60 lines
1.8 KiB
YAML
60 lines
1.8 KiB
YAML
Collections:
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- Name: NAS-FPN
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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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- NAS-FPN
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- ResNet
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Paper:
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URL: https://arxiv.org/abs/1904.07392
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Title: 'NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection'
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README: configs/nas_fpn/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/necks/nas_fpn.py#L67
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Version: v2.0.0
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Models:
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- Name: retinanet_r50_fpn_crop640_50e_coco
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In Collection: NAS-FPN
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Config: configs/nas_fpn/retinanet_r50_fpn_crop640_50e_coco.py
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Metadata:
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Training Memory (GB): 12.9
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inference time (ms/im):
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- value: 43.67
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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: 50
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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: 37.9
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Weights: https://download.openmmlab.com/mmdetection/v2.0/nas_fpn/retinanet_r50_fpn_crop640_50e_coco/retinanet_r50_fpn_crop640_50e_coco-9b953d76.pth
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- Name: retinanet_r50_nasfpn_crop640_50e_coco
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In Collection: NAS-FPN
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Config: configs/nas_fpn/retinanet_r50_nasfpn_crop640_50e_coco.py
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Metadata:
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Training Memory (GB): 13.2
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inference time (ms/im):
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- value: 43.48
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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: 50
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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: 40.5
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Weights: https://download.openmmlab.com/mmdetection/v2.0/nas_fpn/retinanet_r50_nasfpn_crop640_50e_coco/retinanet_r50_nasfpn_crop640_50e_coco-0ad1f644.pth
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