from chainer.backends import cuda
[docs]def bbox_iou(bbox_a, bbox_b):
"""Calculate the Intersection of Unions (IoUs) between bounding boxes.
IoU is calculated as a ratio of area of the intersection
and area of the union.
This function accepts both :obj:`numpy.ndarray` and :obj:`cupy.ndarray` as
inputs. Please note that both :obj:`bbox_a` and :obj:`bbox_b` need to be
same type.
The output is same type as the type of the inputs.
Args:
bbox_a (array): An array whose shape is :math:`(N, 4)`.
:math:`N` is the number of bounding boxes.
The dtype should be :obj:`numpy.float32`.
bbox_b (array): An array similar to :obj:`bbox_a`,
whose shape is :math:`(K, 4)`.
The dtype should be :obj:`numpy.float32`.
Returns:
array:
An array whose shape is :math:`(N, K)`. \
An element at index :math:`(n, k)` contains IoUs between \
:math:`n` th bounding box in :obj:`bbox_a` and :math:`k` th bounding \
box in :obj:`bbox_b`.
"""
if bbox_a.shape[1] != 4 or bbox_b.shape[1] != 4:
raise IndexError
xp = cuda.get_array_module(bbox_a)
# top left
tl = xp.maximum(bbox_a[:, None, :2], bbox_b[:, :2])
# bottom right
br = xp.minimum(bbox_a[:, None, 2:], bbox_b[:, 2:])
area_i = xp.prod(br - tl, axis=2) * (tl < br).all(axis=2)
area_a = xp.prod(bbox_a[:, 2:] - bbox_a[:, :2], axis=1)
area_b = xp.prod(bbox_b[:, 2:] - bbox_b[:, :2], axis=1)
return area_i / (area_a[:, None] + area_b - area_i)