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metafile.yml
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Collections:
- Name: GHM
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- GHM-C
- GHM-R
- FPN
- ResNet
Paper:
URL: https://arxiv.org/abs/1811.05181
Title: 'Gradient Harmonized Single-stage Detector'
README: configs/ghm/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/losses/ghm_loss.py#L21
Version: v2.0.0
Models:
- Name: retinanet_r50_fpn_ghm-1x_coco
In Collection: GHM
Config: configs/ghm/retinanet_r50_fpn_ghm-1x_coco.py
Metadata:
Training Memory (GB): 4.0
inference time (ms/im):
- value: 303.03
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 37.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/ghm/retinanet_ghm_r50_fpn_1x_coco/retinanet_ghm_r50_fpn_1x_coco_20200130-a437fda3.pth
- Name: retinanet_r101_fpn_ghm-1x_coco
In Collection: GHM
Config: configs/ghm/retinanet_r101_fpn_ghm-1x_coco.py
Metadata:
Training Memory (GB): 6.0
inference time (ms/im):
- value: 227.27
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 39.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/ghm/retinanet_ghm_r101_fpn_1x_coco/retinanet_ghm_r101_fpn_1x_coco_20200130-c148ee8f.pth
- Name: retinanet_x101-32x4d_fpn_ghm-1x_coco
In Collection: GHM
Config: configs/ghm/retinanet_x101-32x4d_fpn_ghm-1x_coco.py
Metadata:
Training Memory (GB): 7.2
inference time (ms/im):
- value: 196.08
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/ghm/retinanet_ghm_x101_32x4d_fpn_1x_coco/retinanet_ghm_x101_32x4d_fpn_1x_coco_20200131-e4333bd0.pth
- Name: retinanet_x101-64x4d_fpn_ghm-1x_coco
In Collection: GHM
Config: configs/ghm/retinanet_x101-64x4d_fpn_ghm-1x_coco.py
Metadata:
Training Memory (GB): 10.3
inference time (ms/im):
- value: 192.31
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.4
Weights: https://download.openmmlab.com/mmdetection/v2.0/ghm/retinanet_ghm_x101_64x4d_fpn_1x_coco/retinanet_ghm_x101_64x4d_fpn_1x_coco_20200131-dd381cef.pth