Collections:
- Name: fastscnn
  Metadata:
    Training Data:
    - Cityscapes
Models:
- Name: fast_scnn_lr0.12_8x4_160k_cityscapes
  In Collection: fastscnn
  Metadata:
    backbone: Fast-SCNN
    crop size: (512,1024)
    lr schd: 160000
    inference time (ms/im):
    - value: 17.71
      hardware: V100
      backend: PyTorch
      batch size: 1
      mode: FP32
      resolution: (512,1024)
    memory (GB): 3.3
  Results:
    Task: Semantic Segmentation
    Dataset: Cityscapes
    Metrics:
      mIoU: 70.96
      mIoU(ms+flip): 72.65
  Config: configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fast_scnn/fast_scnn_8x4_160k_lr0.12_cityscapes-0cec9937.pth