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- Collections:
- - Name: HRNet
- Metadata:
- Training Data: COCO
- Training Techniques:
- - SGD with Momentum
- - Weight Decay
- Training Resources: 8x V100 GPUs
- Architecture:
- - HRNet
- Paper:
- URL: https://arxiv.org/abs/1904.04514
- Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
- README: configs/hrnet/README.md
- Code:
- URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
- Version: v2.0.0
-
- Models:
- - Name: faster_rcnn_hrnetv2p_w18_1x_coco
- In Collection: HRNet
- Config: configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.py
- Metadata:
- Training Memory (GB): 6.6
- inference time (ms/im):
- - value: 74.63
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 36.9
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco/faster_rcnn_hrnetv2p_w18_1x_coco_20200130-56651a6d.pth
-
- - Name: faster_rcnn_hrnetv2p_w18_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.py
- Metadata:
- Training Memory (GB): 6.6
- inference time (ms/im):
- - value: 74.63
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 38.9
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco/faster_rcnn_hrnetv2p_w18_2x_coco_20200702_085731-a4ec0611.pth
-
- - Name: faster_rcnn_hrnetv2p_w32_1x_coco
- In Collection: HRNet
- Config: configs/hrnet/faster_rcnn_hrnetv2p_w32_1x_coco.py
- Metadata:
- Training Memory (GB): 9.0
- inference time (ms/im):
- - value: 80.65
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.2
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w32_1x_coco/faster_rcnn_hrnetv2p_w32_1x_coco_20200130-6e286425.pth
-
- - Name: faster_rcnn_hrnetv2p_w32_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/faster_rcnn_hrnetv2p_w32_2x_coco.py
- Metadata:
- Training Memory (GB): 9.0
- inference time (ms/im):
- - value: 80.65
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 41.4
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w32_2x_coco/faster_rcnn_hrnetv2p_w32_2x_coco_20200529_015927-976a9c15.pth
-
- - Name: faster_rcnn_hrnetv2p_w40_1x_coco
- In Collection: HRNet
- Config: configs/hrnet/faster_rcnn_hrnetv2p_w40_1x_coco.py
- Metadata:
- Training Memory (GB): 10.4
- inference time (ms/im):
- - value: 95.24
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 41.2
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w40_1x_coco/faster_rcnn_hrnetv2p_w40_1x_coco_20200210-95c1f5ce.pth
-
- - Name: faster_rcnn_hrnetv2p_w40_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/faster_rcnn_hrnetv2p_w40_2x_coco.py
- Metadata:
- Training Memory (GB): 10.4
- inference time (ms/im):
- - value: 95.24
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.1
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w40_2x_coco/faster_rcnn_hrnetv2p_w40_2x_coco_20200512_161033-0f236ef4.pth
-
- - Name: mask_rcnn_hrnetv2p_w18_1x_coco
- In Collection: HRNet
- Config: configs/hrnet/mask_rcnn_hrnetv2p_w18_1x_coco.py
- Metadata:
- Training Memory (GB): 7.0
- 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: 37.7
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 34.2
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w18_1x_coco/mask_rcnn_hrnetv2p_w18_1x_coco_20200205-1c3d78ed.pth
-
- - Name: mask_rcnn_hrnetv2p_w18_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/mask_rcnn_hrnetv2p_w18_2x_coco.py
- Metadata:
- Training Memory (GB): 7.0
- inference time (ms/im):
- - value: 85.47
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 39.8
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 36.0
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w18_2x_coco/mask_rcnn_hrnetv2p_w18_2x_coco_20200212-b3c825b1.pth
-
- - Name: mask_rcnn_hrnetv2p_w32_1x_coco
- In Collection: HRNet
- Config: configs/hrnet/mask_rcnn_hrnetv2p_w32_1x_coco.py
- Metadata:
- Training Memory (GB): 9.4
- inference time (ms/im):
- - value: 88.5
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 41.2
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.1
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w32_1x_coco/mask_rcnn_hrnetv2p_w32_1x_coco_20200207-b29f616e.pth
-
- - Name: mask_rcnn_hrnetv2p_w32_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/mask_rcnn_hrnetv2p_w32_2x_coco.py
- Metadata:
- Training Memory (GB): 9.4
- inference time (ms/im):
- - value: 88.5
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.5
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.8
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w32_2x_coco/mask_rcnn_hrnetv2p_w32_2x_coco_20200213-45b75b4d.pth
-
- - Name: mask_rcnn_hrnetv2p_w40_1x_coco
- In Collection: HRNet
- Config: configs/hrnet/mask_rcnn_hrnetv2p_w40_1x_coco.py
- Metadata:
- Training Memory (GB): 10.9
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.1
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.5
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w40_1x_coco/mask_rcnn_hrnetv2p_w40_1x_coco_20200511_015646-66738b35.pth
-
- - Name: mask_rcnn_hrnetv2p_w40_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/mask_rcnn_hrnetv2p_w40_2x_coco.py
- Metadata:
- Training Memory (GB): 10.9
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.8
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 38.2
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w40_2x_coco/mask_rcnn_hrnetv2p_w40_2x_coco_20200512_163732-aed5e4ab.pth
-
- - Name: cascade_rcnn_hrnetv2p_w18_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/cascade_rcnn_hrnetv2p_w18_20e_coco.py
- Metadata:
- Training Memory (GB): 7.0
- inference time (ms/im):
- - value: 90.91
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 41.2
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w18_20e_coco/cascade_rcnn_hrnetv2p_w18_20e_coco_20200210-434be9d7.pth
-
- - Name: cascade_rcnn_hrnetv2p_w32_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/cascade_rcnn_hrnetv2p_w32_20e_coco.py
- Metadata:
- Training Memory (GB): 9.4
- inference time (ms/im):
- - value: 90.91
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 43.3
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w32_20e_coco/cascade_rcnn_hrnetv2p_w32_20e_coco_20200208-928455a4.pth
-
- - Name: cascade_rcnn_hrnetv2p_w40_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/cascade_rcnn_hrnetv2p_w40_20e_coco.py
- Metadata:
- Training Memory (GB): 10.8
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 43.8
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w40_20e_coco/cascade_rcnn_hrnetv2p_w40_20e_coco_20200512_161112-75e47b04.pth
-
- - Name: cascade_mask_rcnn_hrnetv2p_w18_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w18_20e_coco.py
- Metadata:
- Training Memory (GB): 8.5
- inference time (ms/im):
- - value: 117.65
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 41.6
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 36.4
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w18_20e_coco/cascade_mask_rcnn_hrnetv2p_w18_20e_coco_20200210-b543cd2b.pth
-
- - Name: cascade_mask_rcnn_hrnetv2p_w32_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w32_20e_coco.py
- Metadata:
- inference time (ms/im):
- - value: 120.48
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 44.3
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 38.6
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w32_20e_coco/cascade_mask_rcnn_hrnetv2p_w32_20e_coco_20200512_154043-39d9cf7b.pth
-
- - Name: cascade_mask_rcnn_hrnetv2p_w40_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w40_20e_coco.py
- Metadata:
- Training Memory (GB): 12.5
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 45.1
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 39.3
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w40_20e_coco/cascade_mask_rcnn_hrnetv2p_w40_20e_coco_20200527_204922-969c4610.pth
-
- - Name: htc_hrnetv2p_w18_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/htc_hrnetv2p_w18_20e_coco.py
- Metadata:
- Training Memory (GB): 10.8
- inference time (ms/im):
- - value: 212.77
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.8
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.9
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w18_20e_coco/htc_hrnetv2p_w18_20e_coco_20200210-b266988c.pth
-
- - Name: htc_hrnetv2p_w32_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/htc_hrnetv2p_w32_20e_coco.py
- Metadata:
- Training Memory (GB): 13.1
- inference time (ms/im):
- - value: 204.08
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 45.4
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 39.9
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w32_20e_coco/htc_hrnetv2p_w32_20e_coco_20200207-7639fa12.pth
-
- - Name: htc_hrnetv2p_w40_20e_coco
- In Collection: HRNet
- Config: configs/hrnet/htc_hrnetv2p_w40_20e_coco.py
- Metadata:
- Training Memory (GB): 14.6
- Epochs: 20
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 46.4
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 40.8
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w40_20e_coco/htc_hrnetv2p_w40_20e_coco_20200529_183411-417c4d5b.pth
-
- - Name: fcos_hrnetv2p_w18_gn-head_4x4_1x_coco
- In Collection: HRNet
- Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco.py
- Metadata:
- Training Resources: 4x V100 GPUs
- Batch Size: 16
- Training Memory (GB): 13.0
- inference time (ms/im):
- - value: 77.52
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 35.3
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco_20201212_100710-4ad151de.pth
-
- - Name: fcos_hrnetv2p_w18_gn-head_4x4_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco.py
- Metadata:
- Training Resources: 4x V100 GPUs
- Batch Size: 16
- Training Memory (GB): 13.0
- inference time (ms/im):
- - value: 77.52
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 38.2
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco_20201212_101110-5c575fa5.pth
-
- - Name: fcos_hrnetv2p_w32_gn-head_4x4_1x_coco
- In Collection: HRNet
- Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco.py
- Metadata:
- Training Resources: 4x V100 GPUs
- Batch Size: 16
- Training Memory (GB): 17.5
- inference time (ms/im):
- - value: 77.52
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 39.5
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco_20201211_134730-cb8055c0.pth
-
- - Name: fcos_hrnetv2p_w32_gn-head_4x4_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco.py
- Metadata:
- Training Resources: 4x V100 GPUs
- Batch Size: 16
- Training Memory (GB): 17.5
- inference time (ms/im):
- - value: 77.52
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.8
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco_20201212_112133-77b6b9bb.pth
-
- - Name: fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco.py
- Metadata:
- Training Resources: 4x V100 GPUs
- Batch Size: 16
- Training Memory (GB): 13.0
- inference time (ms/im):
- - value: 77.52
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 38.3
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco_20201212_111651-441e9d9f.pth
-
- - Name: fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco.py
- Metadata:
- Training Resources: 4x V100 GPUs
- Batch Size: 16
- Training Memory (GB): 17.5
- inference time (ms/im):
- - value: 80.65
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 41.9
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco_20201212_090846-b6f2b49f.pth
-
- - Name: fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco
- In Collection: HRNet
- Config: configs/hrnet/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco.py
- Metadata:
- Training Resources: 4x V100 GPUs
- Batch Size: 16
- Training Memory (GB): 20.3
- inference time (ms/im):
- - value: 92.59
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.7
- Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco_20201212_124752-f22d2ce5.pth
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