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+Collections:
+- Name: gcnet
+  Metadata:
+    Training Data:
+    - Cityscapes
+    - ADE20K
+    - Pascal VOC 2012 + Aug
+  Paper:
+    URL: https://arxiv.org/abs/1904.11492
+    Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond'
+  README: configs/gcnet/README.md
+  Code:
+    URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10
+    Version: v0.17.0
+  Converted From:
+    Code: https://github.com/xvjiarui/GCNet
+Models:
+- Name: gcnet_r50-d8_512x1024_40k_cityscapes
+  In Collection: gcnet
+  Metadata:
+    backbone: R-50-D8
+    crop size: (512,1024)
+    lr schd: 40000
+    inference time (ms/im):
+    - value: 254.45
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP32
+      resolution: (512,1024)
+    Training Memory (GB): 5.8
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 77.69
+      mIoU(ms+flip): 78.56
+  Config: configs/gcnet/gcnet_r50-d8_512x1024_40k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x1024_40k_cityscapes/gcnet_r50-d8_512x1024_40k_cityscapes_20200618_074436-4b0fd17b.pth
+- Name: gcnet_r101-d8_512x1024_40k_cityscapes
+  In Collection: gcnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,1024)
+    lr schd: 40000
+    inference time (ms/im):
+    - value: 383.14
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP32
+      resolution: (512,1024)
+    Training Memory (GB): 9.2
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 78.28
+      mIoU(ms+flip): 79.34
+  Config: configs/gcnet/gcnet_r101-d8_512x1024_40k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x1024_40k_cityscapes/gcnet_r101-d8_512x1024_40k_cityscapes_20200618_074436-5e62567f.pth
+- Name: gcnet_r50-d8_769x769_40k_cityscapes
+  In Collection: gcnet
+  Metadata:
+    backbone: R-50-D8
+    crop size: (769,769)
+    lr schd: 40000
+    inference time (ms/im):
+    - value: 598.8
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP32
+      resolution: (769,769)
+    Training Memory (GB): 6.5
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 78.12
+      mIoU(ms+flip): 80.09
+  Config: configs/gcnet/gcnet_r50-d8_769x769_40k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_769x769_40k_cityscapes/gcnet_r50-d8_769x769_40k_cityscapes_20200618_182814-a26f4471.pth
+- Name: gcnet_r101-d8_769x769_40k_cityscapes
+  In Collection: gcnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (769,769)
+    lr schd: 40000
+    inference time (ms/im):
+    - value: 884.96
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP32
+      resolution: (769,769)
+    Training Memory (GB): 10.5
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 78.95
+      mIoU(ms+flip): 80.71
+  Config: configs/gcnet/gcnet_r101-d8_769x769_40k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_769x769_40k_cityscapes/gcnet_r101-d8_769x769_40k_cityscapes_20200619_092550-ca4f0a84.pth
+- Name: gcnet_r50-d8_512x1024_80k_cityscapes
+  In Collection: gcnet
+  Metadata:
+    backbone: R-50-D8
+    crop size: (512,1024)
+    lr schd: 80000
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 78.48
+      mIoU(ms+flip): 80.01
+  Config: configs/gcnet/gcnet_r50-d8_512x1024_80k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x1024_80k_cityscapes/gcnet_r50-d8_512x1024_80k_cityscapes_20200618_074450-ef8f069b.pth
+- Name: gcnet_r101-d8_512x1024_80k_cityscapes
+  In Collection: gcnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,1024)
+    lr schd: 80000
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 79.03
+      mIoU(ms+flip): 79.84
+  Config: configs/gcnet/gcnet_r101-d8_512x1024_80k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x1024_80k_cityscapes/gcnet_r101-d8_512x1024_80k_cityscapes_20200618_074450-778ebf69.pth
+- Name: gcnet_r50-d8_769x769_80k_cityscapes
+  In Collection: gcnet
+  Metadata:
+    backbone: R-50-D8
+    crop size: (769,769)
+    lr schd: 80000
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 78.68
+      mIoU(ms+flip): 80.66
+  Config: configs/gcnet/gcnet_r50-d8_769x769_80k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_769x769_80k_cityscapes/gcnet_r50-d8_769x769_80k_cityscapes_20200619_092516-4839565b.pth
+- Name: gcnet_r101-d8_769x769_80k_cityscapes
+  In Collection: gcnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (769,769)
+    lr schd: 80000
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 79.18
+      mIoU(ms+flip): 80.71
+  Config: configs/gcnet/gcnet_r101-d8_769x769_80k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_769x769_80k_cityscapes/gcnet_r101-d8_769x769_80k_cityscapes_20200619_092628-8e043423.pth
+- Name: gcnet_r50-d8_512x512_80k_ade20k
+  In Collection: gcnet
+  Metadata:
+    backbone: R-50-D8
+    crop size: (512,512)
+    lr schd: 80000
+    inference time (ms/im):
+    - value: 42.77
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP32
+      resolution: (512,512)
+    Training Memory (GB): 8.5
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: ADE20K
+    Metrics:
+      mIoU: 41.47
+      mIoU(ms+flip): 42.85
+  Config: configs/gcnet/gcnet_r50-d8_512x512_80k_ade20k.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_80k_ade20k/gcnet_r50-d8_512x512_80k_ade20k_20200614_185146-91a6da41.pth
+- Name: gcnet_r101-d8_512x512_80k_ade20k
+  In Collection: gcnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,512)
+    lr schd: 80000
+    inference time (ms/im):
+    - value: 65.79
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP32
+      resolution: (512,512)
+    Training Memory (GB): 12.0
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: ADE20K
+    Metrics:
+      mIoU: 42.82
+      mIoU(ms+flip): 44.54
+  Config: configs/gcnet/gcnet_r101-d8_512x512_80k_ade20k.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_80k_ade20k/gcnet_r101-d8_512x512_80k_ade20k_20200615_020811-c3fcb6dd.pth
+- Name: gcnet_r50-d8_512x512_160k_ade20k
+  In Collection: gcnet
+  Metadata:
+    backbone: R-50-D8
+    crop size: (512,512)
+    lr schd: 160000
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: ADE20K
+    Metrics:
+      mIoU: 42.37
+      mIoU(ms+flip): 43.52
+  Config: configs/gcnet/gcnet_r50-d8_512x512_160k_ade20k.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_160k_ade20k/gcnet_r50-d8_512x512_160k_ade20k_20200615_224122-d95f3e1f.pth
+- Name: gcnet_r101-d8_512x512_160k_ade20k
+  In Collection: gcnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,512)
+    lr schd: 160000
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: ADE20K
+    Metrics:
+      mIoU: 43.69
+      mIoU(ms+flip): 45.21
+  Config: configs/gcnet/gcnet_r101-d8_512x512_160k_ade20k.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_160k_ade20k/gcnet_r101-d8_512x512_160k_ade20k_20200615_225406-615528d7.pth
+- Name: gcnet_r50-d8_512x512_20k_voc12aug
+  In Collection: gcnet
+  Metadata:
+    backbone: R-50-D8
+    crop size: (512,512)
+    lr schd: 20000
+    inference time (ms/im):
+    - value: 42.83
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP32
+      resolution: (512,512)
+    Training Memory (GB): 5.8
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Pascal VOC 2012 + Aug
+    Metrics:
+      mIoU: 76.42
+      mIoU(ms+flip): 77.51
+  Config: configs/gcnet/gcnet_r50-d8_512x512_20k_voc12aug.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_20k_voc12aug/gcnet_r50-d8_512x512_20k_voc12aug_20200617_165701-3cbfdab1.pth
+- Name: gcnet_r101-d8_512x512_20k_voc12aug
+  In Collection: gcnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,512)
+    lr schd: 20000
+    inference time (ms/im):
+    - value: 67.57
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP32
+      resolution: (512,512)
+    Training Memory (GB): 9.2
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Pascal VOC 2012 + Aug
+    Metrics:
+      mIoU: 77.41
+      mIoU(ms+flip): 78.56
+  Config: configs/gcnet/gcnet_r101-d8_512x512_20k_voc12aug.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_20k_voc12aug/gcnet_r101-d8_512x512_20k_voc12aug_20200617_165713-6c720aa9.pth
+- Name: gcnet_r50-d8_512x512_40k_voc12aug
+  In Collection: gcnet
+  Metadata:
+    backbone: R-50-D8
+    crop size: (512,512)
+    lr schd: 40000
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Pascal VOC 2012 + Aug
+    Metrics:
+      mIoU: 76.24
+      mIoU(ms+flip): 77.63
+  Config: configs/gcnet/gcnet_r50-d8_512x512_40k_voc12aug.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_40k_voc12aug/gcnet_r50-d8_512x512_40k_voc12aug_20200613_195105-9797336d.pth
+- Name: gcnet_r101-d8_512x512_40k_voc12aug
+  In Collection: gcnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,512)
+    lr schd: 40000
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Pascal VOC 2012 + Aug
+    Metrics:
+      mIoU: 77.84
+      mIoU(ms+flip): 78.59
+  Config: configs/gcnet/gcnet_r101-d8_512x512_40k_voc12aug.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_40k_voc12aug/gcnet_r101-d8_512x512_40k_voc12aug_20200613_185806-1e38208d.pth