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import torch
import torch.nn as nn
from engine.BiRefNet.config import Config
from engine.BiRefNet.models.modules.aspp import ASPP, ASPPDeformable
config = Config()
class BasicDecBlk(nn.Module):
def __init__(self, in_channels=64, out_channels=64, inter_channels=64):
super(BasicDecBlk, self).__init__()
inter_channels = in_channels // 4 if config.dec_channels_inter == "adap" else 64
self.conv_in = nn.Conv2d(in_channels, inter_channels, 3, 1, padding=1)
self.relu_in = nn.ReLU(inplace=True)
if config.dec_att == "ASPP":
self.dec_att = ASPP(in_channels=inter_channels)
elif config.dec_att == "ASPPDeformable":
self.dec_att = ASPPDeformable(in_channels=inter_channels)
self.conv_out = nn.Conv2d(inter_channels, out_channels, 3, 1, padding=1)
self.bn_in = (
nn.BatchNorm2d(inter_channels) if config.batch_size > 1 else nn.Identity()
)
self.bn_out = (
nn.BatchNorm2d(out_channels) if config.batch_size > 1 else nn.Identity()
)
def forward(self, x):
x = self.conv_in(x)
x = self.bn_in(x)
x = self.relu_in(x)
if hasattr(self, "dec_att"):
x = self.dec_att(x)
x = self.conv_out(x)
x = self.bn_out(x)
return x
class ResBlk(nn.Module):
def __init__(self, in_channels=64, out_channels=None, inter_channels=64):
super(ResBlk, self).__init__()
if out_channels is None:
out_channels = in_channels
inter_channels = in_channels // 4 if config.dec_channels_inter == "adap" else 64
self.conv_in = nn.Conv2d(in_channels, inter_channels, 3, 1, padding=1)
self.bn_in = (
nn.BatchNorm2d(inter_channels) if config.batch_size > 1 else nn.Identity()
)
self.relu_in = nn.ReLU(inplace=True)
if config.dec_att == "ASPP":
self.dec_att = ASPP(in_channels=inter_channels)
elif config.dec_att == "ASPPDeformable":
self.dec_att = ASPPDeformable(in_channels=inter_channels)
self.conv_out = nn.Conv2d(inter_channels, out_channels, 3, 1, padding=1)
self.bn_out = (
nn.BatchNorm2d(out_channels) if config.batch_size > 1 else nn.Identity()
)
self.conv_resi = nn.Conv2d(in_channels, out_channels, 1, 1, 0)
def forward(self, x):
_x = self.conv_resi(x)
x = self.conv_in(x)
x = self.bn_in(x)
x = self.relu_in(x)
if hasattr(self, "dec_att"):
x = self.dec_att(x)
x = self.conv_out(x)
x = self.bn_out(x)
return x + _x
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