mmdetection-2.26.0/configs/dcnv2/metafile.yml

Collections:
 - Name: Deformable Convolutional Networks v2
 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/1811.11168
 Title: "Deformable ConvNets v2: More Deformable, Better Results"
 README: configs/dcnv2/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_mdconv_c3-c5_1x_coco
 In Collection: Deformable Convolutional Networks v2
 Config: configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py
 Metadata:
 Training Memory (GB): 4.1
 inference time (ms/im):
 - value: 56.82
 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/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco_20200130-d099253b.pth

 - Name: faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco
 In Collection: Deformable Convolutional Networks v2
 Config: configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco.py
 Metadata:
 Training Memory (GB): 4.2
 inference time (ms/im):
 - value: 57.47
 hardware: V100
 backend: PyTorch
 batch size: 1
 mode: FP32
 resolution: (800, 1333)
 Epochs: 12
 Results:
 - Task: Object Detection
 Dataset: COCO
 Metrics:
 box AP: 41.5
 Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco_20200130-01262257.pth

 - Name: faster_rcnn_r50_fpn_mdpool_1x_coco
 In Collection: Deformable Convolutional Networks v2
 Config: configs/dcn/faster_rcnn_r50_fpn_mdpool_1x_coco.py
 Metadata:
 Training Memory (GB): 5.8
 inference time (ms/im):
 - value: 60.24
 hardware: V100
 backend: PyTorch
 batch size: 1
 mode: FP32
 resolution: (800, 1333)
 Epochs: 12
 Results:
 - Task: Object Detection
 Dataset: COCO
 Metrics:
 box AP: 38.7
 Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_mdpool_1x_coco/faster_rcnn_r50_fpn_mdpool_1x_coco_20200307-c0df27ff.pth

 - Name: mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco
 In Collection: Deformable Convolutional Networks v2
 Config: configs/dcn/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py
 Metadata:
 Training Memory (GB): 4.5
 inference time (ms/im):
 - value: 66.23
 hardware: V100
 backend: PyTorch
 batch size: 1
 mode: FP32
 resolution: (800, 1333)
 Epochs: 12
 Results:
 - Task: Object Detection
 Dataset: COCO
 Metrics:
 box AP: 41.5
 - Task: Instance Segmentation
 Dataset: COCO
 Metrics:
 mask AP: 37.1
 Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco_20200203-ad97591f.pth

 - Name: mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco
 In Collection: Deformable Convolutional Networks v2
 Config: configs/dcn/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco.py
 Metadata:
 Training Memory (GB): 3.1
 Training Techniques:
 - SGD with Momentum
 - Weight Decay
 - Mixed Precision Training
 Epochs: 12
 Results:
 - Task: Object Detection
 Dataset: COCO
 Metrics:
 box AP: 42.0
 - Task: Instance Segmentation
 Dataset: COCO
 Metrics:
 mask AP: 37.6
 Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco_20210520_180434-cf8fefa5.pth