(self,
extra,
in_channels=3,
conv_cfg=None,
norm_cfg=dict(type='BN'),
norm_eval=True,
with_cp=False,
num_joints=24,
zero_init_residual=False,
multiscale_output=True,
pretrained=None,
init_cfg=None)
| 650 | class PoseHighResolutionNetExpose(PoseHighResolutionNet): |
| 651 | """HRNet backbone for expose.""" |
| 652 | def __init__(self, |
| 653 | extra, |
| 654 | in_channels=3, |
| 655 | conv_cfg=None, |
| 656 | norm_cfg=dict(type='BN'), |
| 657 | norm_eval=True, |
| 658 | with_cp=False, |
| 659 | num_joints=24, |
| 660 | zero_init_residual=False, |
| 661 | multiscale_output=True, |
| 662 | pretrained=None, |
| 663 | init_cfg=None): |
| 664 | super().__init__(extra, in_channels, conv_cfg, norm_cfg, norm_eval, |
| 665 | with_cp, num_joints, zero_init_residual, |
| 666 | multiscale_output, pretrained, init_cfg) |
| 667 | in_dims = (2**2 * self.stage2_cfg['num_channels'][-1] + |
| 668 | 2**1 * self.stage3_cfg['num_channels'][-1] + |
| 669 | self.stage4_cfg['num_channels'][-1]) |
| 670 | self.conv_layers = self._make_conv_layer(in_channels=in_dims, |
| 671 | num_layers=5) |
| 672 | self.subsample_3 = self._make_subsample_layer( |
| 673 | in_channels=self.stage2_cfg['num_channels'][-1], num_layers=2) |
| 674 | self.subsample_2 = self._make_subsample_layer( |
| 675 | in_channels=self.stage3_cfg['num_channels'][-1], num_layers=1) |
| 676 | |
| 677 | def _make_conv_layer(self, |
| 678 | in_channels=2048, |
nothing calls this directly
no test coverage detected