Collections:
  - Name: DeepLabV3+
    Metadata:
      Training Data:
        - Cityscapes
        - Pascal Context
        - Pascal VOC 2012 + Aug
        - ADE20K

Models:

  - Name: deeplabv3plus_r50-d8_512x1024_40k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 253.81
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 79.61
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes/deeplabv3plus_r50-d8_512x1024_40k_cityscapes_20200605_094610-d222ffcd.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py



  - Name: deeplabv3plus_r101-d8_512x1024_40k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 384.62
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 80.21
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_40k_cityscapes/deeplabv3plus_r101-d8_512x1024_40k_cityscapes_20200605_094614-3769eecf.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_512x1024_40k_cityscapes.py



  - Name: deeplabv3plus_r50-d8_769x769_40k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 581.4
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 78.97
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_769x769_40k_cityscapes/deeplabv3plus_r50-d8_769x769_40k_cityscapes_20200606_114143-1dcb0e3c.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50-d8_769x769_40k_cityscapes.py



  - Name: deeplabv3plus_r101-d8_769x769_40k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 869.57
          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/deeplabv3plus/deeplabv3plus_r101-d8_769x769_40k_cityscapes/deeplabv3plus_r101-d8_769x769_40k_cityscapes_20200606_114304-ff414b9e.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_769x769_40k_cityscapes.py



  - Name: deeplabv3plus_r18-d8_512x1024_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 70.08
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 76.89
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes/deeplabv3plus_r18-d8_512x1024_80k_cityscapes_20201226_080942-cff257fe.pth
    Config: configs/deeplabv3+/deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py



  - Name: deeplabv3plus_r50-d8_512x1024_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 253.81
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 80.09
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes/deeplabv3plus_r50-d8_512x1024_80k_cityscapes_20200606_114049-f9fb496d.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py



  - Name: deeplabv3plus_r101-d8_512x1024_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 384.62
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 80.97
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_cityscapes_20200606_114143-068fcfe9.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py



  - Name: deeplabv3plus_r18-d8_769x769_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 174.22
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 76.26
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes/deeplabv3plus_r18-d8_769x769_80k_cityscapes_20201226_083346-f326e06a.pth
    Config: configs/deeplabv3+/deeplabv3plus_r18-d8_769x769_80k_cityscapes.py



  - Name: deeplabv3plus_r50-d8_769x769_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 581.4
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 79.83
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes/deeplabv3plus_r50-d8_769x769_80k_cityscapes_20200606_210233-0e9dfdc4.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py



  - Name: deeplabv3plus_r101-d8_769x769_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 869.57
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 80.98
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes/deeplabv3plus_r101-d8_769x769_80k_cityscapes_20200607_000405-a7573d20.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_769x769_80k_cityscapes.py



  - Name: deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 133.69
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 79.09
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes/deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes_20200908_005644-cf9ce186.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes.py



  - Name: deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 133.69
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 79.90
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes/deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes_20200908_005644-ee6158e0.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes.py



  - Name: deeplabv3plus_r18b-d8_512x1024_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 66.89
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 75.87
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18b-d8_512x1024_80k_cityscapes/deeplabv3plus_r18b-d8_512x1024_80k_cityscapes_20201226_090828-e451abd9.pth
    Config: configs/deeplabv3+/deeplabv3plus_r18b-d8_512x1024_80k_cityscapes.py



  - Name: deeplabv3plus_r50b-d8_512x1024_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 253.81
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 80.28
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes_20201225_213645-a97e4e43.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes.py



  - Name: deeplabv3plus_r101b-d8_512x1024_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 384.62
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 80.16
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes_20201226_190843-9c3c93a4.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes.py



  - Name: deeplabv3plus_r18b-d8_769x769_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 167.79
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 76.36
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18b-d8_769x769_80k_cityscapes/deeplabv3plus_r18b-d8_769x769_80k_cityscapes_20201226_151312-2c868aff.pth
    Config: configs/deeplabv3+/deeplabv3plus_r18b-d8_769x769_80k_cityscapes.py



  - Name: deeplabv3plus_r50b-d8_769x769_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 581.4
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 79.41
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50b-d8_769x769_80k_cityscapes/deeplabv3plus_r50b-d8_769x769_80k_cityscapes_20201225_224655-8b596d1c.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50b-d8_769x769_80k_cityscapes.py



  - Name: deeplabv3plus_r101b-d8_769x769_80k_cityscapes
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 909.09
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Cityscapes
        Metrics:
          mIoU: 79.88
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101b-d8_769x769_80k_cityscapes/deeplabv3plus_r101b-d8_769x769_80k_cityscapes_20201226_205041-227cdf7c.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py



  - Name: deeplabv3plus_r50-d8_512x512_80k_ade20k
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 47.6
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: ADE20K
        Metrics:
          mIoU: 42.72
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_ade20k/deeplabv3plus_r50-d8_512x512_80k_ade20k_20200614_185028-bf1400d8.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50-d8_512x512_80k_ade20k.py



  - Name: deeplabv3plus_r101-d8_512x512_80k_ade20k
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 70.62
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: ADE20K
        Metrics:
          mIoU: 44.60
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_ade20k/deeplabv3plus_r101-d8_512x512_80k_ade20k_20200615_014139-d5730af7.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_512x512_80k_ade20k.py



  - Name: deeplabv3plus_r50-d8_512x512_160k_ade20k
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 47.6
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: ADE20K
        Metrics:
          mIoU: 43.95
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_160k_ade20k/deeplabv3plus_r50-d8_512x512_160k_ade20k_20200615_124504-6135c7e0.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50-d8_512x512_160k_ade20k.py



  - Name: deeplabv3plus_r101-d8_512x512_160k_ade20k
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 70.62
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: ADE20K
        Metrics:
          mIoU: 45.47
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k/deeplabv3plus_r101-d8_512x512_160k_ade20k_20200615_123232-38ed86bb.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_512x512_160k_ade20k.py



  - Name: deeplabv3plus_r50-d8_512x512_20k_voc12aug
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 47.62
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Pascal VOC 2012 + Aug
        Metrics:
          mIoU: 75.93
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug/deeplabv3plus_r50-d8_512x512_20k_voc12aug_20200617_102323-aad58ef1.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50-d8_512x512_20k_voc12aug.py



  - Name: deeplabv3plus_r101-d8_512x512_20k_voc12aug
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 72.05
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Pascal VOC 2012 + Aug
        Metrics:
          mIoU: 77.22
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_20k_voc12aug/deeplabv3plus_r101-d8_512x512_20k_voc12aug_20200617_102345-c7ff3d56.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_512x512_20k_voc12aug.py



  - Name: deeplabv3plus_r50-d8_512x512_40k_voc12aug
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 47.62
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Pascal VOC 2012 + Aug
        Metrics:
          mIoU: 76.81
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_40k_voc12aug/deeplabv3plus_r50-d8_512x512_40k_voc12aug_20200613_161759-e1b43aa9.pth
    Config: configs/deeplabv3+/deeplabv3plus_r50-d8_512x512_40k_voc12aug.py



  - Name: deeplabv3plus_r101-d8_512x512_40k_voc12aug
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 72.05
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Pascal VOC 2012 + Aug
        Metrics:
          mIoU: 78.62
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_40k_voc12aug/deeplabv3plus_r101-d8_512x512_40k_voc12aug_20200613_205333-faf03387.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_512x512_40k_voc12aug.py



  - Name: deeplabv3plus_r101-d8_480x480_40k_pascal_context
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 110.01
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Pascal Context
        Metrics:
          mIoU: 47.30
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context/deeplabv3plus_r101-d8_480x480_40k_pascal_context_20200911_165459-d3c8a29e.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_480x480_40k_pascal_context.py



  - Name: deeplabv3plus_r101-d8_480x480_80k_pascal_context
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: 110.01
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Pascal Context
        Metrics:
          mIoU: 47.23
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context/deeplabv3plus_r101-d8_480x480_80k_pascal_context_20200911_155322-145d3ee8.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_480x480_80k_pascal_context.py



  - Name: deeplabv3plus_r101-d8_480x480_40k_pascal_context
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: None
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Pascal Context
        Metrics:
          mIoU: 52.86
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59_20210416_111233-ed937f15.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_480x480_40k_pascal_context.py



  - Name: deeplabv3plus_r101-d8_480x480_80k_pascal_context
    In Collection: DeepLabV3+
    Metadata:
      inference time (ms/im):
        - value: None
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
    Results:
      - Task: Semantic Segmentation
        Dataset: Pascal Context
        Metrics:
          mIoU: 53.2
    Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59_20210416_111127-7ca0331d.pth
    Config: configs/deeplabv3+/deeplabv3plus_r101-d8_480x480_80k_pascal_context.py