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insightface/detection/scrfd/mmdet/core/bbox/demodata.py
2021-05-12 11:40:54 +08:00

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Python
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import numpy as np
import torch
def ensure_rng(rng=None):
"""Simple version of the ``kwarray.ensure_rng``
Args:
rng (int | numpy.random.RandomState | None):
if None, then defaults to the global rng. Otherwise this can be an
integer or a RandomState class
Returns:
(numpy.random.RandomState) : rng -
a numpy random number generator
References:
https://gitlab.kitware.com/computer-vision/kwarray/blob/master/kwarray/util_random.py#L270
"""
if rng is None:
rng = np.random.mtrand._rand
elif isinstance(rng, int):
rng = np.random.RandomState(rng)
else:
rng = rng
return rng
def random_boxes(num=1, scale=1, rng=None):
"""Simple version of ``kwimage.Boxes.random``
Returns:
Tensor: shape (n, 4) in x1, y1, x2, y2 format.
References:
https://gitlab.kitware.com/computer-vision/kwimage/blob/master/kwimage/structs/boxes.py#L1390
Example:
>>> num = 3
>>> scale = 512
>>> rng = 0
>>> boxes = random_boxes(num, scale, rng)
>>> print(boxes)
tensor([[280.9925, 278.9802, 308.6148, 366.1769],
[216.9113, 330.6978, 224.0446, 456.5878],
[405.3632, 196.3221, 493.3953, 270.7942]])
"""
rng = ensure_rng(rng)
tlbr = rng.rand(num, 4).astype(np.float32)
tl_x = np.minimum(tlbr[:, 0], tlbr[:, 2])
tl_y = np.minimum(tlbr[:, 1], tlbr[:, 3])
br_x = np.maximum(tlbr[:, 0], tlbr[:, 2])
br_y = np.maximum(tlbr[:, 1], tlbr[:, 3])
tlbr[:, 0] = tl_x * scale
tlbr[:, 1] = tl_y * scale
tlbr[:, 2] = br_x * scale
tlbr[:, 3] = br_y * scale
boxes = torch.from_numpy(tlbr)
return boxes