[Fix] Fix correct num_classes of HRNet in LoveDA dataset #1136

open-mmlab · Dec 14, 2021 · e9c41c3 · e9c41c3
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Showing 3 changed files with 19 additions and 18 deletions.
diff --git a/configs/hrnet/README.md b/configs/hrnet/README.md
@@ -89,6 +89,6 @@ High-resolution representations are essential for position-sensitive vision prob
 
 | Method     | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) |  mIoU | mIoU(ms+flip) | config                                                                                                                                 | download                                                                                                                                                                                                                                                                                                                                                                                   |
 | ---------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | -------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| FCN | HRNetV2p-W18-Small  | 512x512   |   80000 | 1.72      | 30.07             | 49.3 |         49.23 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18s_512x512_80k_loveda.py)  | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211105_180825-41dcc5dc.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211105_180825.log.json)     |
-| FCN | HRNetV2p-W18  | 512x512   |   80000 | 2.90      | 16.77             | 50.87 |         51.24 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18_512x512_80k_loveda.py)  | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211105_165542-95be4d2b.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211105_165542.log.json)     |
-| FCN | HRNetV2p-W48 | 512x512   |   80000 | 6.25       | 9.09          | 51.04 |         51.12 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr48_512x512_80k_loveda.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211105_131509-f07e47c6.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211105_131509.log.json) |
+| FCN | HRNetV2p-W18-Small  | 512x512   |   80000 | 1.59      | 24.87             | 49.28 |         49.42 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18s_512x512_80k_loveda.py)  | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228-60a86a7a.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228.log.json)     |
+| FCN | HRNetV2p-W18  | 512x512   |   80000 | 2.76      | 12.92             | 50.81 |         50.95 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18_512x512_80k_loveda.py)  | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952-93d9c3b3.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952.log.json)     |
+| FCN | HRNetV2p-W48 | 512x512   |   80000 | 6.20       | 9.61          | 51.42 |         51.64 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr48_512x512_80k_loveda.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756-67072f55.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756.log.json) |
diff --git a/configs/hrnet/fcn_hr18_512x512_80k_loveda.py b/configs/hrnet/fcn_hr18_512x512_80k_loveda.py
@@ -2,3 +2,4 @@
     '../_base_/models/fcn_hr18.py', '../_base_/datasets/loveda.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
 ]
+model = dict(decode_head=dict(num_classes=7))
diff --git a/configs/hrnet/hrnet.yml b/configs/hrnet/hrnet.yml
@@ -455,62 +455,62 @@ Models:
     crop size: (512,512)
     lr schd: 80000
     inference time (ms/im):
-    - value: 33.26
+    - value: 40.21
       hardware: V100
       backend: PyTorch
       batch size: 1
       mode: FP32
       resolution: (512,512)
-    Training Memory (GB): 1.72
+    Training Memory (GB): 1.59
   Results:
   - Task: Semantic Segmentation
     Dataset: LoveDA
     Metrics:
-      mIoU: 49.3
-      mIoU(ms+flip): 49.23
+      mIoU: 49.28
+      mIoU(ms+flip): 49.42
   Config: configs/hrnet/fcn_hr18s_512x512_80k_loveda.py
-  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211105_180825-41dcc5dc.pth
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228-60a86a7a.pth
 - Name: fcn_hr18_512x512_80k_loveda
   In Collection: hrnet
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,512)
     lr schd: 80000
     inference time (ms/im):
-    - value: 59.63
+    - value: 77.4
       hardware: V100
       backend: PyTorch
       batch size: 1
       mode: FP32
       resolution: (512,512)
-    Training Memory (GB): 2.9
+    Training Memory (GB): 2.76
   Results:
   - Task: Semantic Segmentation
     Dataset: LoveDA
     Metrics:
-      mIoU: 50.87
-      mIoU(ms+flip): 51.24
+      mIoU: 50.81
+      mIoU(ms+flip): 50.95
   Config: configs/hrnet/fcn_hr18_512x512_80k_loveda.py
-  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211105_165542-95be4d2b.pth
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952-93d9c3b3.pth
 - Name: fcn_hr48_512x512_80k_loveda
   In Collection: hrnet
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,512)
     lr schd: 80000
     inference time (ms/im):
-    - value: 110.01
+    - value: 104.06
       hardware: V100
       backend: PyTorch
       batch size: 1
       mode: FP32
       resolution: (512,512)
-    Training Memory (GB): 6.25
+    Training Memory (GB): 6.2
   Results:
   - Task: Semantic Segmentation
     Dataset: LoveDA
     Metrics:
-      mIoU: 51.04
-      mIoU(ms+flip): 51.12
+      mIoU: 51.42
+      mIoU(ms+flip): 51.64
   Config: configs/hrnet/fcn_hr48_512x512_80k_loveda.py
-  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211105_131509-f07e47c6.pth
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756-67072f55.pth