configs/bisenetv2/metafile.yaml

Collections:
- Name: BiSeNetV2
  License: Apache License 2.0
  Metadata:
    Training Data:
    - Cityscapes
  Paper:
    Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic
      Segmentation'
    URL: https://arxiv.org/abs/2004.02147
  README: configs/bisenetv2/README.md
  Frameworks:
  - PyTorch
Models:
- Name: bisenetv2_fcn_4xb4-160k_cityscapes-1024x1024
  In Collection: BiSeNetV2
  Results:
    Task: Semantic Segmentation
    Dataset: Cityscapes
    Metrics:
      mIoU: 73.21
      mIoU(ms+flip): 75.74
  Config: configs/bisenetv2/bisenetv2_fcn_4xb4-160k_cityscapes-1024x1024.py
  Metadata:
    Training Data: Cityscapes
    Batch Size: 16
    Architecture:
    - BiSeNetV2
    - BiSeNetV2
    Training Resources: 4x V100 GPUS
    Memory (GB): 7.64
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes_20210902_015551-bcf10f09.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes_20210902_015551.log.json
  Paper:
    Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic
      Segmentation'
    URL: https://arxiv.org/abs/2004.02147
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545
  Framework: PyTorch
- Name: bisenetv2_fcn_4xb4-ohem-160k_cityscapes-1024x1024
  In Collection: BiSeNetV2
  Results:
    Task: Semantic Segmentation
    Dataset: Cityscapes
    Metrics:
      mIoU: 73.57
      mIoU(ms+flip): 75.8
  Config: configs/bisenetv2/bisenetv2_fcn_4xb4-ohem-160k_cityscapes-1024x1024.py
  Metadata:
    Training Data: Cityscapes
    Batch Size: 16
    Architecture:
    - BiSeNetV2
    - BiSeNetV2
    Training Resources: 4x V100 GPUS
    Memory (GB): 7.64
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes_20210902_112947-5f8103b4.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes_20210902_112947.log.json
  Paper:
    Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic
      Segmentation'
    URL: https://arxiv.org/abs/2004.02147
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545
  Framework: PyTorch
- Name: bisenetv2_fcn_4xb8-160k_cityscapes-1024x1024
  In Collection: BiSeNetV2
  Results:
    Task: Semantic Segmentation
    Dataset: Cityscapes
    Metrics:
      mIoU: 75.76
      mIoU(ms+flip): 77.79
  Config: configs/bisenetv2/bisenetv2_fcn_4xb8-160k_cityscapes-1024x1024.py
  Metadata:
    Training Data: Cityscapes
    Batch Size: 32
    Architecture:
    - BiSeNetV2
    - BiSeNetV2
    Training Resources: 4x V100 GPUS
    Memory (GB): 15.05
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes_20210903_000032-e1a2eed6.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes_20210903_000032.log.json
  Paper:
    Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic
      Segmentation'
    URL: https://arxiv.org/abs/2004.02147
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545
  Framework: PyTorch
- Name: bisenetv2_fcn_4xb4-amp-160k_cityscapes-1024x1024
  In Collection: BiSeNetV2
  Results:
    Task: Semantic Segmentation
    Dataset: Cityscapes
    Metrics:
      mIoU: 73.07
      mIoU(ms+flip): 75.13
  Config: configs/bisenetv2/bisenetv2_fcn_4xb4-amp-160k_cityscapes-1024x1024.py
  Metadata:
    Training Data: Cityscapes
    Batch Size: 16
    Architecture:
    - BiSeNetV2
    - BiSeNetV2
    Training Resources: 4x V100 GPUS
    Memory (GB): 5.77
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes_20210902_045942-b979777b.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes_20210902_045942.log.json
  Paper:
    Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic
      Segmentation'
    URL: https://arxiv.org/abs/2004.02147
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545
  Framework: PyTorch