mmagic.models.editors.fba.fba_decoder

Module Contents

Classes

FBADecoder

Decoder for FBA matting.

class mmagic.models.editors.fba.fba_decoder.FBADecoder(pool_scales, in_channels, channels, conv_cfg=None, norm_cfg=dict(type='BN'), act_cfg=dict(type='ReLU'), align_corners=False)

Bases: torch.nn.Module

Decoder for FBA matting.

Parameters

• pool_scales (tuple[int]) – Pooling scales used in

• Module. (Pooling Pyramid) –

• in_channels (int) – Input channels.

• channels (int) – Channels after modules, before conv_seg.

• conv_cfg (dict|None) – Config of conv layers.

• norm_cfg (dict|None) – Config of norm layers.

• act_cfg (dict) – Config of activation layers.

• align_corners (bool) – align_corners argument of F.interpolate.

init_weights(pretrained=None)

Init weights for the model.

Parameters

pretrained (str, optional) – Path for pretrained weights. If given None, pretrained weights will not be loaded. Defaults to None.

forward(inputs)

Forward function.

Parameters

inputs (dict) – Output dict of FbaEncoder.

Returns

Predicted alpha, fg and bg of the current batch.

Return type

tuple(Tensor)