[Fix] Fix Coco-stuff164k on BiSeNetV1 config error (#1893)

configs/bisenetv1/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py

@@ -3,6 +3,7 @@ _base_ = [
     '../_base_/datasets/coco-stuff164k.py', '../_base_/default_runtime.py',
     '../_base_/schedules/schedule_160k.py'
 ]
+norm_cfg = dict(type='SyncBN', requires_grad=True)
 model = dict(
     backbone=dict(
         context_channels=(512, 1024, 2048),
@@ -11,8 +12,30 @@ model = dict(
         backbone_cfg=dict(type='ResNet', depth=101)),
     decode_head=dict(in_channels=1024, channels=1024, num_classes=171),
     auxiliary_head=[
-        dict(in_channels=512, channels=256, num_classes=171),
+        dict(
-        dict(in_channels=512, channels=256, num_classes=171),
+            type='FCNHead',
+            in_channels=512,
+            channels=256,
+            num_convs=1,
+            num_classes=171,
+            in_index=1,
+            norm_cfg=norm_cfg,
+            concat_input=False,
+            align_corners=False,
+            loss_decode=dict(
+                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
+        dict(
+            type='FCNHead',
+            in_channels=512,
+            channels=256,
+            num_convs=1,
+            num_classes=171,
+            in_index=2,
+            norm_cfg=norm_cfg,
+            concat_input=False,
+            align_corners=False,
+            loss_decode=dict(
+                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
     ])
 lr_config = dict(warmup='linear', warmup_iters=1000)
 optimizer = dict(lr=0.005)

configs/bisenetv1/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py

@@ -3,11 +3,34 @@ _base_ = [
     '../_base_/datasets/coco-stuff164k.py', '../_base_/default_runtime.py',
     '../_base_/schedules/schedule_160k.py'
 ]
+norm_cfg = dict(type='SyncBN', requires_grad=True)
 model = dict(
     decode_head=dict(num_classes=171),
     auxiliary_head=[
-        dict(num_classes=171),
+        dict(
-        dict(num_classes=171),
+            type='FCNHead',
+            in_channels=128,
+            channels=64,
+            num_convs=1,
+            num_classes=171,
+            in_index=1,
+            norm_cfg=norm_cfg,
+            concat_input=False,
+            align_corners=False,
+            loss_decode=dict(
+                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
+        dict(
+            type='FCNHead',
+            in_channels=128,
+            channels=64,
+            num_convs=1,
+            num_classes=171,
+            in_index=2,
+            norm_cfg=norm_cfg,
+            concat_input=False,
+            align_corners=False,
+            loss_decode=dict(
+                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
     ])
 lr_config = dict(warmup='linear', warmup_iters=1000)
 optimizer = dict(lr=0.005)

configs/bisenetv1/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py

@@ -3,6 +3,7 @@ _base_ = [
     '../_base_/datasets/coco-stuff164k.py', '../_base_/default_runtime.py',
     '../_base_/schedules/schedule_160k.py'
 ]
+norm_cfg = dict(type='SyncBN', requires_grad=True)
 model = dict(
     backbone=dict(
         context_channels=(512, 1024, 2048),
@@ -11,8 +12,30 @@ model = dict(
         backbone_cfg=dict(type='ResNet', depth=50)),
     decode_head=dict(in_channels=1024, channels=1024, num_classes=171),
     auxiliary_head=[
-        dict(in_channels=512, channels=256, num_classes=171),
+        dict(
-        dict(in_channels=512, channels=256, num_classes=171),
+            type='FCNHead',
+            in_channels=512,
+            channels=256,
+            num_convs=1,
+            num_classes=171,
+            in_index=1,
+            norm_cfg=norm_cfg,
+            concat_input=False,
+            align_corners=False,
+            loss_decode=dict(
+                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
+        dict(
+            type='FCNHead',
+            in_channels=512,
+            channels=256,
+            num_convs=1,
+            num_classes=171,
+            in_index=2,
+            norm_cfg=norm_cfg,
+            concat_input=False,
+            align_corners=False,
+            loss_decode=dict(
+                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
     ])
 lr_config = dict(warmup='linear', warmup_iters=1000)
 optimizer = dict(lr=0.005)