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.
Arguments:
- 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 | |
---|---|
SampleDistortedBoundingBoxV2(const ::tensorflow::Scope & scope, ::tensorflow::Input image_size, ::tensorflow::Input bounding_boxes, ::tensorflow::Input min_object_covered) | |
SampleDistortedBoundingBoxV2(const ::tensorflow::Scope & scope, ::tensorflow::Input image_size, ::tensorflow::Input bounding_boxes, ::tensorflow::Input min_object_covered, const SampleDistortedBoundingBoxV2::Attrs & attrs) |
Public attributes | |
---|---|
bboxes | |
begin | |
operation | |
size |
Public static functions | |
---|---|
AreaRange(const gtl::ArraySlice< float > & x) | |
AspectRatioRange(const gtl::ArraySlice< float > & x) | |
MaxAttempts(int64 x) | |
Seed(int64 x) | |
Seed2(int64 x) | |
UseImageIfNoBoundingBoxes(bool x) |
Structs | |
---|---|
tensorflow::ops::SampleDistortedBoundingBoxV2::Attrs | 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 )
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/cc/class/tensorflow/ops/sample-distorted-bounding-box-v2