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> |
Inherited Method Summary
Public Methods
public void close ()
Throws
IOException |
---|
public Task<FirebaseVisionDocumentText> processImage (FirebaseVisionImage image)
Detects text from supplied document image.
For best efficiency, create a
FirebaseVisionImage
object using one of the following ways:
fromMediaImage(Image, int)
with aJPEG
formatted image fromandroid.hardware.camera2
.fromBitmap(android.graphics.Bitmap)
.
FirebaseVisionImage
factory methods will work as well, but possibly slightly
slower.
Returns
- A
Task
that asynchronously returns the detectedFirebaseVisionDocumentText
.