def __call__(self, xs):
"""Compute loc and conf from feature maps
This method computes :obj:`mb_locs` and :obj:`mb_confs`
from given feature maps.
Args:
xs (iterable of chainer.Variable): An iterable of feature maps.
The number of feature maps must be same as the number of
:obj:`aspect_ratios`.
Returns:
tuple of chainer.Variable:
This method returns two :obj:`chainer.Variable`: :obj:`mb_locs` and
:obj:`mb_confs`.
* **mb_locs**: A variable of float arrays of shape \
:math:`(B, K, 4)`, \
where :math:`B` is the number of samples in the batch and \
:math:`K` is the number of default bounding boxes.
* **mb_confs**: A variable of float arrays of shape \
:math:`(B, K, n\_fg\_class + 1)`.
"""
mb_locs = list()
mb_confs = list()
for i, x in enumerate(xs):
mb_loc = self.loc[i](x)
mb_loc = F.transpose(mb_loc, (0, 2, 3, 1))
mb_loc = F.reshape(mb_loc, (mb_loc.shape[0], -1, 4))
mb_locs.append(mb_loc)
mb_conf = self.conf[i](x)
mb_conf = F.transpose(mb_conf, (0, 2, 3, 1))
mb_conf = F.reshape(
mb_conf, (mb_conf.shape[0], -1, self.n_class))
mb_confs.append(mb_conf)
mb_locs = F.concat(mb_locs, axis=1)
mb_confs = F.concat(mb_confs, axis=1)
return mb_locs, mb_confs
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