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metafile.yml
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Collections:
- Name: Deformable Convolutional Networks
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- Deformable Convolution
Paper:
URL: https://arxiv.org/abs/1703.06211
Title: "Deformable Convolutional Networks"
README: configs/dcn/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/ops/dcn/deform_conv.py#L15
Version: v2.0.0
Models:
- Name: faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 4.0
inference time (ms/im):
- value: 56.18
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.3
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco/faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco_20200130-d68aed1e.pth
- Name: faster_rcnn_r50_fpn_dpool_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/faster_rcnn_r50_fpn_dpool_1x_coco.py
Metadata:
Training Memory (GB): 5.0
inference time (ms/im):
- value: 58.14
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 38.9
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_dpool_1x_coco/faster_rcnn_r50_fpn_dpool_1x_coco_20200307-90d3c01d.pth
- Name: faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 6.0
inference time (ms/im):
- value: 80
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco/faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco_20200203-1377f13d.pth
- Name: faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 7.3
inference time (ms/im):
- value: 100
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 44.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco/faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco_20200203-4f85c69c.pth
- Name: mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 4.5
inference time (ms/im):
- value: 64.94
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.8
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.4
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco_20200203-4d9ad43b.pth
- Name: mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco.py
Metadata:
Training Techniques:
- SGD with Momentum
- Weight Decay
- Mixed Precision Training
Training Memory (GB): 3.0
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.9
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco_20210520_180247-c06429d2.pth
- Name: mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 6.5
inference time (ms/im):
- value: 85.47
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 43.5
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 38.9
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco/mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco_20200216-a71f5bce.pth
- Name: cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 4.5
inference time (ms/im):
- value: 68.49
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 43.8
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco/cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco_20200130-2f1fca44.pth
- Name: cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 6.4
inference time (ms/im):
- value: 90.91
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 45.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco/cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco_20200203-3b2f0594.pth
- Name: cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 6.0
inference time (ms/im):
- value: 100
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 44.4
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 38.6
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco/cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco_20200202-42e767a2.pth
- Name: cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 8.0
inference time (ms/im):
- value: 116.28
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 45.8
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 39.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco/cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco_20200204-df0c5f10.pth
- Name: cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks
Config: configs/dcn/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py
Metadata:
Training Memory (GB): 9.2
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 47.3
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 41.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco-e75f90c8.pth