[Huawei Developers] HMS Community:
View attachment 5659799

Introduction

In this article, we will learn how to integrate Huawei ML kit camera stream in Android application KnowMyBoard. Account Kit provides seamless login functionality to the app with large user base.

The text recognition service can extract text from images of receipts, business cards, and documents. This service is useful for industries such as printing, education, and logistics. You can use it to create apps that handle data entry and check tasks.

The text recognition service is able to recognize text in both static images and dynamic camera streams with a host of APIs, which you can call synchronously or asynchronously to build your text recognition-enabled apps.

The on-device language detection service can detect the language of text when the Internet is unavailable. ML Kit detects languages in text and returns the language codes (which comply with the ISO 639-1 standard) and their respective confidences or the language code with the highest confidence. Currently, 56 languages can be detected.

Similar to the real-time translation service, the on-device translation service can be widely used in scenarios where translation between different languages is required. For example, travel apps can integrate this service to translate road signs and menus in other languages into tourists' native languages, providing more considerate services for them. Different from real-time translation, on-device translation does not require the Internet connection. You can easily use the translation service even if the Internet is disconnected.

Precautions

View attachment 5659805

Development Overview

You need to install Android Studio IDE and I assume that you have prior knowledge of Android application development.

Hardware Requirements

A computer (desktop or laptop) running Windows 10.

Android phone (with the USB cable), which is used for debugging.

Software Requirements

Java JDK 1.8 or later.

Android Studio software or Visual Studio or Code installed.

HMS Core (APK) 4.X or later

Integration steps

Step 1. Huawei developer account and complete identity verification in Huawei developer website, refer to register Huawei ID.

Step 2. Create project in AppGallery Connect

Step 3. Adding HMS Core SDK

Let's start coding

navigation_graph.xml

[/B]
<?xml version="1.0" encoding="utf-8"?>
<navigation xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:id="@+id/navigation_graph"
app:startDestination="@id/loginFragment">
<fragment
android:id="@+id/loginFragment"
android:name="com.huawei.hms.knowmyboard.dtse.activity.fragments.LoginFragment"
android:label="LoginFragment"/>
<fragment
android:id="@+id/mainFragment"
android:name="com.huawei.hms.knowmyboard.dtse.activity.fragments.MainFragment"
android:label="MainFragment"/>
<fragment
android:id="@+id/searchFragment"
android:name="com.huawei.hms.knowmyboard.dtse.activity.fragments.SearchFragment"
android:label="fragment_search"
tools:layout="@layout/fragment_search" />
</navigation>
[B]

TextRecognitionActivity.java

[/B]
public final class TextRecognitionActivity extends BaseActivity
implements OnRequestPermissionsResultCallback, View.OnClickListener {
private static final String TAG = "TextRecognitionActivity";
private LensEngine lensEngine = null;
private LensEnginePreview preview;
private GraphicOverlay graphicOverlay;
private ImageButton takePicture;
private ImageButton imageSwitch;
private RelativeLayout zoomImageLayout;
private ZoomImageView zoomImageView;
private ImageButton zoomImageClose;
CameraConfiguration cameraConfiguration = null;
private int facing = CameraConfiguration.CAMERA_FACING_BACK;
private Camera mCamera;
private boolean isLandScape;
private Bitmap bitmap;
private Bitmap bitmapCopy;
private LocalTextTransactor localTextTransactor;
private Handler mHandler = new MsgHandler(this);
private Dialog languageDialog;
private AddPictureDialog addPictureDialog;
private TextView textCN;
private TextView textEN;
private TextView textJN;
private TextView textKN;
private TextView textLN;
private TextView tv_language,tv_translated_txt;

private String textType = Constant.POSITION_CN;
private boolean isInitialization = false;
MLTextAnalyzer analyzer;
private static class MsgHandler extends Handler {
WeakReference<TextRecognitionActivity> mMainActivityWeakReference;

public MsgHandler(TextRecognitionActivity mainActivity) {
this.mMainActivityWeakReference = new WeakReference<>(mainActivity);
}

@Override
public void handleMessage(Message msg) {
super.handleMessage(msg);
TextRecognitionActivity mainActivity = this.mMainActivityWeakReference.get();
if (mainActivity == null) {

return;
}

if (msg.what == Constant.SHOW_TAKE_PHOTO_BUTTON) {
mainActivity.setVisible();

} else if (msg.what == Constant.HIDE_TAKE_PHOTO_BUTTON) {
mainActivity.setGone();

}
}
}

private void setVisible() {
if (this.takePicture.getVisibility() == View.GONE) {
this.takePicture.setVisibility(View.VISIBLE);
}
}

private void setGone() {
if (this.takePicture.getVisibility() == View.VISIBLE) {
this.takePicture.setVisibility(View.GONE);
}
}

@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
this.setContentView(R.layout.activity_text_recognition);
if (savedInstanceState != null) {
this.facing = savedInstanceState.getInt(Constant.CAMERA_FACING);
}
this.tv_language = this.findViewById(R.id.tv_lang);
this.tv_translated_txt = this.findViewById(R.id.tv_translated_txt);
this.preview = this.findViewById(R.id.live_preview);
this.graphicOverlay = this.findViewById(R.id.live_overlay);
this.cameraConfiguration = new CameraConfiguration();
this.cameraConfiguration.setCameraFacing(this.facing);
this.initViews();
this.isLandScape = (this.getResources().getConfiguration().orientation == Configuration.ORIENTATION_LANDSCAPE);
this.createLensEngine();
this.setStatusBar();
}

private void initViews() {
this.takePicture = this.findViewById(R.id.takePicture);
this.takePicture.setOnClickListener(this);
this.imageSwitch = this.findViewById(R.id.text_imageSwitch);
this.imageSwitch.setOnClickListener(this);
this.zoomImageLayout = this.findViewById(R.id.zoomImageLayout);
this.zoomImageView = this.findViewById(R.id.take_picture_overlay);
this.zoomImageClose = this.findViewById(R.id.zoomImageClose);
this.zoomImageClose.setOnClickListener(this);
this.findViewById(R.id.back).setOnClickListener(this);
this.findViewById(R.id.language_setting).setOnClickListener(this);
this.createLanguageDialog();
this.createAddPictureDialog();
}

@Override
public void onClick(View view) {
if (view.getId() == R.id.takePicture) {
this.takePicture();
} else if (view.getId() == R.id.zoomImageClose) {
this.zoomImageLayout.setVisibility(View.GONE);
this.recycleBitmap();
} else if (view.getId() == R.id.text_imageSwitch) {
this.showAddPictureDialog();
} else if (view.getId() == R.id.language_setting) {
this.showLanguageDialog();
} else if (view.getId() == R.id.simple_cn) {
SharedPreferencesUtil.getInstance(this)
.putStringValue(Constant.POSITION_KEY, Constant.POSITION_CN);
this.languageDialog.dismiss();
this.restartLensEngine(Constant.POSITION_CN);
} else if (view.getId() == R.id.english) {
SharedPreferencesUtil.getInstance(this)
.putStringValue(Constant.POSITION_KEY, Constant.POSITION_EN);
this.languageDialog.dismiss();
this.preview.release();
this.restartLensEngine(Constant.POSITION_EN);
} else if (view.getId() == R.id.japanese) {
SharedPreferencesUtil.getInstance(this)
.putStringValue(Constant.POSITION_KEY, Constant.POSITION_JA);
this.languageDialog.dismiss();
this.preview.release();
this.restartLensEngine(Constant.POSITION_JA);
} else if (view.getId() == R.id.korean) {
SharedPreferencesUtil.getInstance(this)
.putStringValue(Constant.POSITION_KEY, Constant.POSITION_KO);
this.languageDialog.dismiss();
this.preview.release();
this.restartLensEngine(Constant.POSITION_KO);
} else if (view.getId() == R.id.latin) {
SharedPreferencesUtil.getInstance(this)
.putStringValue(Constant.POSITION_KEY, Constant.POSITION_LA);
this.languageDialog.dismiss();
this.preview.release();
this.restartLensEngine(Constant.POSITION_LA);
} else if (view.getId() == R.id.back) {
releaseLensEngine();
this.finish();
}
}

private void restartLensEngine(String type) {
if (this.textType.equals(type)) {
return;
}
this.lensEngine.release();
this.lensEngine = null;
this.createLensEngine();
this.startLensEngine();
if (this.lensEngine == null || this.lensEngine.getCamera() == null) {
return;
}
this.mCamera = this.lensEngine.getCamera();
try {
this.mCamera.setPreviewDisplay(this.preview.getSurfaceHolder());
} catch (IOException e) {
Log.d(TextRecognitionActivity.TAG, "initViews IOException");
}
}

@Override
public void onBackPressed() {
if (this.zoomImageLayout.getVisibility() == View.VISIBLE) {
this.zoomImageLayout.setVisibility(View.GONE);
this.recycleBitmap();
} else {
super.onBackPressed();
releaseLensEngine();
}
}

private void createLanguageDialog() {
this.languageDialog = new Dialog(this, R.style.MyDialogStyle);
View view = View.inflate(this, R.layout.dialog_language_setting, null);
// Set up a custom layout
this.languageDialog.setContentView(view);
this.textCN = view.findViewById(R.id.simple_cn);
this.textCN.setOnClickListener(this);
this.textEN = view.findViewById(R.id.english);
this.textEN.setOnClickListener(this);
this.textJN = view.findViewById(R.id.japanese);
this.textJN.setOnClickListener(this);
this.textKN = view.findViewById(R.id.korean);
this.textKN.setOnClickListener(this);
this.textLN = view.findViewById(R.id.latin);
this.textLN.setOnClickListener(this);
this.languageDialog.setCanceledOnTouchOutside(true);
// Set the size of the dialog
Window dialogWindow = this.languageDialog.getWindow();
WindowManager.LayoutParams layoutParams = dialogWindow.getAttributes();
layoutParams.width = WindowManager.LayoutParams.MATCH_PARENT;
layoutParams.height = WindowManager.LayoutParams.WRAP_CONTENT;
layoutParams.gravity = Gravity.BOTTOM;
dialogWindow.setAttributes(layoutParams);
}

private void showLanguageDialog() {
this.initDialogViews();
this.languageDialog.show();
}

private void createAddPictureDialog() {
this.addPictureDialog = new AddPictureDialog(this, AddPictureDialog.TYPE_NORMAL);
final Intent intent = new Intent(TextRecognitionActivity.this, RemoteDetectionActivity.class);
intent.putExtra(Constant.MODEL_TYPE, Constant.CLOUD_TEXT_DETECTION);
this.addPictureDialog.setClickListener(new AddPictureDialog.ClickListener() {
@Override
public void takePicture() {
lensEngine.release();
isInitialization = false;
intent.putExtra(Constant.ADD_PICTURE_TYPE, Constant.TYPE_TAKE_PHOTO);
TextRecognitionActivity.this.startActivity(intent);
}

@Override
public void selectImage() {
intent.putExtra(Constant.ADD_PICTURE_TYPE, Constant.TYPE_SELECT_IMAGE);
TextRecognitionActivity.this.startActivity(intent);
}

@Override
public void doExtend() {

}
});
}

private void showAddPictureDialog() {
this.addPictureDialog.show();
}

private void initDialogViews() {
String position = SharedPreferencesUtil.getInstance(this).getStringValue(Constant.POSITION_KEY);
this.textType = position;
this.textCN.setSelected(false);
this.textEN.setSelected(false);
this.textJN.setSelected(false);
this.textLN.setSelected(false);
this.textKN.setSelected(false);
switch (position) {
case Constant.POSITION_CN:
this.textCN.setSelected(true);
break;
case Constant.POSITION_EN:
this.textEN.setSelected(true);
break;
case Constant.POSITION_LA:
this.textLN.setSelected(true);
break;
case Constant.POSITION_JA:
this.textJN.setSelected(true);
break;
case Constant.POSITION_KO:
this.textKN.setSelected(true);
break;
default:
}
}

@Override
protected void onSaveInstanceState(Bundle outState) {
outState.putInt(Constant.CAMERA_FACING, this.facing);
super.onSaveInstanceState(outState);
}

private void createLensEngine() {
MLLocalTextSetting setting = new MLLocalTextSetting.Factory()
.setOCRMode(MLLocalTextSetting.OCR_DETECT_MODE)
// Specify languages that can be recognized.
.setLanguage("ko")
.create();
analyzer = MLAnalyzerFactory.getInstance().getLocalTextAnalyzer(setting);
//analyzer = new MLTextAnalyzer.Factory(this).create();

if (this.lensEngine == null) {
this.lensEngine = new LensEngine(this, this.cameraConfiguration, this.graphicOverlay);

}
try {
this.localTextTransactor = new LocalTextTransactor(this.mHandler, this);
this.lensEngine.setMachineLearningFrameTransactor(this.localTextTransactor);
// this.lensEngine.setMachineLearningFrameTransactor((ImageTransactor) new ObjectAnalyzerTransactor());
isInitialization = true;
} catch (Exception e) {
Toast.makeText(
this,
"Can not create image transactor: " + e.getMessage(),
Toast.LENGTH_LONG)
.show();
}
}

private void startLensEngine() {
if (this.lensEngine != null) {
try {
this.preview.start(this.lensEngine, false);
} catch (IOException e) {
Log.e(TextRecognitionActivity.TAG, "Unable to start lensEngine.", e);
this.lensEngine.release();
this.lensEngine = null;
}
}
}

@Override
public void onResume() {
super.onResume();
if (!isInitialization){
createLensEngine();
}
this.startLensEngine();
}

@Override
protected void onStop() {
super.onStop();
this.preview.stop();
}

private void releaseLensEngine() {
if (this.lensEngine != null) {
this.lensEngine.release();
this.lensEngine = null;
}
recycleBitmap();
}

@Override
protected void onDestroy() {
super.onDestroy();
releaseLensEngine();
if (analyzer != null) {
try {
analyzer.stop();
} catch (IOException e) {
// Exception handling.
Log.e(TAG,"Error while releasing analyzer");
}
}
}

private void recycleBitmap() {
if (this.bitmap != null && !this.bitmap.isRecycled()) {
this.bitmap.recycle();
this.bitmap = null;
}
if (this.bitmapCopy != null && !this.bitmapCopy.isRecycled()) {
this.bitmapCopy.recycle();
this.bitmapCopy = null;
}
}

private void takePicture() {

this.zoomImageLayout.setVisibility(View.VISIBLE);
LocalDataProcessor localDataProcessor = new LocalDataProcessor();
localDataProcessor.setLandScape(this.isLandScape);
this.bitmap = BitmapUtils.getBitmap(this.localTextTransactor.getTransactingImage(), this.localTextTransactor.getTransactingMetaData());

float previewWidth = localDataProcessor.getMaxWidthOfImage(this.localTextTransactor.getTransactingMetaData());
float previewHeight = localDataProcessor.getMaxHeightOfImage(this.localTextTransactor.getTransactingMetaData());
if (this.isLandScape) {
previewWidth = localDataProcessor.getMaxHeightOfImage(this.localTextTransactor.getTransactingMetaData());
previewHeight = localDataProcessor.getMaxWidthOfImage(this.localTextTransactor.getTransactingMetaData());
}
this.bitmapCopy = Bitmap.createBitmap(this.bitmap).copy(Bitmap.Config.ARGB_8888, true);

Canvas canvas = new Canvas(this.bitmapCopy);
float min = Math.min(previewWidth, previewHeight);
float max = Math.max(previewWidth, previewHeight);

if (this.getResources().getConfiguration().orientation == Configuration.ORIENTATION_PORTRAIT) {
localDataProcessor.setCameraInfo(this.graphicOverlay, canvas, min, max);
} else {
localDataProcessor.setCameraInfo(this.graphicOverlay, canvas, max, min);
}
localDataProcessor.drawHmsMLVisionText(canvas, this.localTextTransactor.getLastResults().getBlocks());
this.zoomImageView.setImageBitmap(this.bitmapCopy);
// Create an MLFrame object using the bitmap, which is the image data in bitmap format.
MLFrame frame = MLFrame.fromBitmap(bitmap);
Task<MLText> task = analyzer.asyncAnalyseFrame(frame);
task.addOnSuccessListener(new OnSuccessListener<MLText>() {
@Override
public void onSuccess(MLText text) {
String detectText = text.getStringValue();
// Processing for successful recognition.
// Create a local language detector.
MLLangDetectorFactory factory = MLLangDetectorFactory.getInstance();
MLLocalLangDetectorSetting setting = new MLLocalLangDetectorSetting.Factory()
// Set the minimum confidence threshold for language detection.
.setTrustedThreshold(0.01f)
.create();
MLLocalLangDetector myLocalLangDetector = factory.getLocalLangDetector(setting);
Task<String> firstBestDetectTask = myLocalLangDetector.firstBestDetect(detectText);
firstBestDetectTask.addOnSuccessListener(new OnSuccessListener<String>() {
@Override
public void onSuccess(String languageDetected) {
// Processing logic for detection success.
Log.d("TAG", "Lang detect :" + languageDetected);
Log.d("TAG", " detectText :" + detectText);

translate(languageDetected,detectText);
}
}).addOnFailureListener(new OnFailureListener() {
@Override
public void onFailure(Exception e) {
// Processing logic for detection failure.
Log.e("TAG", "Lang detect error:" + e.getMessage());
}
});
}
}).addOnFailureListener(new OnFailureListener() {
@Override
public void onFailure(Exception e) {
// Processing logic for recognition failure.
Log.e("TAG"," Text : Processing logic for recognition failure");
}
});
}

private void translate(String languageDetected, String detectText) {

MLApplication.initialize(getApplication());
MLApplication.getInstance().setApiKey("DAEDAF48ZIMI4ettQdTfCKlXgaln/E+TO/PrsX+LpP2BubkmED/iC0iVEps5vfx1ol27rHvuwiq64YphpPkGYWbf9La8XjnvC9qhwQ==");

// Create an offline translator.
MLLocalTranslateSetting setting = new MLLocalTranslateSetting.Factory()
// Set the source language code. The ISO 639-1 standard is used. This parameter is mandatory. If this parameter is not set, an error may occur.
.setSourceLangCode(languageDetected)
// Set the target language code. The ISO 639-1 standard is used. This parameter is mandatory. If this parameter is not set, an error may occur.
.setTargetLangCode("en")
.create();

MLLocalTranslator myLocalTranslator = MLTranslatorFactory.getInstance().getLocalTranslator(setting);
// Set the model download policy.
MLModelDownloadStrategy downloadStrategy = new MLModelDownloadStrategy.Factory()
.needWifi()// It is recommended that you download the package in a Wi-Fi environment.
.create();
// Create a download progress listener.
MLModelDownloadListener modelDownloadListener = new MLModelDownloadListener() {
@Override
public void onProcess(long alreadyDownLength, long totalLength) {
runOnUiThread(new Runnable() {
@Override
public void run() {
// Display the download progress or perform other operations.
}
});
}
};

myLocalTranslator.preparedModel(downloadStrategy, modelDownloadListener).
addOnSuccessListener(new OnSuccessListener<Void>() {
@Override
public void onSuccess(Void aVoid) {
// Called when the model package is successfully downloaded.
// input is a string of less than 5000 characters.
final Task<String> task = myLocalTranslator.asyncTranslate(detectText);
// Before translation, ensure that the models have been successfully downloaded.
task.addOnSuccessListener(new OnSuccessListener<String>() {
@Override
public void onSuccess(String translated) {
// Processing logic for detection success.
Log.e("TAG"," Translated Text : "+translated);
tv_translated_txt.setText(translated);
}
}).addOnFailureListener(new OnFailureListener() {
@Override
public void onFailure(Exception e) {
// Processing logic for detection failure.
Log.e("TAG"," Translation failed "+e.getMessage());
Toast.makeText(TextRecognitionActivity.this,"Please check internet connection.",Toast.LENGTH_SHORT).show();
}
});
}
}).addOnFailureListener(new OnFailureListener() {
@Override
public void onFailure(Exception e) {
// Called when the model package fails to be downloaded.
Log.e("TAG"," Translation failed onFailure "+e.getMessage());
}
});

}

}

[B]

MainFragment.java