# tf.image.non_max_suppression_overlaps

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/image_ops_impl.py#L3910-L3956) |

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

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.image.non_max_suppression_overlaps`](https://www.tensorflow.org/api_docs/python/tf/image/non_max_suppression_overlaps)

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    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`](https://www.tensorflow.org/versions/r2.13/api_docs/python/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)

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| ## Args ||
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| `overlaps` | A 2-D float `Tensor` of shape `[num_boxes, num_boxes]` representing the n-by-n box overlap values. |
| `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 0-D float tensor representing the threshold for deciding whether boxes overlap too much with respect to the provided overlap values. |
| `score_threshold` | A 0-D float tensor representing the threshold for deciding when to remove boxes based on score. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
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| `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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