy of the result, you can do that
// by calling clone() on it, for example:
BlinkIdMultiSideRecognizer . Result immutableCopy = result . clone ();
// After this method ends, scanning will be resumed and recognition
// state will be retained. If you want to prevent that, then
// you should call:
mRecognizerRunnerView . resetRecognitionState ();
// Note that reseting recognition state will clear internal result
// objects of all recognizers that are bundled in RecognizerBundle
// associated with RecognizerRunnerView.
// If you want to pause scanning to prevent receiving recognition
// results or mutating result, you should call:
mRecognizerRunnerView . pauseScanning ();
// if scanning is paused at the end of this method, it is guaranteed
// that result within mRecognizer will not be mutated, therefore you
// can avoid creating a copy as described above
// After scanning is paused, you will have to resume it with:
mRecognizerRunnerView . resumeScanning ( true );
// boolean in resumeScanning method indicates whether recognition
// state should be automatically reset when resuming scanning - this
// includes clearing result of mRecognizer
}
};
} Se a propriedade screenOrientation da Atividade no AndroidManifest.xml estiver definida como sensor , fullSensor ou similar, a atividade será reiniciada sempre que o dispositivo mudar de orientação do retrato para a paisagem e vice -versa. Ao reiniciar a atividade, a sua onPause , os métodos onStop e onDestroy serão chamados e, em seguida, novas atividades serão criadas novamente. Esse é um problema em potencial para a atividade de varredura, porque em seu ciclo de vida controla a câmera e a biblioteca nativa - reiniciar a atividade acionará a reinicialização da câmera e da biblioteca nativa. Isso é um problema, porque a mudança de orientação da paisagem para retrato e vice -versa será muito lenta, degradando assim uma experiência do usuário. Não recomendamos essa configuração.
Nesse sentido, recomendamos definir sua atividade de varredura como o modo portrait ou landscape e lidar com as mudanças de orientação do dispositivo manualmente. Para ajudá -lo com isso, RecognizerRunnerView suporta a adição de visualizações da criança, que serão giradas, independentemente da screenOrientation da atividade. Você adiciona uma visualização que deseja ser girada (como visualização que contém botões, mensagens de status etc.) para RecognizerRunnerView o Método AddChildView. O segundo parâmetro do método é um booleano que define se a visualização que você está adicionando será girada com o dispositivo. Para definir orientações permitidas, implemente a interface OrientationAllowEdListener e adicione -a ao RecognizerRunnerView com o Method setOrientationAllowedListener . Esta é a maneira recomendada de girar a sobreposição da câmera.
No entanto, se você realmente deseja definir a propriedade screenOrientation como sensor ou similar e deseja que o Android lide com alterações de orientação da sua atividade de varredura, recomendamos definir a propriedade configChanges de sua atividade como orientation|screenSize Isso dirá ao Android para não reiniciar sua atividade quando a orientação do dispositivo mudar. Em vez disso, o método onConfigurationChanged da Atividade será chamado para que a atividade possa ser notificada sobre a alteração da configuração. Na sua implementação deste método, você deve chamar o método do RecognizerView do changeConfiguration para que ele possa adaptar a superfície da câmera e as visualizações da criança a uma nova configuração.
Esta seção descreverá como usar a API direta para reconhecer o Android Bitmaps sem a necessidade de câmera. Você pode usar a API direta em qualquer lugar do seu aplicativo, não apenas das atividades.
O desempenho do reconhecimento de imagem depende muito da qualidade das imagens de entrada. Quando o gerenciamento da câmera é usado (digitalização de uma câmera), fazemos o possível para obter quadros de câmera com a melhor qualidade possível para o dispositivo usado. Por outro lado, quando a API direta é usada, você precisa fornecer imagens de alta qualidade sem borrão e brilho para o reconhecimento bem-sucedido.
Bitmaps obtido, por exemplo, da galeria. Use reconhecerbitmap ou reconhecerbitmapwithrecognizers.Images de vídeo que são construídas a partir de quadros de vídeo de câmera personalizados, por exemplo, quando você usa seu próprio gerenciamento de câmera ou terceiros. O reconhecimento será otimizado para velocidade e dependerá da redundância de tempo entre quadros de vídeo consecutivos, a fim de produzir o melhor resultado de reconhecimento possível. Use reconhecervideoimage ou reconhecervideoimagewithrecognizers.Images estáticas quando você precisa de digitalização completa de imagens únicas ou poucas que não fazem parte do fluxo de vídeo e você deseja obter os melhores resultados possíveis da InputImage única. O tipo de inputimage vem do nosso SDK ou pode ser criado usando o ImageBuilder. Use ReconhecestillImage ou ReconhecestillImageWithReconhores.Aqui está o exemplo mínimo de uso da API direta para reconhecer o Android Bitmap:
public class DirectAPIActivity extends Activity {
private RecognizerRunner mRecognizerRunner ;
private BlinkIdMultiSideRecognizer mRecognizer ;
private RecognizerBundle mRecognizerBundle ;
@ Override
protected void onCreate ( Bundle savedInstanceState ) {
super . onCreate ();
// initialize your activity here
// create BlinkIdMultiSideRecognizer
mRecognizer = new BlinkIdMultiSideRecognizer ();
// bundle recognizers into RecognizerBundle
mRecognizerBundle = new RecognizerBundle ( mRecognizer );
try {
mRecognizerRunner = RecognizerRunner . getSingletonInstance ();
} catch ( FeatureNotSupportedException e ) {
Toast . makeText ( this , "Feature not supported! Reason: " + e . getReason (). getDescription (), Toast . LENGTH_LONG ). show ();
finish ();
return ;
}
mRecognizerRunner . initialize ( this , mRecognizerBundle , new DirectApiErrorListener () {
@ Override
public void onRecognizerError ( Throwable t ) {
Toast . makeText ( DirectAPIActivity . this , "There was an error in initialization of Recognizer: " + t . getMessage (), Toast . LENGTH_SHORT ). show ();
finish ();
}
});
}
@ Override
protected void onResume () {
super . onResume ();
// start recognition
Bitmap bitmap = BitmapFactory . decodeFile ( "/path/to/some/file.jpg" );
mRecognizerRunner . recognizeBitmap ( bitmap , Orientation . ORIENTATION_LANDSCAPE_RIGHT , mScanResultListener );
}
@ Override
protected void onDestroy () {
super . onDestroy ();
mRecognizerRunner . terminate ();
}
private final ScanResultListener mScanResultListener = new ScanResultListener () {
@ Override
public void onScanningDone ( @ NonNull RecognitionSuccessType recognitionSuccessType ) {
// this method is from ScanResultListener and will be called
// when scanning completes
// you can obtain scanning result by calling getResult on each
// recognizer that you bundled into RecognizerBundle.
// for example:
BlinkIdMultiSideRecognizer . Result result = mRecognizer . getResult ();
if ( result . getResultState () == Recognizer . Result . State . Valid ) {
// result is valid, you can use it however you wish
}
}
};
} O método ScanResultListener.OnscanningDone é chamado para cada imagem de entrada que você envia para o reconhecimento. Você pode chamar o Método RecognizerRunner.recognize* várias vezes com imagens diferentes do mesmo documento para melhor precisão de leitura até obter um resultado bem -sucedido no método onScanningDone do ouvinte. Isso é útil quando você está usando o seu próprio gerenciamento de câmera ou de terceiros.
String (análise) Alguns reconhecedores apóiam o reconhecimento da String . Eles podem ser usados através da API direta para analisar String dada e retornar dados, como quando são usados em uma imagem de entrada. Quando o reconhecimento é realizado na String , não há necessidade do OCR. String de entrada é usada da mesma maneira que a saída OCR é usada quando a imagem está sendo reconhecida.
O reconhecimento da String pode ser realizado da mesma maneira que o reconhecimento da imagem, descrito na seção anterior.
A única diferença é que um dos métodos de reconhecimento de Singleton Reconhecerunner para reconhecimento de String deve ser chamado:
RecognizerRunner da Direct API Singleton é uma máquina de estado que pode estar em um dos 3 estados: OFFLINE , READY e WORKING .
RecognizerRunner Singleton, ele estará no estado OFFLINE .RecognizerRunner chamando o método Initialize. Se você chamar o método initialize enquanto RecognizerRunner não estiver no estado OFFLINE , você receberá IllegalStateException .RecognizerRunner se mudará para o estado READY . Agora você pode chamar qualquer um dos métodos recognize* .recognize* , RecognizerRunner passará para o estado WORKING . Se você tentar chamar esses métodos enquanto RecognizerRunner não estiver em estado READY , você receberá IllegalStateExceptionRecognizerRunner's do thread da interface do usuárioRecognizerRunner primeiro se move de volta ao estado READY e depois chama o método OnScanningDone do ScanResultListener fornecido.onScanningDone do ScanResultListener será chamado no encadeamento de processamento de fundo, portanto, não execute operações de interface do usuário nesse retorno de chamada. Observe também que, até que o método onScanningDone seja concluído, RecognizerRunner não executará o reconhecimento de outra imagem ou string, mesmo que algum dos métodos recognize* tenha sido chamado logo após a transição para o estado READY . Isso é para garantir que os resultados dos reconhecedores empacotados no RecognizerBundle associados ao RecognizerRunner não sejam modificados enquanto possivelmente são usados no método onScanningDone .terminate , RecognizerRunner Singleton lançará todos os seus recursos internos. Observe que, mesmo após o terminate você pode receber o evento onScanningDone se houvesse trabalho em andamento quando terminate foi chamado.terminate pode ser chamado de qualquer estado de RecognizerRunner SingletonRecognizerRunner do Singleton com o método getCurrentState Tanto o Reconhecerunnerview quanto RecognizerRunner usam o mesmo singleton interno que gerencia o código nativo. Esse singleton lida com a inicialização e o término da biblioteca nativa e a propagação dos reconhecidos à biblioteca nativa. É possível usar RecognizerRunnerView e RecognizerRunner , pois o singleton interno garantirá que a sincronização correta e as configurações de reconhecimento corretas sejam usadas. Se você tiver problemas ao usar RecognizerRunner em combinação com RecognizerRunnerView , informe -nos!
Quando você está usando o reconhecedor combinado e as imagens de ambos os lados do documento são necessários, é necessário chamar RecognizerRunner.recognize* várias vezes. Chame -o primeiro com as imagens do primeiro lado do documento, até que seja lido e depois com as imagens do segundo lado. O reconhecedor combinado muda automaticamente para a digitalização lateral da segunda, depois de ler com sucesso o primeiro lado. Para ser notificado quando a primeira varredura lateral é concluída, você deve definir o FirstSideCognitionCallback através do Metadatacallbacks. Se você não precisar dessas informações, por exemplo, quando tiver apenas uma imagem para cada lado do documento, não defina o FirstSideRecognitionCallback e verifique o reconhecimento, após o scanResultListener.OnscanningDone, após a segunda imagem lateral ter sido processada.
BlinkIdUISettings e BlinkIdOverlayController BlinkIdOverlayController implementa a nova interface do usuário para a digitalização de documentos de identidade, que foi projetada de maneira ideal para ser usada com o novo BlinkIdMultiSideRecognizer e BlinkIdSingleSideRecognizer . Ele implementa vários novos recursos:
A nova interface do usuário permite que o usuário digitalize o documento em qualquer ângulo, em qualquer orientação. Recomendamos forçar a orientação da paisagem se você digitalizar códigos de barras na parte traseira, porque nessa taxa de sucesso será maior.
Para iniciar uma atividade interna que usa BlinkIdOverlayController use BlinkIdUISettings .
Para personalizar a sobreposição, forneça seu recurso de estilo personalizado via BlinkIdUISettings.setOverlayViewStyle() ou via ReticleOverlayView Constructor. Você pode personalizar elementos rotulados nas capturas de tela acima, fornecendo os seguintes atributos em seu estilo:
saída
mb_exitScanDrawable - ícone desenhadoBlinkIdUISettings.setShowCancelButton(false)tocha
mb_torchOnDrawable - ICON Drawable que é mostrado quando a tocha é ativadamb_torchOffDrawable - ICON Drawable que é mostrado quando a tocha é desativadaBlinkIdUISettings.setShowTorchButton(false)instruções
mb_instructionsTextAppearance - estilo que será usado como android:textAppearancemb_instructionsBackgroundDrawable - desenhado usado para fundomb_instructionsBackgroundColor - cor usada para fundoAviso de lanterna
mb_flashlightWarningTextAppearance - Estilo que será usado como android:textAppearancemb_flashlightWarningBackgroundDrawable - desenhado usado para fundoBlinkIdUISettings.setShowFlashlightWarning(false)ícone do cartão
mb_cardFrontDrawable - ICON Drawable mostrado durante a animação de flip de cartão, representando a frente do cartãomb_cardBackDrawable - ICON Drawable mostrado durante a animação do Card Flip, representando o lado de trás do cartãoretículo
mb_reticleDefaultDrawable - traçado mostrado quando o retículo está em estado neutromb_reticleSuccessDrawable - traçado mostrado quando o retículo está no estado de sucesso (a varredura foi bem -sucedida)mb_reticleErrorDrawable - Drawable mostrado quando o retículo está em estado de erromb_reticleColor - cor usada para o elemento de retículo rotativomb_reticleDefaultColor - cor usada para retículo em estado neutromb_reticleErrorColor - cor usada para retículo no estado de erromb_successFlashColor - cor usada para efeito flash na varredura bem -sucedida Para personalizar a visibilidade e o estilo desses dois diálogos, use métodos fornecidos no BlinkIdUISettings .
O método para controlar a visibilidade da caixa de diálogo Introdução é BlinkIdUISettings.setShowIntroductionDialog(boolean showIntroductionDialog) e é definido como true por padrão, o que significa que a caixa de diálogo Introdução será mostrada.
O método para controlar a visibilidade da caixa de diálogo de integração é BlinkIdUISettings.setShowOnboardingInfo(boolean showOnboardingInfo) e está definido como true por padrão, o que significa que a caixa de diálogo Introdução será mostrada.
Há também um método para controlar o atraso do "Mostrar ajuda?" dica de ferramenta mostrada acima do botão Ajuda. O botão em si será mostrado se o método anterior para mostrar a integração for verdadeiro. O método para definir o comprimento de atraso da dica de ferramenta é BlinkIdUISettings.setShowTooltipTimeIntervalMs(long showTooltipTimeIntervalMs) . O parâmetro de tempo é definido em milissegundos.
A configuração padrão do atraso é de 12 segundos (12000 milissegundos).
A personalização e o tema desses elementos de introdução e integração podem ser feitos da mesma maneira que explicados no capítulo anterior, fornecendo os seguintes atributos:
botão de ajuda
mb_helpButtonDrawable - desenhado que é mostrado quando o botão de ajuda é ativadomb_helpButtonBackgroundColor - cor usada para ajudar o fundo do botão de ajudamb_helpButtonQuestionmarkColor - Cor usada para o botão de ajuda em primeiro planoAjuda a dica de ferramenta
mb_helpTooltipBackground - desenhado que é mostrado como um fundo quando a dica de ferramenta de ajuda aparecemb_helpTooltipColor - cor usada para fundo de ajudamb_helpTooltipTextAppearance - Estilo que será usado como android:textAppearanceIntrodução Diálogo
mb_introductionBackgroundColor - cor usada para fundo de introdução na telamb_introductionTitleTextAppearance - estilo que será usado como android:textAppearancemb_introductionMessageTextAppearance - estilo que será usado como android:textAppearancemb_introductionButtonTextAppearance - estilo que será usado como android:textAppearanceBlinkIdUISettings.setShowIntroductionDialog(false)diálogo a integração
mb_onboardingBackgroundColor - cor usada para telas de integração em fundomb_onboardingPageIndicatorColor - cor usada para indicadores de página circular nas telas de integraçãomb_onboardingTitleTextAppearance - estilo que será usado como android:textAppearancemb_onboardingMessageTextAppearance - estilo que será usado como android:textAppearancemb_onboardingButtonTextAppearance - estilo que será usado como android:textAppearanceBlinkIdUISettings.setShowOnboardingInfo(false) Os diálogos de alerta chamados pelo SDK têm seu próprio conjunto de propriedades que podem ser modificadas no styles.xml .
MB_alert_dialog é um tema que estende o tema Theme.AppCompat.Light.Dialog.Alert e usa as cores padrão do tema do aplicativo. Para alterar os atributos nesses diálogos de alerta sem alterar outros atributos no aplicativo do usuário, o tema MB_alert_dialog precisa ser substituído.
< style name = " MB_alert_dialog " parent = " Theme.AppCompat.Light.Dialog.Alert " >
< item name = " android:textSize " >TEXT_SIZE</ item >
< item name = " android:background " >COLOR</ item >
< item name = " android:textColorPrimary " >COLOR</ item >
< item name = " colorAccent " >COLOR</ item >
</ style >Os atributos que não são substituídos usarão as cores e tamanhos padrão do tema do aplicativo.
colorAccent Atttribute é usado para alterar a cor do botão de diálogo de alerta. Se o atributo colorAccent do tema do aplicativo for alterado em outro lugar, essa cor de diálogo alerta também será alterada. No entanto, substituindo o tema MB_alert_dialog e esse atributo nele garantirá que apenas a cor do botão na caixa de diálogo Alerta do MicroBlink SDK seja alterada. Se o tema do aplicativo estender um tema do conjunto MaterialComponents (por exemplo, Theme.MaterialComponents.Light.NoActionBar ), a cor do botão acima mencionada só poderá ser alterada pelo atributo colorOnPrimary substituído em vez do atributo colorAccent .
DocumentUISettings DocumentUISettings lança atividade que usa BlinkIdOverlayController com interface do usuário alternativa. É mais adequado para digitalizar o lado de um único documento de vários documentos do cartão e não deve ser usado com reconhecidos combinados, pois não fornece instruções do usuário sobre quando mudar para o verso.
LegacyDocumentVerificationUISettings LegacyDocumentVerificationUISettings lança atividade que usa BlinkIdOverlayController com a interface do usuário alternativa. É mais adequado para reconhecedores combinados porque gerencia a digitalização de vários lados de documentos na abertura da câmera única e orienta o usuário no processo de digitalização. Também pode ser usado para digitalização lateral única de cartões de identificação, passaportes, carteiras de motorista etc.
Strings usadas dentro de atividades e sobreposições internas podem ser localizadas em qualquer idioma. Se você estiver usando RecognizerRunnerView (consulte este capítulo para obter mais informações) em sua atividade ou fragmento de digitalização personalizada, lidar com a localização como em qualquer outro aplicativo Android. RecognizerRunnerView não usa strings nem desenhos, ele usa apenas ativos da pasta assets/microblink . Esses ativos não devem ser tocados, pois são necessários para que o reconhecimento funcione corretamente.
No entanto, se você usar nossas atividades ou sobreposições internas, elas usarão os recursos embalados no LibBlinkID.aar para exibir strings e imagens na parte superior da visualização da câmera. Já preparamos strings para vários idiomas que você pode usar fora da caixa. Você também pode modificar essas seqüências ou adicionar seu próprio idioma.
Para usar um idioma, você deve ativá -lo no código:
Para usar um determinado idioma, na inicialização do aplicativo, antes de abrir qualquer componente da interface do usuário do SDK, você deve chamar o método LanguageUtils.setLanguageAndCountry(language, country, context) . Por exemplo, você pode definir a linguagem para croata assim:
// define BlinkID language
LanguageUtils . setLanguageAndCountry ( "hr" , "" , this ); O BlinkId pode ser facilmente traduzido para outros idiomas. A pasta res em LibBlinkID.aar Archive possui values de pasta que contém strings.xml - Este arquivo contém seqüências de strings em inglês. In order to make eg croatian translation, create a folder values-hr in your project and put the copy of strings.xml inside it (you might need to extract LibBlinkID.aar archive to access those files). Then, open that file and translate the strings from English into Croatian.
To modify an existing string, the best approach would be to:
strings.xml in folder res/values-hr of the LibBlinkID.aar archive<string name="MBBack">Back</string>strings.xml in the folder res/values-hr , if it doesn't already exist<string name="MBBack">Natrag</string>RecognizerRunner and RecognizerRunnerViewProcessing events, also known as Metadata callbacks are purely intended for giving processing feedback on UI or to capture some debug information during development of your app using BlinkID SDK. For that reason, built-in activities and fragments handle those events internally. If you need to handle those events yourself, you need to use either RecognizerRunnerView or RecognizerRunner.
Callbacks for all events are bundled into the MetadataCallbacks object. Both RecognizerRunner and RecognizerRunnerView have methods which allow you to set all your callbacks.
We suggest that you check for more information about available callbacks and events to which you can handle in the javadoc for MetadataCallbacks class.
Please note that both those methods need to pass information about available callbacks to the native code and for efficiency reasons this is done at the time setMetadataCallbacks method is called and not every time when change occurs within the MetadataCallbacks object. This means that if you, for example, set QuadDetectionCallback to MetadataCallbacks after you already called setMetadataCallbacks method, the QuadDetectionCallback will not be registered with the native code and you will not receive its events.
Similarly, if you, for example, remove the QuadDetectionCallback from MetadataCallbacks object after you already called setMetadataCallbacks method, your app will crash with NullPointerException when our processing code attempts to invoke the method on removed callback (which is now set to null ). We deliberately do not perform null check here because of two reasons:
null callback, while still being registered to native code is illegal state of your program and it should therefore crash Remember , each time you make some changes to MetadataCallbacks object, you need to apply those changes to to your RecognizerRunner or RecognizerRunnerView by calling its setMetadataCallbacks method.
Recognizer concept and RecognizerBundle This section will first describe what is a Recognizer and how it should be used to perform recognition of the images, videos and camera stream. Next, we will describe how RecognizerBundle can be used to tweak the recognition procedure and to transfer Recognizer objects between activities.
RecognizerBundle is an object which wraps the Recognizers and defines settings about how recognition should be performed. Besides that, RecognizerBundle makes it possible to transfer Recognizer objects between different activities, which is required when using built-in activities to perform scanning, as described in first scan section, but is also handy when you need to pass Recognizer objects between your activities.
List of all available Recognizer objects, with a brief description of each Recognizer , its purpose and recommendations how it should be used to get best performance and user experience, can be found here .
Recognizer concept The Recognizer is the basic unit of processing within the BlinkID SDK. Its main purpose is to process the image and extract meaningful information from it. As you will see later, the BlinkID SDK has lots of different Recognizer objects that have various purposes.
Each Recognizer has a Result object, which contains the data that was extracted from the image. The Result object is a member of corresponding Recognizer object and its lifetime is bound to the lifetime of its parent Recognizer object. If you need your Result object to outlive its parent Recognizer object, you must make a copy of it by calling its method clone() .
Every Recognizer is a stateful object, that can be in two states: idle state and working state . While in idle state , you can tweak Recognizer object's properties via its getters and setters. After you bundle it into a RecognizerBundle and use either RecognizerRunner or RecognizerRunnerView to run the processing with all Recognizer objects bundled within RecognizerBundle , it will change to working state where the Recognizer object is being used for processing. While being in working state , you cannot tweak Recognizer object's properties. If you need to, you have to create a copy of the Recognizer object by calling its clone() , then tweak that copy, bundle it into a new RecognizerBundle and use reconfigureRecognizers to ensure new bundle gets used on processing thread.
While Recognizer object works, it changes its internal state and its result. The Recognizer object's Result always starts in Empty state. When corresponding Recognizer object performs the recognition of given image, its Result can either stay in Empty state (in case Recognizer failed to perform recognition), move to Uncertain state (in case Recognizer performed the recognition, but not all mandatory information was extracted), move to StageValid state (in case Recognizer successfully scanned one part/side of the document and there are more fields to extract) or move to Valid state (in case Recognizer performed recognition and all mandatory information was successfully extracted from the image).
As soon as one Recognizer object's Result within RecognizerBundle given to RecognizerRunner or RecognizerRunnerView changes to Valid state, the onScanningDone callback will be invoked on same thread that performs the background processing and you will have the opportunity to inspect each of your Recognizer objects' Results to see which one has moved to Valid state.
As already stated in section about RecognizerRunnerView , as soon as onScanningDone method ends, the RecognizerRunnerView will continue processing new camera frames with same Recognizer objects, unless paused. Continuation of processing or resetting recognition will modify or reset all Recognizer objects's Results . When using built-in activities, as soon as onScanningDone is invoked, built-in activity pauses the RecognizerRunnerView and starts finishing the activity, while saving the RecognizerBundle with active Recognizer objects into Intent so they can be transferred back to the calling activities.
RecognizerBundle The RecognizerBundle is wrapper around Recognizers objects that can be used to transfer Recognizer objects between activities and to give Recognizer objects to RecognizerRunner or RecognizerRunnerView for processing.
The RecognizerBundle is always constructed with array of Recognizer objects that need to be prepared for recognition (ie their properties must be tweaked already). The varargs constructor makes it easier to pass Recognizer objects to it, without the need of creating a temporary array.
The RecognizerBundle manages a chain of Recognizer objects within the recognition process. When a new image arrives, it is processed by the first Recognizer in chain, then by the second and so on, iterating until a Recognizer object's Result changes its state to Valid or all of the Recognizer objects in chain were invoked (none getting a Valid result state). If you want to invoke all Recognizers in the chain, regardless of whether some Recognizer object's Result in chain has changed its state to Valid or not, you can allow returning of multiple results on a single image.
You cannot change the order of the Recognizer objects within the chain - no matter the order in which you give Recognizer objects to RecognizerBundle , they are internally ordered in a way that provides best possible performance and accuracy. Also, in order for BlinkID SDK to be able to order Recognizer objects in recognition chain in the best way possible, it is not allowed to have multiple instances of Recognizer objects of the same type within the chain. Attempting to do so will crash your application.
Recognizer objects between activities Besides managing the chain of Recognizer objects, RecognizerBundle also manages transferring bundled Recognizer objects between different activities within your app. Although each Recognizer object, and each its Result object implements Parcelable interface, it is not so straightforward to put those objects into Intent and pass them around between your activities and services for two main reasons:
Result object is tied to its Recognizer object, which manages lifetime of the native Result object.Result object often contains large data blocks, such as images, which cannot be transferred via Intent because of Android's Intent transaction data limit. Although the first problem can be easily worked around by making a copy of the Result and transfer it independently, the second problem is much tougher to cope with. This is where, RecognizerBundle's methods saveToIntent and loadFromIntent come to help, as they ensure the safe passing of Recognizer objects bundled within RecognizerBundle between activities according to policy defined with method setIntentDataTransferMode :
STANDARD , the Recognizer objects will be passed via Intent using normal Intent transaction mechanism , which is limited by Android's Intent transaction data limit. This is same as manually putting Recognizer objects into Intent and is OK as long as you do not use Recognizer objects that produce images or other large objects in their Results .OPTIMISED , the Recognizer objects will be passed via internal singleton object and no serialization will take place. This means that there is no limit to the size of data that is being passed. This is also the fastest transfer method, but it has a serious drawback - if Android kills your app to save memory for other apps and then later restarts it and redelivers Intent that should contain Recognizer objects, the internal singleton that should contain saved Recognizer objects will be empty and data that was being sent will be lost. You can easily provoke that condition by choosing No background processes under Limit background processes in your device's Developer options , and then switch from your app to another app and then back to your app.PERSISTED_OPTIMISED , the Recognizer objects will be passed via internal singleton object (just like in OPTIMISED mode) and will additionaly be serialized into a file in your application's private folder. In case Android restarts your app and internal singleton is empty after re-delivery of the Intent , the data will be loaded from file and nothing will be lost. The files will be automatically cleaned up when data reading takes place. Just like OPTIMISED , this mode does not have limit to the size of data that is being passed and does not have a drawback that OPTIMISED mode has, but some users might be concerned about files to which data is being written.onSaveInstanceState and save bundle back to file by calling its saveState method. Also, after saving state, you should ensure that you clear saved state in your onResume , as onCreate may not be called if activity is not restarted, while onSaveInstanceState may be called as soon as your activity goes to background (before onStop ), even though activity may not be killed at later time.OPTIMISED mode to transfer large data and image between activities or create your own mechanism for data transfer. Note that your application's private folder is only accessible by your application and your application alone, unless the end-user's device is rooted. This section will give a list of all Recognizer objects that are available within BlinkID SDK, their purpose and recommendations how they should be used to get best performance and user experience.
The FrameGrabberRecognizer is the simplest recognizer in BlinkID SDK, as it does not perform any processing on the given image, instead it just returns that image back to its FrameCallback . Its Result never changes state from Empty.
This recognizer is best for easy capturing of camera frames with RecognizerRunnerView . Note that Image sent to onFrameAvailable are temporary and their internal buffers all valid only until the onFrameAvailable method is executing - as soon as method ends, all internal buffers of Image object are disposed. If you need to store Image object for later use, you must create a copy of it by calling clone .
Also note that FrameCallback interface extends Parcelable interface, which means that when implementing FrameCallback interface, you must also implement Parcelable interface.
This is especially important if you plan to transfer FrameGrabberRecognizer between activities - in that case, keep in mind that the instance of your object may not be the same as the instance on which onFrameAvailable method gets called - the instance that receives onFrameAvailable calls is the one that is created within activity that is performing the scan.
The SuccessFrameGrabberRecognizer is a special Recognizer that wraps some other Recognizer and impersonates it while processing the image. However, when the Recognizer being impersonated changes its Result into Valid state, the SuccessFrameGrabberRecognizer captures the image and saves it into its own Result object.
Since SuccessFrameGrabberRecognizer impersonates its slave Recognizer object, it is not possible to give both concrete Recognizer object and SuccessFrameGrabberRecognizer that wraps it to same RecognizerBundle - doing so will have the same result as if you have given two instances of same Recognizer type to the RecognizerBundle - it will crash your application.
This recognizer is best for use cases when you need to capture the exact image that was being processed by some other Recognizer object at the time its Result became Valid . When that happens, SuccessFrameGrabber's Result will also become Valid and will contain described image. That image can then be retrieved with getSuccessFrame() method.
Unless stated otherwise for concrete recognizer, single side BlinkID recognizers from this list can be used in any context, but they work best with BlinkIdUISettings and DocumentScanUISettings , with UIs best suited for document scanning.
Combined recognizers should be used with BlinkIdUISettings . They manage scanning of multiple document sides in the single camera opening and guide the user through the scanning process. Some combined recognizers support scanning of multiple document types, but only one document type can be scanned at a time.
The BlinkIdSingleSideRecognizer scans and extracts data from the single side of the supported document. You can find the list of the currently supported documents here. We will continue expanding this recognizer by adding support for new document types in the future. Star this repo to stay updated.
The BlinkIdSingleSideRecognizer works best with the BlinkIdUISettings and BlinkIdOverlayController .
Use BlinkIdMultiSideRecognizer for scanning both sides of the supported document. First, it scans and extracts data from the front, then scans and extracts data from the back, and finally, combines results from both sides. The BlinkIdMultiSideRecognizer also performs data matching and returns a flag if the extracted data captured from the front side matches the data from the back. You can find the list of the currently supported documents here. We will continue expanding this recognizer by adding support for new document types in the future. Star this repo to stay updated.
The BlinkIdMultiSideRecognizer works best with the BlinkIdUISettings and BlinkIdOverlayController .
The MrtdRecognizer is used for scanning and data extraction from the Machine Readable Zone (MRZ) of the various Machine Readable Travel Documents (MRTDs) like ID cards and passports. This recognizer is not bound to the specific country, but it can be configured to only return data that match some criteria defined by the MrzFilter .
You can find information about usage context at the beginning of this section.
The MrtdCombinedRecognizer scans Machine Readable Zone (MRZ) after scanning the full document image and face image (usually MRZ is on the back side and face image is on the front side of the document). Internally, it uses DocumentFaceRecognizer for obtaining full document image and face image as the first step and then MrtdRecognizer for scanning the MRZ.
You can find information about usage context at the beginning of this section.
The PassportRecognizer is used for scanning and data extraction from the Machine Readable Zone (MRZ) of the various passport documents. This recognizer also returns face image from the passport.
You can find information about usage context at the beginning of this section.
The VisaRecognizer is used for scanning and data extraction from the Machine Readable Zone (MRZ) of the various visa documents. This recognizer also returns face image from the visa document.
You can find information about usage context at the beginning of this section.
The IdBarcodeRecognizer is used for scanning barcodes from various ID cards. Check this document to see the list of supported document types.
You can find information about usage context at the beginning of this section.
The DocumentFaceRecognizer is a special type of recognizer that only returns face image and full document image of the scanned document. It does not extract document fields like first name, last name, etc. This generic recognizer can be used to obtain document images in cases when specific support for some document type is not available.
You can find information about usage context at the beginning of this section.
You need to ensure that the final app gets all resources required by BlinkID . At the time of writing this documentation, Android does not have support for combining multiple AAR libraries into single fat AAR. The problem is that resource merging is done while building application, not while building AAR, so application must be aware of all its dependencies. There is no official Android way of "hiding" third party AAR within your AAR.
This problem is usually solved with transitive Maven dependencies, ie when publishing your AAR to Maven you specify dependencies of your AAR so they are automatically referenced by app using your AAR. Besides this, there are also several other approaches you can try:
RecognizerRunnerView ). You can perform custom UI integration while taking care that all resources (strings, layouts, images, ...) used are solely from your AAR, not from BlinkID . Then, in your AAR you should not reference LibBlinkID.aar as gradle dependency, instead you should unzip it and copy its assets to your AAR's assets folder, its classes.jar to your AAR's lib folder (which should be referenced by gradle as jar dependency) and contents of its jni folder to your AAR's src/main/jniLibs folder.BlinkID is distributed with ARMv7 and ARM64 native library binaries.
ARMv7 architecture gives the ability to take advantage of hardware accelerated floating point operations and SIMD processing with NEON. This gives BlinkID a huge performance boost on devices that have ARMv7 processors. Most new devices (all since 2012.) have ARMv7 processor so it makes little sense not to take advantage of performance boosts that those processors can give. Also note that some devices with ARMv7 processors do not support NEON and VFPv4 instruction sets, most popular being those based on NVIDIA Tegra 2, ARM Cortex A9 and older. Since these devices are old by today's standard, BlinkID does not support them. For the same reason, BlinkID does not support devices with ARMv5 ( armeabi ) architecture.
ARM64 is the new processor architecture that most new devices use. ARM64 processors are very powerful and also have the possibility to take advantage of new NEON64 SIMD instruction set to quickly process multiple pixels with a single instruction.
There are some issues to be considered:
LibBlinkID.aar archive contains ARMv7 and ARM64 builds of the native library. By default, when you integrate BlinkID into your app, your app will contain native builds for all these processor architectures. Thus, BlinkID will work on ARMv7 and ARM64 devices and will use ARMv7 features on ARMv7 devices and ARM64 features on ARM64 devices. However, the size of your application will be rather large.
We recommend that you distribute your app using App Bundle. This will defer apk generation to Google Play, allowing it to generate minimal APK for each specific device that downloads your app, including only required processor architecture support.
If you are unable to use App Bundle, you can create multiple flavors of your app - one flavor for each architecture. With gradle and Android studio this is very easy - just add the following code to build.gradle file of your app:
android {
...
splits {
abi {
enable true
reset()
include 'armeabi-v7a', 'arm64-v8a'
universalApk true
}
}
}
With that build instructions, gradle will build two different APK files for your app. Each APK will contain only native library for one processor architecture and one APK will contain all architectures. In order for Google Play to accept multiple APKs of the same app, you need to ensure that each APK has different version code. This can easily be done by defining a version code prefix that is dependent on architecture and adding real version code number to it in following gradle script:
// map for the version code
def abiVersionCodes = ['armeabi-v7a':1, 'arm64-v8a':2]
import com.android.build.OutputFile
android.applicationVariants.all { variant ->
// assign different version code for each output
variant.outputs.each { output ->
def filter = output.getFilter(OutputFile.ABI)
if(filter != null) {
output.versionCodeOverride = abiVersionCodes.get(output.getFilter(OutputFile.ABI)) * 1000000 + android.defaultConfig.versionCode
}
}
}
For more information about creating APK splits with gradle, check this article from Google.
After generating multiple APK's, you need to upload them to Google Play. For tutorial and rules about uploading multiple APK's to Google Play, please read the official Google article about multiple APKs.
If you won't be distributing your app via Google Play or for some other reasons want to have single APK of smaller size, you can completely remove support for certain CPU architecture from your APK. This is not recommended due to consequences .
To keep only some CPU architectures, for example armeabi-v7a and arm64-v8a , add the following statement to your android block inside build.gradle :
android {
...
ndk {
// Tells Gradle to package the following ABIs into your application
abiFilters 'armeabi-v7a', 'arm64-v8a'
}
}
This will remove other architecture builds for all native libraries used by the application.
To remove support for a certain CPU architecture only for BlinkID , add the following statement to your android block inside build.gradle :
android {
...
packagingOptions {
exclude 'lib/<ABI>/libBlinkID.so'
}
}
where <ABI> represents the CPU architecture you want to remove:
exclude 'lib/armeabi-v7a/libBlinkID.so'exclude 'lib/arm64-v8a/libBlinkID.so' You can also remove multiple processor architectures by specifying exclude directive multiple times. Just bear in mind that removing processor architecture will have side effects on performance and stability of your app. Please read this for more information.
Google decided that as of August 2019 all apps on Google Play that contain native code need to have native support for 64-bit processors (this includes ARM64 and x86_64). This means that you cannot upload application to Google Play Console that supports only 32-bit ABI and does not support corresponding 64-bit ABI.
By removing ARMv7 support, BlinkID will not work on devices that have ARMv7 processors.
By removing ARM64 support, BlinkID will not use ARM64 features on ARM64 device
If you are combining BlinkID library with other libraries that contain native code into your application, make sure you match the architectures of all native libraries. For example, if third party library has got only ARMv7 version, you must use exactly ARMv7 version of BlinkID with that library, but not ARM64. Using this architectures will crash your app at initialization step because JVM will try to load all its native dependencies in same preferred architecture and will fail with UnsatisfiedLinkError .
libc++_shared.so BlinkID contains native code that depends on the C++ runtime. This runtime is provided by the libc++_shared.so , which needs to be available in your app that is using BlinkID . However, the same file is also used by various other libraries that contain native components. If you happen to integrate both such library together with BlinkID in your app, your build will fail with an error similar to this one:
* What went wrong:
Execution failed for task ':app:mergeDebugNativeLibs'.
> A failure occurred while executing com.android.build.gradle.internal.tasks.MergeJavaResWorkAction
> 2 files found with path 'lib/arm64-v8a/libc++_shared.so' from inputs:
- <path>/.gradle/caches/transforms-3/3d428f9141586beb8805ce57f97bedda/transformed/jetified-opencv-4.5.3.0/jni/arm64-v8a/libc++_shared.so
- <path>/.gradle/caches/transforms-3/609476a082a81bd7af00fd16a991ee43/transformed/jetified-blinkid-6.12.0/jni/arm64-v8a/libc++_shared.so
If you are using jniLibs and CMake IMPORTED targets, see
https://developer.android.com/r/tools/jniLibs-vs-imported-targets
The error states that multiple different dependencies provide the same file lib/arm64/libc++_shared.so (in this case, OpenCV and BlinkID).
You can resolve this issue by making sure that the dependency that uses newer version of libc++_shared.so is listed first in your dependency list, and then, simply add the following to your build.gradle :
android {
packaging {
jniLibs {
pickFirsts.add("lib/armeabi-v7a/libc++_shared.so")
pickFirsts.add("lib/arm64-v8a/libc++_shared.so")
}
}
}
IMPORTANT NOTE
The code above will always select the first libc++_shared.so from your dependency list, so make sure that the dependency that uses the latest version of libc++_shared.so is listed first. This is because libc++_shared.so is backward-compatible, but not forward-compatible. This means that, eg libBlinkID.so built against libc++_shared.so from NDK r24 will work without problems when you package it together with libc++_shared.so from NDK r26, but will crash when you package it together with libc++_shared.so from NDK r21. This is true for all your native dependencies.
In case of problems with SDK integration, first make sure that you have followed integration instructions. If you're still having problems, please contact us at help.microblink.com.
If you are getting "invalid license key" error or having other license-related problems (eg some feature is not enabled that should be or there is a watermark on top of camera), first check the ADB logcat. All license-related problems are logged to error log so it is easy to determine what went wrong.
When you have to determine what is the license-relate problem or you simply do not understand the log, you should contact us help.microblink.com. When contacting us, please make sure you provide following information:
AndroidManifest.xml and/or your build.gradle file)Keep in mind: Versions 5.8.0 and above require an internet connection to work under our new License Management Program.
We're only asking you to do this so we can validate your trial license key. Data extraction still happens offline, on the device itself. Once the validation is complete, you can continue using the SDK in offline mode (or over a private network) until the next check.
If you are having problems with scanning certain items, undesired behaviour on specific device(s), crashes inside BlinkID or anything unmentioned, please do as follows:
enable logging to get the ability to see what is library doing. To enable logging, put this line in your application:
com . microblink . blinkid . util . Log . setLogLevel ( com . microblink . blinkid . util . Log . LogLevel . LOG_VERBOSE );After this line, library will display as much information about its work as possible. Please save the entire log of scanning session to a file that you will send to us. It is important to send the entire log, not just the part where crash occurred, because crashes are sometimes caused by unexpected behaviour in the early stage of the library initialization.
Contact us at help.microblink.com describing your problem and provide following information:
InvalidLicenseKeyException when I construct specific Recognizer object Each license key contains information about which features are allowed to use and which are not. This exception indicates that your production license does not allow using of specific Recognizer object. You should contact support to check if provided license is OK and that it really contains all features that you have purchased.
InvalidLicenseKeyException with trial license key Whenever you construct any Recognizer object or any other object that derives from Entity , a check whether license allows using that object will be performed. If license is not set prior constructing that object, you will get InvalidLicenseKeyException . We recommend setting license as early as possible in your app, ideally in onCreate callback of your Application singleton.
ClassNotFoundExceptionThis usually happens when you perform integration into Eclipse project and you forget to add resources or native libraries into the project. You must alway take care that same versions of both resources, assets, java library and native libraries are used in combination. Combining different versions of resources, assets, java and native libraries will trigger crash in SDK. This problem can also occur when you have performed improper integration of BlinkID SDK into your SDK. Please read how to embed BlinkID inside another SDK.
UnsatisfiedLinkError This error happens when JVM fails to load some native method from native library If performing integration into Android studio and this error happens, make sure that you have correctly combined BlinkID SDK with third party SDKs that contain native code, especially if you need resolving conflict over libc++_shared.so . If this error also happens in our integration sample apps, then it may indicate a bug in the SDK that is manifested on specific device. Please report that to our support team.
libc++_shared.so Please consult the section about resolving libc++_shared.so conflict.
MetadataCallbacks object, but it is not being called Make sure that after adding your callback to MetadataCallbacks you have applied changes to RecognizerRunnerView or RecognizerRunner as described in this section.
MetadataCallbacks object, and now app is crashing with NullPointerException Make sure that after removing your callback from MetadataCallbacks you have applied changes to RecognizerRunnerView or RecognizerRunner as described in this section.
onScanningDone callback I have the result inside my Recognizer , but when scanning activity finishes, the result is gone This usually happens when using RecognizerRunnerView and forgetting to pause the RecognizerRunnerView in your onScanningDone callback. Then, as soon as onScanningDone happens, the result is mutated or reset by additional processing that Recognizer performs in the time between end of your onScanningDone callback and actual finishing of the scanning activity. For more information about statefulness of the Recognizer objects, check this section.
IllegalStateException stating Data cannot be saved to intent because its size exceeds intent limit . This usually happens when you use Recognizer that produces image or similar large object inside its Result and that object exceeds the Android intent transaction limit. You should enable different intent data transfer mode. For more information about this, check this section. Also, instead of using built-in activity, you can use RecognizerRunnerFragment with built-in scanning overlay.
This usually happens when you attempt to transfer standalone Result that contains images or similar large objects via Intent and the size of the object exceeds Android intent transaction limit. Depending on the device, you will get either TransactionTooLargeException, a simple message BINDER TRANSACTION FAILED in log and your app will freeze or your app will get into restart loop. We recommend that you use RecognizerBundle and its API for sending Recognizer objects via Intent in a more safe manner (check this section for more information). However, if you really need to transfer standalone Result object (eg Result object obtained by cloning Result object owned by specific Recognizer object), you need to do that using global variables or singletons within your application. Sending large objects via Intent is not supported by Android.
Direct API When automatic scanning of camera frames with our camera management is used (provided camera overlays or direct usage of RecognizerRunnerView ), we use a stream of video frames and send multiple images to the recognition to boost reading accuracy. Also, we perform frame quality analysis and combine scanning results from multiple camera frames. On the other hand, when you are using the Direct API with a single image per document side, we cannot combine multiple images. We do our best to extract as much information as possible from that image. In some cases, when the quality of the input image is not good enough, for example, when the image is blurred or when glare is present, we are not able to successfully read the document.
Online trial licenses require a public network access for validation purposes. See Licensing issues.
onOcrResult() method in my OcrCallback is never invoked and all Result objects always return null in their OCR result gettersIn order to be able to obtain raw OCR result, which contains locations of each character, its value and its alternatives, you need to have a license that allows that. By default, licenses do not allow exposing raw OCR results in public API. If you really need that, please contact us and explain your use case.
You can find BlinkID SDK size report for all supported ABIs here.
Complete API reference can be found in Javadoc.
For any other questions, feel free to contact us at help.microblink.com.
