SampleDistortedBoundingBox

public final class SampleDistortedBoundingBox

Generate a single randomly distorted bounding box for an image.

Bounding box annotations are often supplied in addition to ground-truth labels in image recognition or object localization tasks. A common technique for training such a system is to randomly distort an image while preserving its content, i.e. data augmentation. This Op outputs a randomly distorted localization of an object, i.e. bounding box, given an `image_size`, `bounding_boxes` and a series of constraints.

The output of this Op is a single bounding box that may be used to crop the original image. The output is returned as 3 tensors: `begin`, `size` and `bboxes`. The first 2 tensors can be fed directly into tf.slice to crop the image. The latter may be supplied to tf.image.draw_bounding_boxes to visualize what the bounding box looks like.

Bounding boxes are supplied and returned as `[y_min, x_min, y_max, x_max]`. The bounding box coordinates are floats in `[0.0, 1.0]` relative to the width and height of the underlying image.

For example,

# Generate a single distorted bounding box.
     begin, size, bbox_for_draw = tf.image.sample_distorted_bounding_box(
         tf.shape(image),
         bounding_boxes=bounding_boxes)
 
     # Draw the bounding box in an image summary.
     image_with_box = tf.image.draw_bounding_boxes(tf.expand_dims(image, 0),
                                                   bbox_for_draw)
     tf.summary.image('images_with_box', image_with_box)
 
     # Employ the bounding box to distort the image.
     distorted_image = tf.slice(image, begin, size)

Note that if no bounding box information is available, setting `use_image_if_no_bounding_boxes = true` will assume there is a single implicit bounding box covering the whole image. If `use_image_if_no_bounding_boxes` is false and no bounding boxes are supplied, an error is raised.

Nested Classes

class SampleDistortedBoundingBox.Options Optional attributes for SampleDistortedBoundingBox

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

static SampleDistortedBoundingBox.Options	areaRange(List<Float> areaRange)
static SampleDistortedBoundingBox.Options	aspectRatioRange(List<Float> aspectRatioRange)
Output<TFloat32>	bboxes() 3-D with shape `[1, 1, 4]` containing the distorted bounding box.
Output<T>	begin() 1-D, containing `[offset_height, offset_width, 0]`.
static <T extends TNumber> SampleDistortedBoundingBox<T>	create(Scope scope, Operand<T> imageSize, Operand<TFloat32> boundingBoxes, Operand<TFloat32> minObjectCovered, Options... options) Factory method to create a class wrapping a new SampleDistortedBoundingBox operation.
static SampleDistortedBoundingBox.Options	maxAttempts(Long maxAttempts)
static SampleDistortedBoundingBox.Options	seed(Long seed)
static SampleDistortedBoundingBox.Options	seed2(Long seed2)
Output<T>	size() 1-D, containing `[target_height, target_width, -1]`.
static SampleDistortedBoundingBox.Options	useImageIfNoBoundingBoxes(Boolean useImageIfNoBoundingBoxes)

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single `Operation`.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
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 org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single `Operation`.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "SampleDistortedBoundingBoxV2"

Public Methods

public static SampleDistortedBoundingBox.Options areaRange (List<Float> areaRange)

Parameters

areaRange	The cropped area of the image must contain a fraction of the supplied image within this range.

public static SampleDistortedBoundingBox.Options aspectRatioRange (List<Float> aspectRatioRange)

Parameters

aspectRatioRange	The cropped area of the image must have an aspect ratio = width / height within this range.

public Output<TFloat32> bboxes ()

3-D with shape `[1, 1, 4]` containing the distorted bounding box. Provide as input to tf.image.draw_bounding_boxes.

public Output<T> begin ()

1-D, containing `[offset_height, offset_width, 0]`. Provide as input to tf.slice.

public static SampleDistortedBoundingBox<T> create (Scope scope, Operand<T> imageSize, Operand<TFloat32> boundingBoxes, Operand<TFloat32> minObjectCovered, Options... options)

Factory method to create a class wrapping a new SampleDistortedBoundingBox operation.

Parameters

scope	current scope
imageSize	1-D, containing `[height, width, channels]`.
boundingBoxes	3-D with shape `[batch, N, 4]` describing the N bounding boxes associated with the image.
minObjectCovered	The cropped area of the image must contain at least this fraction of any bounding box supplied. The value of this parameter should be non-negative. In the case of 0, the cropped area does not need to overlap any of the bounding boxes supplied.
options	carries optional attributes values

Returns

a new instance of SampleDistortedBoundingBox

public static SampleDistortedBoundingBox.Options maxAttempts (Long maxAttempts)

Parameters

maxAttempts	Number of attempts at generating a cropped region of the image of the specified constraints. After `max_attempts` failures, return the entire image.

public static SampleDistortedBoundingBox.Options seed (Long seed)

Parameters

seed	If either `seed` or `seed2` are set to non-zero, the random number generator is seeded by the given `seed`. Otherwise, it is seeded by a random seed.

public static SampleDistortedBoundingBox.Options seed2 (Long seed2)

Parameters

seed2	A second seed to avoid seed collision.

public Output<T> size ()

1-D, containing `[target_height, target_width, -1]`. Provide as input to tf.slice.

public static SampleDistortedBoundingBox.Options useImageIfNoBoundingBoxes (Boolean useImageIfNoBoundingBoxes)

Parameters

useImageIfNoBoundingBoxes	Controls behavior if no bounding boxes supplied. If true, assume an implicit bounding box covering the whole input. If false, raise an error.