mindspore.ops.BoundingBoxDecode
- class mindspore.ops.BoundingBoxDecode(max_shape, means=(0.0, 0.0, 0.0, 0.0), stds=(1.0, 1.0, 1.0, 1.0), wh_ratio_clip=0.016)[源代码]
Decodes bounding boxes locations.
The function of the operator is to calculate the offset, and this operator converts the offset into a Bbox, which is used to mark the target in the subsequent images, etc.
- Parameters
means (tuple) – The means of deltas 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).
max_shape (tuple) – The max size limit for decoding box calculation.
wh_ratio_clip (float) – The limit of width and height ratio for decoding box calculation. Default: 0.016.
- Inputs:
anchor_box (Tensor) - Anchor boxes. The shape of anchor_box must be (n, 4).
deltas (Tensor) - Delta of boxes. Which has the same shape with anchor_box.
- Outputs:
Tensor, decoded boxes. It has the same data type and shape as anchor_box.
- Raises
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> anchor_box = Tensor([[4, 1, 2, 1], [2, 2, 2, 3]], mindspore.float32) >>> deltas = Tensor([[3, 1, 2, 2], [1, 2, 1, 4]], mindspore.float32) >>> boundingbox_decode = ops.BoundingBoxDecode(means=(0.0, 0.0, 0.0, 0.0), stds=(1.0, 1.0, 1.0, 1.0), ... max_shape=(768, 1280), wh_ratio_clip=0.016) >>> output = boundingbox_decode(anchor_box, deltas) >>> print(output) [[ 4.1953125 0. 0. 5.1953125] [ 2.140625 0. 3.859375 60.59375 ]]