Fix fastscnn resize problems. (#82)

* Fix fast_scnn resize problems

* Fix fast_scnn resize problems 1

* Fix fast_scnn resize problems 2

* test for pascal voc

configs/fastscnn/fast_scnn_4x8_80k_lr0.12_pascal.py

@@ -0,0 +1,70 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/pascal_voc12.py',
+    '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
+]
+
+# Re-config the data sampler.
+data = dict(samples_per_gpu=8, workers_per_gpu=4)
+
+# Re-config the optimizer.
+optimizer = dict(type='SGD', lr=0.12, momentum=0.9, weight_decay=4e-5)
+
+# update num_classes of the segmentor.
+# model settings
+norm_cfg = dict(type='SyncBN', requires_grad=True, momentum=0.01)
+model = dict(
+    type='EncoderDecoder',
+    backbone=dict(
+        type='FastSCNN',
+        downsample_dw_channels=(32, 48),
+        global_in_channels=64,
+        global_block_channels=(64, 96, 128),
+        global_block_strides=(2, 2, 1),
+        global_out_channels=128,
+        higher_in_channels=64,
+        lower_in_channels=128,
+        fusion_out_channels=128,
+        out_indices=(0, 1, 2),
+        norm_cfg=norm_cfg,
+        align_corners=False),
+    decode_head=dict(
+        type='DepthwiseSeparableFCNHead',
+        in_channels=128,
+        channels=128,
+        concat_input=False,
+        num_classes=21,
+        in_index=-1,
+        norm_cfg=norm_cfg,
+        align_corners=False,
+        loss_decode=dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.)),
+    auxiliary_head=[
+        dict(
+            type='FCNHead',
+            in_channels=128,
+            channels=32,
+            num_convs=1,
+            num_classes=21,
+            in_index=-2,
+            norm_cfg=norm_cfg,
+            concat_input=False,
+            align_corners=False,
+            loss_decode=dict(
+                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
+        dict(
+            type='FCNHead',
+            in_channels=64,
+            channels=32,
+            num_convs=1,
+            num_classes=21,
+            in_index=-3,
+            norm_cfg=norm_cfg,
+            concat_input=False,
+            align_corners=False,
+            loss_decode=dict(
+                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
+    ])
+
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')

mmseg/__init__.py

@@ -3,7 +3,7 @@ import mmcv
 from .version import __version__, version_info
 
 MMCV_MIN = '1.0.5'
-MMCV_MAX = '1.0.5'
+MMCV_MAX = '1.1.0'
 
 
 def digit_version(version_str):

mmseg/models/backbones/fast_scnn.py

@@ -186,9 +186,6 @@ class FeatureFusionModule(nn.Module):
         lower_in_channels (int): Number of input channels of the
             lower-resolution branch.
         out_channels (int): Number of output channels.
-        scale_factor (int): Scale factor applied to the lower-res input.
-            Should be coherent with the downsampling factor determined
-            by the GFE module.
         conv_cfg (dict | None): Config of conv layers. Default: None
         norm_cfg (dict | None): Config of norm layers. Default:
             dict(type='BN')
@@ -202,13 +199,11 @@ class FeatureFusionModule(nn.Module):
                  higher_in_channels,
                  lower_in_channels,
                  out_channels,
-                 scale_factor,
                  conv_cfg=None,
                  norm_cfg=dict(type='BN'),
                  act_cfg=dict(type='ReLU'),
                  align_corners=False):
         super(FeatureFusionModule, self).__init__()
-        self.scale_factor = scale_factor
         self.conv_cfg = conv_cfg
         self.norm_cfg = norm_cfg
         self.act_cfg = act_cfg
@@ -239,7 +234,7 @@ class FeatureFusionModule(nn.Module):
     def forward(self, higher_res_feature, lower_res_feature):
         lower_res_feature = resize(
             lower_res_feature,
-            scale_factor=self.scale_factor,
+            size=higher_res_feature.size()[2:],
             mode='bilinear',
             align_corners=self.align_corners)
         lower_res_feature = self.dwconv(lower_res_feature)
@@ -321,11 +316,6 @@ class FastSCNN(nn.Module):
             raise AssertionError('Global Output Channels must be the same \
                                 with Lower Input Channels!')
 
-        # Calculate scale factor used in FFM.
-        self.scale_factor = 1
-        for factor in global_block_strides:
-            self.scale_factor *= factor
-
         self.in_channels = in_channels
         self.downsample_dw_channels1 = downsample_dw_channels[0]
         self.downsample_dw_channels2 = downsample_dw_channels[1]
@@ -361,7 +351,6 @@ class FastSCNN(nn.Module):
             higher_in_channels,
             lower_in_channels,
             fusion_out_channels,
-            scale_factor=self.scale_factor,
             conv_cfg=self.conv_cfg,
             norm_cfg=self.norm_cfg,
             act_cfg=self.act_cfg,