AI-generated Key Takeaways
-  Segmenter identifies foreground or background pixels in an image. 
-  To perform segmentation, you first create an InputImage instance. 
-  The processmethod performs segmentation and returns a SegmentationMask asynchronously.
-  The closemethod closes the detector and releases its resources.
A Segmentation client for identifying pixels in a supplied image as being part of the foreground or the background.
Segmenter segmenter = Segmentation.getClient(segmenterOptions); To perform segmentation of an image, you first need to create an instance of InputImage from a Bitmap, ByteBuffer, etc. See InputImage documentation for more details. For example, the code below creates a InputImage from a Bitmap.
InputImage image = InputImage.fromBitmap(bitmap, rotationDegrees); InputImage and asynchronously return a SegmentationMask. Task<SegmentationMask> task = segmenter.process(image); task.addOnSuccessListener(...).addOnFailureListener(...); Public Method Summary
| abstract void |  close()   Closes the detector and releases its resources.  | 
| abstract Task<SegmentationMask> | |
| abstract Task<SegmentationMask> | 
Inherited Method Summary
Public Methods
public abstract void close ()
Closes the detector and releases its resources.
public abstract Task<SegmentationMask> process (MlImage image)
Performs segmentation on an input image.
This is an experimental API in beta version.
Create an MlImage object using one of MlImage's builder methods. See MlImage documentation for more details.
Returns
- a Taskthat asynchronously returns aSegmentationMask.
public abstract Task<SegmentationMask> process (InputImage image)
Performs segmentation on an input image.
Create an InputImage object using one of InputImage's factory methods. See InputImage documentation for more details.
Returns
- a Taskthat asynchronously returns aSegmentationMask.
