metafile.yml

Collections:
  - Name: GLIP
    Metadata:
      Training Data: Objects365, GoldG, CC3M, SBU and COCO
      Training Techniques:
        - SGD with Momentum
        - Weight Decay
      Training Resources: A100 GPUs
      Architecture:
        - Swin Transformer
        - DYHead
        - BERT
    Paper:
      URL: https://arxiv.org/abs/2112.03857
      Title: 'GLIP: Grounded Language-Image Pre-training'
    README: configs/glip/README.md
    Code:
      URL:
      Version: v3.0.0

Models:
  - Name: glip_atss_swin-t_a_fpn_dyhead_pretrain_obj365
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-t_a_fpn_dyhead_pretrain_obj365.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 43.0
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_tiny_a_mmdet-b3654169.pth
  - Name: glip_atss_swin-t_b_fpn_dyhead_pretrain_obj365
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-t_b_fpn_dyhead_pretrain_obj365.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 44.9
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_tiny_b_mmdet-6dfbd102.pth
  - Name: glip_atss_swin-t_c_fpn_dyhead_pretrain_obj365-goldg
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-t_c_fpn_dyhead_pretrain_obj365-goldg.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 46.7
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_tiny_c_mmdet-2fc427dd.pth
  - Name: glip_atss_swin-t_fpn_dyhead_pretrain_obj365-goldg-cc3m-sub
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-t_fpn_dyhead_pretrain_obj365-goldg-cc3m-sub.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 46.4
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_tiny_mmdet-c24ce662.pth
  - Name: glip_atss_swin-l_fpn_dyhead_pretrain_mixeddata
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-l_fpn_dyhead_pretrain_mixeddata.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 51.3
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_l_mmdet-abfe026b.pth
  - Name: glip_atss_swin-t_a_fpn_dyhead_16xb2_ms-2x_funtune_coco
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-t_a_fpn_dyhead_16xb2_ms-2x_funtune_coco.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 53.3
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_atss_swin-t_a_fpn_dyhead_16xb2_ms-2x_funtune_coco/glip_atss_swin-t_a_fpn_dyhead_16xb2_ms-2x_funtune_coco_20230914_180419-e6addd96.pth
  - Name: glip_atss_swin-t_b_fpn_dyhead_16xb2_ms-2x_funtune_coco
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-t_b_fpn_dyhead_16xb2_ms-2x_funtune_coco.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 54.1
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_atss_swin-t_b_fpn_dyhead_16xb2_ms-2x_funtune_coco/glip_atss_swin-t_b_fpn_dyhead_16xb2_ms-2x_funtune_coco_20230916_163538-650323ba.pth
  - Name: glip_atss_swin-t_c_fpn_dyhead_16xb2_ms-2x_funtune_coco
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-t_c_fpn_dyhead_16xb2_ms-2x_funtune_coco.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 55.2
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_atss_swin-t_c_fpn_dyhead_16xb2_ms-2x_funtune_coco/glip_atss_swin-t_c_fpn_dyhead_16xb2_ms-2x_funtune_coco_20230914_182935-4ba3fc3b.pth
  - Name: glip_atss_swin-t_fpn_dyhead_16xb2_ms-2x_funtune_coco
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-t_fpn_dyhead_16xb2_ms-2x_funtune_coco.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 55.4
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_atss_swin-t_fpn_dyhead_16xb2_ms-2x_funtune_coco/glip_atss_swin-t_fpn_dyhead_16xb2_ms-2x_funtune_coco_20230914_224410-ba97be24.pth
  - Name: glip_atss_swin-l_fpn_dyhead_16xb2_ms-2x_funtune_coco
    In Collection: GLIP
    Config: configs/glip/glip_atss_swin-l_fpn_dyhead_16xb2_ms-2x_funtune_coco.py
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 59.4
    Weights: https://download.openmmlab.com/mmdetection/v3.0/glip/glip_atss_swin-l_fpn_dyhead_16xb2_ms-2x_funtune_coco/glip_atss_swin-l_fpn_dyhead_16xb2_ms-2x_funtune_coco_20230910_100800-e9be4274.pth