图像去雾处理python代码.rar

def default_conv(in_channels, out_channels, kernel_size, bias=True): return nn.Conv2d(in_channels, out_channels, kernel_size,padding=(kernel_size//2), bias=bias) class PALayer(nn.Module): def __init__(self, channel): super(PALayer, self).__init__() self.pa = nn.Sequential( nn.Conv2d(channel, channel // 8, 1, padding=0, bias=True), nn.ReLU(inplace=True), nn.Conv2d(channel // 8, 1, 1, padding=0, bias=True), nn.Sigmoid() ) def forward(self, x): y = self.pa(x) return x * y class CALayer(nn.Module): def __init__(self, channel): super(CALayer, self).__init__() self.avg_pool = nn.AdaptiveAvgPool2d(1) self.ca = nn.Sequential( nn.Conv2d(channel, channel // 8, 1, padding=0, bias=True), nn.ReLU(inplace=True), nn.Conv2d(channel // 8, channel, 1, padding=0, bias=True), nn.Sigmoid() ) def forward(self, x): y = self.avg_pool(x) y = self.ca(y) return x * y class Block(nn.Module): def __init__(self, conv, dim, kernel_size,): super(Block, self).__init__() self.conv1=conv(dim, dim, kernel_size, bias=True) self.act1=nn.ReLU(inplace=True) self.conv2=conv(dim,dim,kernel_size,bias=True) self.calayer=CALayer(dim) self.palayer=PALayer(dim) def forward(self, x): res=self.act1(self.conv1(x)) res=res+x res=self.conv2(res) res=self.calayer(res) res=self.palayer(res) res += x return res