mindspore.ops.BoundingBoxEncode

class mindspore.ops.BoundingBoxEncode(means=(0.0, 0.0, 0.0, 0.0), stds=(1.0, 1.0, 1.0, 1.0))[源代码]

Encodes bounding boxes locations.

This operator will calculate the offset between the predicted bounding boxes and the real bounding boxes, and this offset will be used as a variable for the loss.

Parameters

means (tuple) – Means for encoding bounding boxes calculation. Default: (0.0, 0.0, 0.0, 0.0).
stds (tuple) – The standard deviations of deltas calculation. Default: (1.0, 1.0, 1.0, 1.0).

Inputs:

anchor_box (Tensor) - Anchor boxes. The shape of anchor_box must be (n, 4).
groundtruth_box (Tensor) - Ground truth boxes. Which has the same shape with anchor_box.

Outputs:

Tensor, encoded bounding boxes. It has the same data type and shape as input anchor_box.

Raises

TypeError – If means or stds is not a tuple.
TypeError – If anchor_box or groundtruth_box is not a Tensor.

Supported Platforms:: Ascend GPU CPU

Examples

>>> anchor_box = Tensor([[2, 2, 2, 3], [2, 2, 2, 3]], mindspore.float32)
>>> groundtruth_box = Tensor([[1, 2, 1, 4], [1, 2, 1, 4]], mindspore.float32)
>>> boundingbox_encode = ops.BoundingBoxEncode(means=(0.0, 0.0, 0.0, 0.0), stds=(1.0, 1.0, 1.0, 1.0))
>>> output = boundingbox_encode(anchor_box, groundtruth_box)
>>> print(output)
[[ -1.  0.25  0.  0.40551758]
 [ -1.  0.25  0.  0.40551758]]