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

tf.image.non_max_suppression_overlaps( overlaps, scores, max_output_size, overlap_threshold=0.5, score_threshold=float('-inf'), name=None )

Prunes away boxes that have high overlap with previously selected boxes. N-by-n overlap values are supplied as square matrix. 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_overlaps( overlaps, scores, max_output_size, iou_threshold) selected_boxes = tf.gather(boxes, selected_indices)

Args | |
---|---|

`overlaps` | A 2-D float `Tensor` of shape `[num_boxes, num_boxes]` . |

`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. |

`overlap_threshold` | A float representing the threshold for deciding whether boxes overlap too much with respect to the provided overlap values. |

`score_threshold` | A float representing the threshold for deciding when to remove boxes based on score. |

`name` | A name for the operation (optional). |

Returns | |
---|---|

`selected_indices` | A 1-D integer `Tensor` of shape `[M]` representing the selected indices from the overlaps tensor, where `M <= max_output_size` . |

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/image/non_max_suppression_overlaps