Collections:

- Name: deeplabv3plus

  Metadata:

    Training Data:

    - Cityscapes

    - ADE20K

    - Pascal VOC 2012 + Aug

    - Pascal Context

    - Pascal Context 59

    - LoveDA

  Paper:

    URL: https://arxiv.org/abs/1802.02611

    Title: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

  README: configs/deeplabv3plus/README.md

  Code:

    URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/sep_aspp_head.py#L30

    Version: v0.17.0

  Converted From:

    Code: https://github.com/tensorflow/models/tree/master/research/deeplab

Models:

- Name: deeplabv3plus_r50-d8_512x1024_40k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (512,1024)

    lr schd: 40000

    inference time (ms/im):

    - value: 253.81

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,1024)

    Training Memory (GB): 7.5

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 79.61

      mIoU(ms+flip): 81.01

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py

  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

- Name: deeplabv3plus_r101-d8_512x1024_40k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (512,1024)

    lr schd: 40000

    inference time (ms/im):

    - value: 384.62

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,1024)

    Training Memory (GB): 11.0

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 80.21

      mIoU(ms+flip): 81.82

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_40k_cityscapes.py

  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

- Name: deeplabv3plus_r50-d8_769x769_40k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (769,769)

    lr schd: 40000

    inference time (ms/im):

    - value: 581.4

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (769,769)

    Training Memory (GB): 8.5

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 78.97

      mIoU(ms+flip): 80.46

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_40k_cityscapes.py

  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

- Name: deeplabv3plus_r101-d8_769x769_40k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (769,769)

    lr schd: 40000

    inference time (ms/im):

    - value: 869.57

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (769,769)

    Training Memory (GB): 12.5

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 79.46

      mIoU(ms+flip): 80.5

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_40k_cityscapes.py

  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

- Name: deeplabv3plus_r18-d8_512x1024_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-18-D8

    crop size: (512,1024)

    lr schd: 80000

    inference time (ms/im):

    - value: 70.08

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,1024)

    Training Memory (GB): 2.2

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 76.89

      mIoU(ms+flip): 78.76

  Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py

  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

- Name: deeplabv3plus_r50-d8_512x1024_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (512,1024)

    lr schd: 80000

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 80.09

      mIoU(ms+flip): 81.13

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py

  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

- Name: deeplabv3plus_r101-d8_512x1024_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (512,1024)

    lr schd: 80000

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 80.97

      mIoU(ms+flip): 82.03

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py

  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

- Name: deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (512,1024)

    lr schd: 80000

    inference time (ms/im):

    - value: 127.06

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP16

      resolution: (512,1024)

    Training Memory (GB): 6.35

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 80.46

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py

  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-f1104f4b.pth

- Name: deeplabv3plus_r18-d8_769x769_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-18-D8

    crop size: (769,769)

    lr schd: 80000

    inference time (ms/im):

    - value: 174.22

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (769,769)

    Training Memory (GB): 2.5

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 76.26

      mIoU(ms+flip): 77.91

  Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes.py

  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

- Name: deeplabv3plus_r50-d8_769x769_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (769,769)

    lr schd: 80000

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 79.83

      mIoU(ms+flip): 81.48

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py

  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

- Name: deeplabv3plus_r101-d8_769x769_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (769,769)

    lr schd: 80000

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 80.98

      mIoU(ms+flip): 82.18

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes.py

  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

- Name: deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D16-MG124

    crop size: (512,1024)

    lr schd: 40000

    inference time (ms/im):

    - value: 133.69

      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: 79.09

      mIoU(ms+flip): 80.36

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes.py

  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

- Name: deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D16-MG124

    crop size: (512,1024)

    lr schd: 80000

    Training Memory (GB): 9.9

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 79.9

      mIoU(ms+flip): 81.33

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes.py

  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

- Name: deeplabv3plus_r18b-d8_512x1024_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-18b-D8

    crop size: (512,1024)

    lr schd: 80000

    inference time (ms/im):

    - value: 66.89

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,1024)

    Training Memory (GB): 2.1

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 75.87

      mIoU(ms+flip): 77.52

  Config: configs/deeplabv3plus/deeplabv3plus_r18b-d8_512x1024_80k_cityscapes.py

  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

- Name: deeplabv3plus_r50b-d8_512x1024_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50b-D8

    crop size: (512,1024)

    lr schd: 80000

    inference time (ms/im):

    - value: 253.81

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,1024)

    Training Memory (GB): 7.4

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 80.28

      mIoU(ms+flip): 81.44

  Config: configs/deeplabv3plus/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes.py

  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

- Name: deeplabv3plus_r101b-d8_512x1024_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101b-D8

    crop size: (512,1024)

    lr schd: 80000

    inference time (ms/im):

    - value: 384.62

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,1024)

    Training Memory (GB): 10.9

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 80.16

      mIoU(ms+flip): 81.41

  Config: configs/deeplabv3plus/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes.py

  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

- Name: deeplabv3plus_r18b-d8_769x769_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-18b-D8

    crop size: (769,769)

    lr schd: 80000

    inference time (ms/im):

    - value: 167.79

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (769,769)

    Training Memory (GB): 2.4

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 76.36

      mIoU(ms+flip): 78.24

  Config: configs/deeplabv3plus/deeplabv3plus_r18b-d8_769x769_80k_cityscapes.py

  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

- Name: deeplabv3plus_r50b-d8_769x769_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50b-D8

    crop size: (769,769)

    lr schd: 80000

    inference time (ms/im):

    - value: 581.4

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (769,769)

    Training Memory (GB): 8.4

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 79.41

      mIoU(ms+flip): 80.56

  Config: configs/deeplabv3plus/deeplabv3plus_r50b-d8_769x769_80k_cityscapes.py

  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

- Name: deeplabv3plus_r101b-d8_769x769_80k_cityscapes

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101b-D8

    crop size: (769,769)

    lr schd: 80000

    inference time (ms/im):

    - value: 909.09

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (769,769)

    Training Memory (GB): 12.3

  Results:

  - Task: Semantic Segmentation

    Dataset: Cityscapes

    Metrics:

      mIoU: 79.88

      mIoU(ms+flip): 81.46

  Config: configs/deeplabv3plus/deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py

  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

- Name: deeplabv3plus_r50-d8_512x512_80k_ade20k

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (512,512)

    lr schd: 80000

    inference time (ms/im):

    - value: 47.6

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,512)

    Training Memory (GB): 10.6

  Results:

  - Task: Semantic Segmentation

    Dataset: ADE20K

    Metrics:

      mIoU: 42.72

      mIoU(ms+flip): 43.75

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_ade20k.py

  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

- Name: deeplabv3plus_r101-d8_512x512_80k_ade20k

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (512,512)

    lr schd: 80000

    inference time (ms/im):

    - value: 70.62

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,512)

    Training Memory (GB): 14.1

  Results:

  - Task: Semantic Segmentation

    Dataset: ADE20K

    Metrics:

      mIoU: 44.6

      mIoU(ms+flip): 46.06

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_ade20k.py

  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

- Name: deeplabv3plus_r50-d8_512x512_160k_ade20k

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (512,512)

    lr schd: 160000

  Results:

  - Task: Semantic Segmentation

    Dataset: ADE20K

    Metrics:

      mIoU: 43.95

      mIoU(ms+flip): 44.93

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_160k_ade20k.py

  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

- Name: deeplabv3plus_r101-d8_512x512_160k_ade20k

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (512,512)

    lr schd: 160000

  Results:

  - Task: Semantic Segmentation

    Dataset: ADE20K

    Metrics:

      mIoU: 45.47

      mIoU(ms+flip): 46.35

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k.py

  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

- Name: deeplabv3plus_r50-d8_512x512_20k_voc12aug

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (512,512)

    lr schd: 20000

    inference time (ms/im):

    - value: 47.62

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,512)

    Training Memory (GB): 7.6

  Results:

  - Task: Semantic Segmentation

    Dataset: Pascal VOC 2012 + Aug

    Metrics:

      mIoU: 75.93

      mIoU(ms+flip): 77.5

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug.py

  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

- Name: deeplabv3plus_r101-d8_512x512_20k_voc12aug

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (512,512)

    lr schd: 20000

    inference time (ms/im):

    - value: 72.05

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,512)

    Training Memory (GB): 11.0

  Results:

  - Task: Semantic Segmentation

    Dataset: Pascal VOC 2012 + Aug

    Metrics:

      mIoU: 77.22

      mIoU(ms+flip): 78.59

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_20k_voc12aug.py

  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

- Name: deeplabv3plus_r50-d8_512x512_40k_voc12aug

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (512,512)

    lr schd: 40000

  Results:

  - Task: Semantic Segmentation

    Dataset: Pascal VOC 2012 + Aug

    Metrics:

      mIoU: 76.81

      mIoU(ms+flip): 77.57

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_40k_voc12aug.py

  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

- Name: deeplabv3plus_r101-d8_512x512_40k_voc12aug

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (512,512)

    lr schd: 40000

  Results:

  - Task: Semantic Segmentation

    Dataset: Pascal VOC 2012 + Aug

    Metrics:

      mIoU: 78.62

      mIoU(ms+flip): 79.53

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_40k_voc12aug.py

  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

- Name: deeplabv3plus_r101-d8_480x480_40k_pascal_context

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (480,480)

    lr schd: 40000

    inference time (ms/im):

    - value: 110.01

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (480,480)

  Results:

  - Task: Semantic Segmentation

    Dataset: Pascal Context

    Metrics:

      mIoU: 47.3

      mIoU(ms+flip): 48.47

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context.py

  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

- Name: deeplabv3plus_r101-d8_480x480_80k_pascal_context

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (480,480)

    lr schd: 80000

  Results:

  - Task: Semantic Segmentation

    Dataset: Pascal Context

    Metrics:

      mIoU: 47.23

      mIoU(ms+flip): 48.26

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context.py

  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

- Name: deeplabv3plus_r101-d8_480x480_40k_pascal_context_59

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (480,480)

    lr schd: 40000

  Results:

  - Task: Semantic Segmentation

    Dataset: Pascal Context 59

    Metrics:

      mIoU: 52.86

      mIoU(ms+flip): 54.54

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59.py

  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

- Name: deeplabv3plus_r101-d8_480x480_80k_pascal_context_59

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (480,480)

    lr schd: 80000

  Results:

  - Task: Semantic Segmentation

    Dataset: Pascal Context 59

    Metrics:

      mIoU: 53.2

      mIoU(ms+flip): 54.67

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59.py

  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

- Name: deeplabv3plus_r18-d8_512x512_80k_loveda

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-18-D8

    crop size: (512,512)

    lr schd: 80000

    inference time (ms/im):

    - value: 39.11

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,512)

    Training Memory (GB): 1.93

  Results:

  - Task: Semantic Segmentation

    Dataset: LoveDA

    Metrics:

      mIoU: 50.28

      mIoU(ms+flip): 50.47

  Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_512x512_80k_loveda.py

  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x512_80k_loveda/deeplabv3plus_r18-d8_512x512_80k_loveda_20211104_132800-ce0fa0ca.pth

- Name: deeplabv3plus_r50-d8_512x512_80k_loveda

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-50-D8

    crop size: (512,512)

    lr schd: 80000

    inference time (ms/im):

    - value: 166.67

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,512)

    Training Memory (GB): 7.37

  Results:

  - Task: Semantic Segmentation

    Dataset: LoveDA

    Metrics:

      mIoU: 50.99

      mIoU(ms+flip): 50.65

  Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_loveda.py

  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_loveda/deeplabv3plus_r50-d8_512x512_80k_loveda_20211105_080442-f0720392.pth

- Name: deeplabv3plus_r101-d8_512x512_80k_loveda

  In Collection: deeplabv3plus

  Metadata:

    backbone: R-101-D8

    crop size: (512,512)

    lr schd: 80000

    inference time (ms/im):

    - value: 230.95

      hardware: V100

      backend: PyTorch

      batch size: 1

      mode: FP32

      resolution: (512,512)

    Training Memory (GB): 10.84

  Results:

  - Task: Semantic Segmentation

    Dataset: LoveDA

    Metrics:

      mIoU: 51.47

      mIoU(ms+flip): 51.32

  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_loveda.py

  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_loveda/deeplabv3plus_r101-d8_512x512_80k_loveda_20211105_110759-4c1f297e.pth