40 lines
1.3 KiB
YAML
40 lines
1.3 KiB
YAML
Collections:
|
|
- Name: CentripetalNet
|
|
Metadata:
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- Adam
|
|
Training Resources: 16x V100 GPUs
|
|
Architecture:
|
|
- Corner Pooling
|
|
- Stacked Hourglass Network
|
|
Paper:
|
|
URL: https://arxiv.org/abs/2003.09119
|
|
Title: 'CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection'
|
|
README: configs/centripetalnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.5.0/mmdet/models/detectors/cornernet.py#L9
|
|
Version: v2.5.0
|
|
|
|
Models:
|
|
- Name: centripetalnet_hourglass104_mstest_16x6_210e_coco
|
|
In Collection: CentripetalNet
|
|
Config: configs/centripetalnet/centripetalnet_hourglass104_mstest_16x6_210e_coco.py
|
|
Metadata:
|
|
Batch Size: 96
|
|
Training Memory (GB): 16.7
|
|
inference time (ms/im):
|
|
- value: 270.27
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 210
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 44.8
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/centripetalnet/centripetalnet_hourglass104_mstest_16x6_210e_coco/centripetalnet_hourglass104_mstest_16x6_210e_coco_20200915_204804-3ccc61e5.pth
|