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snnetv2-semantic-segmentation
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Collections:
- Name: Segmenter
  License: Apache License 2.0
  Metadata:
    Training Data:
    - ADE20K
  Paper:
    Title: 'Segmenter: Transformer for Semantic Segmentation'
    URL: https://arxiv.org/abs/2105.05633
  README: configs/segmenter/README.md
  Frameworks:
  - PyTorch
Models:
- Name: segmenter_vit-t_mask_8xb1-160k_ade20k-512x512
  In Collection: Segmenter
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 39.99
      mIoU(ms+flip): 40.83
  Config: configs/segmenter/segmenter_vit-t_mask_8xb1-160k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 8
    Architecture:
    - ViT-T_16
    - Segmenter
    - Mask
    Training Resources: 8x V100 GPUS
    Memory (GB): 1.21
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-t_mask_8x1_512x512_160k_ade20k/segmenter_vit-t_mask_8x1_512x512_160k_ade20k_20220105_151706-ffcf7509.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-t_mask_8x1_512x512_160k_ade20k/segmenter_vit-t_mask_8x1_512x512_160k_ade20k_20220105_151706.log.json
  Paper:
    Title: 'Segmenter: Transformer for Semantic Segmentation'
    URL: https://arxiv.org/abs/2105.05633
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.21.0/mmseg/models/decode_heads/segmenter_mask_head.py#L15
  Framework: PyTorch
- Name: segmenter_vit-s_fcn_8xb1-160k_ade20k-512x512
  In Collection: Segmenter
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 45.75
      mIoU(ms+flip): 46.82
  Config: configs/segmenter/segmenter_vit-s_fcn_8xb1-160k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 8
    Architecture:
    - ViT-S_16
    - Segmenter
    - Linear
    Training Resources: 8x V100 GPUS
    Memory (GB): 1.78
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_linear_8x1_512x512_160k_ade20k/segmenter_vit-s_linear_8x1_512x512_160k_ade20k_20220105_151713-39658c46.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_linear_8x1_512x512_160k_ade20k/segmenter_vit-s_linear_8x1_512x512_160k_ade20k_20220105_151713.log.json
  Paper:
    Title: 'Segmenter: Transformer for Semantic Segmentation'
    URL: https://arxiv.org/abs/2105.05633
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.21.0/mmseg/models/decode_heads/segmenter_mask_head.py#L15
  Framework: PyTorch
- Name: segmenter_vit-s_mask_8xb1-160k_ade20k-512x512
  In Collection: Segmenter
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 46.19
      mIoU(ms+flip): 47.85
  Config: configs/segmenter/segmenter_vit-s_mask_8xb1-160k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 8
    Architecture:
    - ViT-S_16
    - Segmenter
    - Mask
    Training Resources: 8x V100 GPUS
    Memory (GB): 2.03
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_mask_8x1_512x512_160k_ade20k/segmenter_vit-s_mask_8x1_512x512_160k_ade20k_20220105_151706-511bb103.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_mask_8x1_512x512_160k_ade20k/segmenter_vit-s_mask_8x1_512x512_160k_ade20k_20220105_151706.log.json
  Paper:
    Title: 'Segmenter: Transformer for Semantic Segmentation'
    URL: https://arxiv.org/abs/2105.05633
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.21.0/mmseg/models/decode_heads/segmenter_mask_head.py#L15
  Framework: PyTorch
- Name: segmenter_vit-b_mask_8xb1-160k_ade20k-512x512
  In Collection: Segmenter
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 49.6
      mIoU(ms+flip): 51.07
  Config: configs/segmenter/segmenter_vit-b_mask_8xb1-160k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 8
    Architecture:
    - ViT-B_16
    - Segmenter
    - Mask
    Training Resources: 8x V100 GPUS
    Memory (GB): 4.2
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k/segmenter_vit-b_mask_8x1_512x512_160k_ade20k_20220105_151706-bc533b08.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k/segmenter_vit-b_mask_8x1_512x512_160k_ade20k_20220105_151706.log.json
  Paper:
    Title: 'Segmenter: Transformer for Semantic Segmentation'
    URL: https://arxiv.org/abs/2105.05633
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.21.0/mmseg/models/decode_heads/segmenter_mask_head.py#L15
  Framework: PyTorch
- Name: segmenter_vit-l_mask_8xb1-160k_ade20k-512x512
  In Collection: Segmenter
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 52.16
      mIoU(ms+flip): 53.65
  Config: configs/segmenter/segmenter_vit-l_mask_8xb1-160k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 8
    Architecture:
    - ViT-L_16
    - Segmenter
    - Mask
    Training Resources: 8x V100 GPUS
    Memory (GB): 16.56
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k/segmenter_vit-l_mask_8x1_512x512_160k_ade20k_20220105_162750-7ef345be.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k/segmenter_vit-l_mask_8x1_512x512_160k_ade20k_20220105_162750.log.json
  Paper:
    Title: 'Segmenter: Transformer for Semantic Segmentation'
    URL: https://arxiv.org/abs/2105.05633
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.21.0/mmseg/models/decode_heads/segmenter_mask_head.py#L15
  Framework: PyTorch