remove unused

Author: kwea123

models/modules.py

@@ -13,17 +13,6 @@ def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, pad=1, no
     def forward(self, x):
         return self.bn(self.conv(x))
 
-
-class ConvBn(nn.Module):
-    def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, pad=1, norm_act=InPlaceABN):
-        super(ConvBn, self).__init__()
-        self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride=stride, padding=pad, bias=False)
-        self.bn = norm_act(out_channels, activation='identity')
-
-    def forward(self, x):
-        return self.bn(self.conv(x))
-
-
 class ConvBnReLU3D(nn.Module):
     def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, pad=1, norm_act=InPlaceABN):
         super(ConvBnReLU3D, self).__init__()
@@ -33,16 +22,6 @@ def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, pad=1, no
     def forward(self, x):
         return self.bn(self.conv(x))
 
-
-class ConvBn3D(nn.Module):
-    def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, pad=1, norm_act=InPlaceABN):
-        super(ConvBn3D, self).__init__()
-        self.conv = nn.Conv3d(in_channels, out_channels, kernel_size, stride=stride, padding=pad, bias=False)
-        self.bn = norm_act(out_channels, activation='identity')
-
-    def forward(self, x):
-        return self.bn(self.conv(x))
-
 def homo_warp(src_feat, src_proj, ref_proj_inv, depth_values):
     # src_feat: (B, C, H, W)
     # src_proj: (B, 4, 4)

models/mvsnet.py

@@ -67,20 +67,6 @@ def forward(self, x):
         x = self.prob(x)
         return x
 
-class RefineNet(nn.Module):
-    def __init__(self):
-        super(RefineNet, self).__init__()
-        self.conv1 = ConvBnReLU(4, 32)
-        self.conv2 = ConvBnReLU(32, 32)
-        self.conv3 = ConvBnReLU(32, 32)
-        self.res = ConvBnReLU(32, 1)
-
-    def forward(self, img, depth_init):
-        concat = torch.cat((img, depth_init), dim=1)
-        depth_residual = self.res(self.conv3(self.conv2(self.conv1(concat))))
-        depth_refined = depth_init + depth_residual
-        return depth_refined
-
 class MVSNet(nn.Module):
     def __init__(self, norm_act=InPlaceABN):
         super(MVSNet, self).__init__()

test.ipynb

@@ -180,14 +180,14 @@ def val_dataloader(self):
     hparams = get_opts()
     system = MVSSystem(hparams)
     checkpoint_callback = ModelCheckpoint(filepath=os.path.join('ckpts', 
-                                                   f'{hparams.exp_name}'),
+                                                   hparams.exp_name),
                                           monitor='val/loss',
                                           mode='min',
                                           save_top_k=1,)
 
     logger = TestTubeLogger(
         save_dir="logs",
-        name=f'{hparams.exp_name}',
+        name=hparams.exp_name,
         debug=False,
         create_git_tag=False
     )