tensorflow:: ops:: SampleDistortedBoundingBoxV2
#include <image_ops.h>
Generate a single randomly distorted bounding box for an image.
Summary
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.
Args:
- scope: A Scope object
- image_size: 1-D, containing
[height, width, channels]
. - bounding_boxes: 3-D with shape
[batch, N, 4]
describing the N bounding boxes associated with the image. - min_object_covered: 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.
Optional attributes (see Attrs
):
- seed: If either
seed
orseed2
are set to non-zero, the random number generator is seeded by the givenseed
. Otherwise, it is seeded by a random seed. - seed2: A second seed to avoid seed collision.
- aspect_ratio_range: The cropped area of the image must have an aspect ratio = width / height within this range.
- area_range: The cropped area of the image must contain a fraction of the supplied image within this range.
- max_attempts: Number of attempts at generating a cropped region of the image of the specified constraints. After
max_attempts
failures, return the entire image. - use_image_if_no_bounding_boxes: Controls behavior if no bounding boxes supplied. If true, assume an implicit bounding box covering the whole input. If false, raise an error.
Returns:
Output
begin: 1-D, containing[offset_height, offset_width, 0]
. Provide as input totf.slice
.Output
size: 1-D, containing[target_height, target_width, -1]
. Provide as input totf.slice
.Output
bboxes: 3-D with shape[1, 1, 4]
containing the distorted bounding box. Provide as input totf.image.draw_bounding_boxes
.
Constructors and Destructors |
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SampleDistortedBoundingBoxV2(const ::tensorflow::Scope & scope, ::tensorflow::Input image_size, ::tensorflow::Input bounding_boxes, ::tensorflow::Input min_object_covered)
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SampleDistortedBoundingBoxV2(const ::tensorflow::Scope & scope, ::tensorflow::Input image_size, ::tensorflow::Input bounding_boxes, ::tensorflow::Input min_object_covered, const SampleDistortedBoundingBoxV2::Attrs & attrs)
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Public attributes |
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bboxes
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begin
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operation
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size
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Public static functions |
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AreaRange(const gtl::ArraySlice< float > & x)
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AspectRatioRange(const gtl::ArraySlice< float > & x)
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MaxAttempts(int64 x)
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Seed(int64 x)
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Seed2(int64 x)
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UseImageIfNoBoundingBoxes(bool x)
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Structs |
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tensorflow:: |
Optional attribute setters for SampleDistortedBoundingBoxV2. |
Public attributes
bboxes
::tensorflow::Output bboxes
begin
::tensorflow::Output begin
operation
Operation operation
size
::tensorflow::Output size
Public functions
SampleDistortedBoundingBoxV2
SampleDistortedBoundingBoxV2( const ::tensorflow::Scope & scope, ::tensorflow::Input image_size, ::tensorflow::Input bounding_boxes, ::tensorflow::Input min_object_covered )
SampleDistortedBoundingBoxV2
SampleDistortedBoundingBoxV2( const ::tensorflow::Scope & scope, ::tensorflow::Input image_size, ::tensorflow::Input bounding_boxes, ::tensorflow::Input min_object_covered, const SampleDistortedBoundingBoxV2::Attrs & attrs )
Public static functions
AreaRange
Attrs AreaRange( const gtl::ArraySlice< float > & x )
AspectRatioRange
Attrs AspectRatioRange( const gtl::ArraySlice< float > & x )
MaxAttempts
Attrs MaxAttempts( int64 x )
Seed
Attrs Seed( int64 x )
Seed2
Attrs Seed2( int64 x )
UseImageIfNoBoundingBoxes
Attrs UseImageIfNoBoundingBoxes( bool x )