metafile.yml
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Collections:
- Name: Rethinking Classification and Localization for Object Detection
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- FPN
- RPN
- ResNet
- RoIAlign
Paper:
URL: https://arxiv.org/pdf/1904.06493
Title: 'Rethinking Classification and Localization for Object Detection'
README: configs/double_heads/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/roi_heads/double_roi_head.py#L6
Version: v2.0.0
Models:
- Name: dh_faster_rcnn_r50_fpn_1x_coco
In Collection: Rethinking Classification and Localization for Object Detection
Config: configs/double_heads/dh_faster_rcnn_r50_fpn_1x_coco.py
Metadata:
Training Memory (GB): 6.8
inference time (ms/im):
- value: 105.26
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/double_heads/dh_faster_rcnn_r50_fpn_1x_coco/dh_faster_rcnn_r50_fpn_1x_coco_20200130-586b67df.pth