Models:

  - Name: fcn_r101-d8_512x1024_80k_fp16_cityscapes
    In Collection: FCN
    Metadata:
      inference time (ms/im):
        - value: 115.74
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 76.80
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes/fcn_r101-d8_512x1024_80k_fp16_cityscapes-50245227.pth
    Config: configs/fcn/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py



  - Name: pspnet_r101-d8_512x1024_80k_fp16_cityscapes
    In Collection: PSPNet
    Metadata:
      inference time (ms/im):
        - value: 114.03
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 79.46
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes/pspnet_r101-d8_512x1024_80k_fp16_cityscapes-ade37931.pth
    Config: configs/pspnet/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py



  - Name: deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes
    In Collection: DeepLabV3
    Metadata:
      inference time (ms/im):
        - value: 259.07
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 80.48
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes-bc86dc84.pth
    Config: configs/deeplabv3/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py



  - Name: deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 127.06
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 80.46
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes-cc58bc8d.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py