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添加openmmlab测试用例  
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Collections:
  - Name: PointRend
    Metadata:
      Training Data: COCO
      Training Techniques:
        - SGD with Momentum
        - Weight Decay
      Training Resources: 8x NVIDIA V100 GPUs
      Architecture:
        - PointRend
        - FPN
        - ResNet
    Paper: https://arxiv.org/abs/1912.08193
    README: configs/point_rend/README.md

Models:
  - Name: point_rend_r50_caffe_fpn_mstrain_1x_coco
    In Collection: PointRend
    Config: configs/point_rend/point_rend_r50_caffe_fpn_mstrain_1x_coco.py
    Metadata:
      Training Memory (GB): 4.6
      Epochs: 12
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 38.4
      - Task: Instance Segmentation
        Dataset: COCO
        Metrics:
          mask AP: 36.3
    Weights: https://download.openmmlab.com/mmdetection/v2.0/point_rend/point_rend_r50_caffe_fpn_mstrain_1x_coco/point_rend_r50_caffe_fpn_mstrain_1x_coco-1bcb5fb4.pth

  - Name: point_rend_r50_caffe_fpn_mstrain_3x_coco
    In Collection: PointRend
    Config: configs/point_rend/point_rend_r50_caffe_fpn_mstrain_3x_coco.py
    Metadata:
      Training Memory (GB): 4.6
      Epochs: 36
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 41.0
      - Task: Instance Segmentation
        Dataset: COCO
        Metrics:
          mask AP: 38.0
    Weights: https://download.openmmlab.com/mmdetection/v2.0/point_rend/point_rend_r50_caffe_fpn_mstrain_3x_coco/point_rend_r50_caffe_fpn_mstrain_3x_coco-e0ebb6b7.pth