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mmedit.models.editors.nafnet.nafbaseline_net

Module Contents

Classes

NAFBaseline

The original version of Baseline model in "Simple Baseline for Image

NAFBaselineLocal

The original version of Baseline model in "Simple Baseline for Image

BaselineBlock

Baseline's Block in paper.

class mmedit.models.editors.nafnet.nafbaseline_net.NAFBaseline(img_channel=3, mid_channels=16, middle_blk_num=1, enc_blk_nums=[1, 1, 1, 28], dec_blk_nums=[1, 1, 1, 1], dw_expand=1, ffn_expand=2)[源代码]

Bases: mmengine.model.BaseModule

The original version of Baseline model in “Simple Baseline for Image Restoration”.

参数
  • img_channels (int) – Channel number of inputs.

  • mid_channels (int) – Channel number of intermediate features.

  • middle_blk_num (int) – Number of middle blocks.

  • enc_blk_nums (List of int) – Number of blocks for each encoder.

  • dec_blk_nums (List of int) – Number of blocks for each decoder.

forward(inp)[源代码]

Forward function.

参数

inp – input tensor image with (B, C, H, W) shape

check_image_size(x)[源代码]

Check image size and pad images so that it has enough dimension do downsample.

参数

x – input tensor image with (B, C, H, W) shape.

class mmedit.models.editors.nafnet.nafbaseline_net.NAFBaselineLocal(*args, train_size=(1, 3, 256, 256), fast_imp=False, **kwargs)[源代码]

Bases: mmedit.models.editors.nafnet.naf_avgpool2d.Local_Base, NAFBaseline

The original version of Baseline model in “Simple Baseline for Image Restoration”.

参数
  • img_channels (int) – Channel number of inputs.

  • mid_channels (int) – Channel number of intermediate features.

  • middle_blk_num (int) – Number of middle blocks.

  • enc_blk_nums (List of int) – Number of blocks for each encoder.

  • dec_blk_nums (L`ist of int) – Number of blocks for each decoder.

class mmedit.models.editors.nafnet.nafbaseline_net.BaselineBlock(in_channels, DW_Expand=1, FFN_Expand=2, drop_out_rate=0.0)[源代码]

Bases: mmengine.model.BaseModule

Baseline’s Block in paper.

参数
  • in_channels (int) – number of channels

  • DW_Expand (int) – channel expansion factor for part 1

  • FFN_Expand (int) – channel expansion factor for part 2

  • drop_out_rate (float) – drop out ratio

forward(inp)[源代码]

Forward Function.

参数

inp – input tensor image

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