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tensorflow::ops::NonMaxSuppressionV4

#include <image_ops.h>

Greedily selects a subset of bounding boxes in descending order of score,.

Summary

pruning away boxes that have high intersection-over-union (IOU) overlap with previously selected boxes. Bounding boxes with score less than score_threshold are removed. Bounding boxes are supplied as [y1, x1, y2, x2], where (y1, x1) and (y2, x2) are the coordinates of any diagonal pair of box corners and the coordinates can be provided as normalized (i.e., lying in the interval [0, 1]) or absolute. Note that this algorithm is agnostic to where the origin is in the coordinate system and more generally is invariant to orthogonal transformations and translations of the coordinate system; thus translating or reflections of the coordinate system result in the same boxes being selected by the algorithm. The output of this operation is a set of integers indexing into the input collection of bounding boxes representing the selected boxes. The bounding box coordinates corresponding to the selected indices can then be obtained using the tf.gather operation. For example: selected_indices = tf.image.non_max_suppression_v2( boxes, scores, max_output_size, iou_threshold, score_threshold) selected_boxes = tf.gather(boxes, selected_indices)

Arguments:

  • scope: A Scope object
  • boxes: A 2-D float tensor of shape [num_boxes, 4].
  • scores: A 1-D float tensor of shape [num_boxes] representing a single score corresponding to each box (each row of boxes).
  • max_output_size: A scalar integer tensor representing the maximum number of boxes to be selected by non max suppression.
  • iou_threshold: A 0-D float tensor representing the threshold for deciding whether boxes overlap too much with respect to IOU.
  • score_threshold: A 0-D float tensor representing the threshold for deciding when to remove boxes based on score.

Optional attributes (see Attrs):

  • pad_to_max_output_size: If true, the output selected_indices is padded to be of length max_output_size. Defaults to false.

Returns:

  • Output selected_indices: A 1-D integer tensor of shape [M] representing the selected indices from the boxes tensor, where M <= max_output_size.
  • Output valid_outputs: A 0-D integer tensor representing the number of valid elements in selected_indices, with the valid elements appearing first.

Constructors and Destructors

NonMaxSuppressionV4(const ::tensorflow::Scope & scope, ::tensorflow::Input boxes, ::tensorflow::Input scores, ::tensorflow::Input max_output_size, ::tensorflow::Input iou_threshold, ::tensorflow::Input score_threshold)
NonMaxSuppressionV4(const ::tensorflow::Scope & scope, ::tensorflow::Input boxes, ::tensorflow::Input scores, ::tensorflow::Input max_output_size, ::tensorflow::Input iou_threshold, ::tensorflow::Input score_threshold, const NonMaxSuppressionV4::Attrs & attrs)

Public attributes

operation
selected_indices
valid_outputs

Public static functions

PadToMaxOutputSize(bool x)

Structs

tensorflow::ops::NonMaxSuppressionV4::Attrs

Optional attribute setters for NonMaxSuppressionV4.

Public attributes

operation

Operation operation

selected_indices

::tensorflow::Output selected_indices

valid_outputs

::tensorflow::Output valid_outputs

Public functions

NonMaxSuppressionV4

 NonMaxSuppressionV4(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input boxes,
  ::tensorflow::Input scores,
  ::tensorflow::Input max_output_size,
  ::tensorflow::Input iou_threshold,
  ::tensorflow::Input score_threshold
)

NonMaxSuppressionV4

 NonMaxSuppressionV4(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input boxes,
  ::tensorflow::Input scores,
  ::tensorflow::Input max_output_size,
  ::tensorflow::Input iou_threshold,
  ::tensorflow::Input score_threshold,
  const NonMaxSuppressionV4::Attrs & attrs
)

Public static functions

PadToMaxOutputSize

Attrs PadToMaxOutputSize(
  bool x
)