function nonMaxSuppressionWithScoreAsync_(_x, _x2, _x3, _x4, _x5, _x6) {
	  return _nonMaxSuppressionWithScoreAsync_.apply(this, arguments);
	}
Asynchronously performs non maximum suppression of bounding boxes based on
iou (intersection over union).

This op also supports a Soft-NMS mode (c.f.
Bodla et al, https://arxiv.org/abs/1704.04503) where boxes reduce the score
of other overlapping boxes, therefore favoring different regions of the image
with high scores. To enable this Soft-NMS mode, set the `softNmsSigma`
parameter to be larger than 0.

@param boxes a 2d tensor of shape `[numBoxes, 4]`. Each entry is
    `[y1, x1, y2, x2]`, where `(y1, x1)` and `(y2, x2)` are the corners of
    the bounding box.
@param scores a 1d tensor providing the box scores of shape `[numBoxes]`.
@param maxOutputSize The maximum number of boxes to be selected.
@param iouThreshold A float representing the threshold for deciding whether
    boxes overlap too much with respect to IOU. Must be between [0, 1].
    Defaults to 0.5 (50% box overlap).
@param scoreThreshold A threshold for deciding when to remove boxes based
    on score. Defaults to -inf, which means any score is accepted.
@param softNmsSigma A float representing the sigma parameter for Soft NMS.
    When sigma is 0, it falls back to nonMaxSuppression.
@return A map with the following properties:
    - selectedIndices: A 1D tensor with the selected box indices.
    - selectedScores: A 1D tensor with the corresponding scores for each
      selected box.

@doc {heading: 'Operations', subheading: 'Images', namespace: 'image'}