configs/dpt/metafile.yaml

Collections:
- Name: DPT
  License: Apache License 2.0
  Metadata:
    Training Data:
    - ADE20K
  Paper:
    Title: Vision Transformer for Dense Prediction
    URL: https://arxiv.org/abs/2103.13413
  README: configs/dpt/README.md
  Frameworks:
  - PyTorch
Models:
- Name: dpt_vit-b16_8xb2-160k_ade20k-512x512
  In Collection: DPT
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 46.97
      mIoU(ms+flip): 48.34
  Config: configs/dpt/dpt_vit-b16_8xb2-160k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 16
    Architecture:
    - ViT-B
    - DPT
    Training Resources: 8x V100 GPUS
    Memory (GB): 8.09
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dpt/dpt_vit-b16_512x512_160k_ade20k/dpt_vit-b16_512x512_160k_ade20k-db31cf52.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/dpt/dpt_vit-b16_512x512_160k_ade20k/dpt_vit-b16_512x512_160k_ade20k-20210809_172025.log.json
  Paper:
    Title: Vision Transformer for Dense Prediction
    URL: https://arxiv.org/abs/2103.13413
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/dpt_head.py#L215
  Framework: PyTorch