Shortcuts

mmedit.models.editors.deepfillv1.deepfill_encoder

Module Contents

Classes

DeepFillEncoder

Encoder used in DeepFill model.

class mmedit.models.editors.deepfillv1.deepfill_encoder.DeepFillEncoder(in_channels=5, conv_type='conv', norm_cfg=None, act_cfg=dict(type='ELU'), encoder_type='stage1', channel_factor=1.0, **kwargs)[source]

Bases: mmengine.model.BaseModule

Encoder used in DeepFill model.

This implementation follows: Generative Image Inpainting with Contextual Attention

Parameters
  • in_channels (int) – The number of input channels. Default: 5.

  • conv_type (str) – The type of conv module. In DeepFillv1 model, the conv_type should be ‘conv’. In DeepFillv2 model, the conv_type should be ‘gated_conv’.

  • norm_cfg (dict) – Config dict to build norm layer. Default: None.

  • act_cfg (dict) – Config dict for activation layer, “elu” by default.

  • encoder_type (str) – Type of the encoder. Should be one of [‘stage1’, ‘stage2_conv’, ‘stage2_attention’]. Default: ‘stage1’.

  • channel_factor (float) – The scale factor for channel size. Default: 1.

  • kwargs (keyword arguments) –

_conv_type[source]
forward(x)[source]

Forward Function.

Parameters

x (torch.Tensor) – Input tensor with shape of (n, c, h, w).

Returns

Output tensor with shape of (n, c, h’, w’).

Return type

torch.Tensor

Read the Docs v: latest
Versions
master
latest
stable
zyh-re-docs
zyh-doc-notfound-extend
zyh-api-rendering
Downloads
pdf
epub
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.