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