Detector for performing optical character recognition(OCR) on an input image by sending the image to Google cloud ML backend. In comparison to FirebaseVisionTextRecognizer, it detects dense document text.

A cloud document text detector is created via getCloudDocumentTextRecognizer(FirebaseVisionCloudDocumentRecognizerOptions) or getCloudDocumentTextRecognizer() if you wish to use the default FirebaseVisionCloudDocumentRecognizerOptions. For example, the code below creates a cloud document text detector with default options.

 FirebaseVisionDocumentTextRecognizer cloudDocumentTextDetector =
    FirebaseVision.getInstance().getCloudDocumentTextRecognizer();
 

To perform document text detection in an image, you first need to create an instance of FirebaseVisionImage from a Bitmap, ByteBuffer, etc. See FirebaseVisionImage documentation for more details. For example, the code below creates a FirebaseVisionImage from a Bitmap.

      FirebaseVisionImage image = FirebaseVisionImage.fromBitmap(bitmap);

Then the code below can detect texts in the supplied FirebaseVisionImage.

 Task<FirebaseVisionDocumentText> task = cloudDocumentTextDetector.processImage(image);
 task.addOnSuccessListener(...).addOnFailureListener(...);
 

Public Method Summary

void	close()
Task<FirebaseVisionDocumentText>	processImage(FirebaseVisionImage image) Detects text from supplied document image.

Inherited Method Summary

From class java.lang.Object

Object	clone()
boolean	equals(Object arg0)
void	finalize()
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface java.io.Closeable

abstract void

close()

From interface java.lang.AutoCloseable

abstract void

close()