mindspore.ops.IOU

class mindspore.ops.IOU(mode='iou')[source]

Calculates intersection over union for boxes.

Computes the intersection over union (IOU) or the intersection over foreground (IOF) based on the ground-truth and predicted regions.

Refer to mindspore.ops.iou() for more details.

Parameters: mode (string) – The mode is used to specify the calculation method, now supporting 'iou' (intersection over union) or 'iof' (intersection over foreground) mode. Default: 'iou' .

Inputs:

anchor_boxes (Tensor) - Anchor boxes, tensor of shape $(N, 4)$ . "N" indicates the number of anchor boxes, and the value "4" refers to "x0", "y0", "x1", and "y1". Data type must be float16 or float32.
gt_boxes (Tensor) - Ground truth boxes, tensor of shape $(M, 4)$ . "M" indicates the number of ground truth boxes, and the value "4" refers to "x0", "y0", "x1", and "y1". Data type must be float16 or float32.

Outputs:

Tensor, the 'iou' values, tensor of shape $(M, N)$ , with the same data type as anchor_boxes.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> iou = ops.IOU(mode='iou')
>>> anchor_boxes = Tensor(np.random.randint(1.0, 5.0, [3, 4]), mindspore.float16)
>>> gt_boxes = Tensor(np.random.randint(1.0, 5.0, [3, 4]), mindspore.float16)
>>> output = iou(anchor_boxes, gt_boxes)
>>> print(output.shape)
(3, 3)