Collections:
  - Name: CGNet
    Metadata:
      Training Data:
        - Cityscapes

Models:

  - Name: cgnet_680x680_60k_cityscapes
    In Collection: CGNet
    Metadata:
      inference time (ms/im):
        - value: 32.78
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 65.63
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/cgnet/cgnet_680x680_60k_cityscapes/cgnet_680x680_60k_cityscapes_20201101_110253-4c0b2f2d.pth
    Config: configs/cgnet/cgnet_680x680_60k_cityscapes.py



  - Name: cgnet_512x1024_60k_cityscapes
    In Collection: CGNet
    Metadata:
      inference time (ms/im):
        - value: 32.11
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 68.27
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/cgnet/cgnet_512x1024_60k_cityscapes/cgnet_512x1024_60k_cityscapes_20201101_110254-124ea03b.pth
    Config: configs/cgnet/cgnet_512x1024_60k_cityscapes.py