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metafile.yml
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Collections:
- Name: RetinaNet
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- Focal Loss
- FPN
- ResNet
Paper:
URL: https://arxiv.org/abs/1708.02002
Title: "Focal Loss for Dense Object Detection"
README: configs/retinanet/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/detectors/retinanet.py#L6
Version: v2.0.0
Models:
- Name: retinanet_r18_fpn_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r18_fpn_1x_coco.py
Metadata:
Training Memory (GB): 1.7
Training Resources: 8x V100 GPUs
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 31.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r18_fpn_1x_coco/retinanet_r18_fpn_1x_coco_20220407_171055-614fd399.pth
- Name: retinanet_r18_fpn_1x8_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r18_fpn_1x8_1x_coco.py
Metadata:
Training Memory (GB): 5.0
Training Resources: 1x V100 GPUs
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 31.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r18_fpn_1x8_1x_coco/retinanet_r18_fpn_1x8_1x_coco_20220407_171255-4ea310d7.pth
- Name: retinanet_r50_caffe_fpn_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r50_caffe_fpn_1x_coco.py
Metadata:
Training Memory (GB): 3.5
inference time (ms/im):
- value: 53.76
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 36.3
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r50_caffe_fpn_1x_coco/retinanet_r50_caffe_fpn_1x_coco_20200531-f11027c5.pth
- Name: retinanet_r50_fpn_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r50_fpn_1x_coco.py
Metadata:
Training Memory (GB): 3.8
inference time (ms/im):
- value: 52.63
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 36.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r50_fpn_1x_coco/retinanet_r50_fpn_1x_coco_20200130-c2398f9e.pth
- Name: retinanet_r50_fpn_fp16_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r50_fpn_fp16_1x_coco.py
Metadata:
Training Memory (GB): 2.8
Training Techniques:
- SGD with Momentum
- Weight Decay
- Mixed Precision Training
inference time (ms/im):
- value: 31.65
hardware: V100
backend: PyTorch
batch size: 1
mode: FP16
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 36.4
Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/retinanet_r50_fpn_fp16_1x_coco/retinanet_r50_fpn_fp16_1x_coco_20200702-0dbfb212.pth
- Name: retinanet_r50_fpn_2x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r50_fpn_2x_coco.py
Metadata:
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 37.4
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r50_fpn_2x_coco/retinanet_r50_fpn_2x_coco_20200131-fdb43119.pth
- Name: retinanet_r50_fpn_mstrain_3x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r50_fpn_mstrain_640-800_3x_coco.py
Metadata:
Epochs: 36
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 39.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r50_fpn_mstrain_3x_coco/retinanet_r50_fpn_mstrain_3x_coco_20210718_220633-88476508.pth
- Name: retinanet_r101_caffe_fpn_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r101_caffe_fpn_1x_coco.py
Metadata:
Training Memory (GB): 5.5
inference time (ms/im):
- value: 68.03
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 38.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r101_caffe_fpn_1x_coco/retinanet_r101_caffe_fpn_1x_coco_20200531-b428fa0f.pth
- Name: retinanet_r101_caffe_fpn_mstrain_3x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r101_caffe_fpn_1x_coco.py
Metadata:
Epochs: 36
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r101_caffe_fpn_mstrain_3x_coco/retinanet_r101_caffe_fpn_mstrain_3x_coco_20210721_063439-88a8a944.pth
- Name: retinanet_r101_fpn_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r101_fpn_1x_coco.py
Metadata:
Training Memory (GB): 5.7
inference time (ms/im):
- value: 66.67
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 38.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r101_fpn_1x_coco/retinanet_r101_fpn_1x_coco_20200130-7a93545f.pth
- Name: retinanet_r101_fpn_2x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r101_fpn_2x_coco.py
Metadata:
Training Memory (GB): 5.7
inference time (ms/im):
- value: 66.67
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/retinanet/retinanet_r101_fpn_2x_coco/retinanet_r101_fpn_2x_coco_20200131-5560aee8.pth
- Name: retinanet_r101_fpn_mstrain_3x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_r101_fpn_2x_coco.py
Metadata:
Epochs: 36
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r101_fpn_mstrain_3x_coco/retinanet_r101_fpn_mstrain_3x_coco_20210720_214650-7ee888e0.pth
- Name: retinanet_x101_32x4d_fpn_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_x101_32x4d_fpn_1x_coco.py
Metadata:
Training Memory (GB): 7.0
inference time (ms/im):
- value: 82.64
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 39.9
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_x101_32x4d_fpn_1x_coco/retinanet_x101_32x4d_fpn_1x_coco_20200130-5c8b7ec4.pth
- Name: retinanet_x101_32x4d_fpn_2x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_x101_32x4d_fpn_2x_coco.py
Metadata:
Training Memory (GB): 7.0
inference time (ms/im):
- value: 82.64
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_x101_32x4d_fpn_2x_coco/retinanet_x101_32x4d_fpn_2x_coco_20200131-237fc5e1.pth
- Name: retinanet_x101_64x4d_fpn_1x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_x101_64x4d_fpn_1x_coco.py
Metadata:
Training Memory (GB): 10.0
inference time (ms/im):
- value: 114.94
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_x101_64x4d_fpn_1x_coco/retinanet_x101_64x4d_fpn_1x_coco_20200130-366f5af1.pth
- Name: retinanet_x101_64x4d_fpn_2x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_x101_64x4d_fpn_2x_coco.py
Metadata:
Training Memory (GB): 10.0
inference time (ms/im):
- value: 114.94
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/retinanet/retinanet_x101_64x4d_fpn_2x_coco/retinanet_x101_64x4d_fpn_2x_coco_20200131-bca068ab.pth
- Name: retinanet_x101_64x4d_fpn_mstrain_3x_coco
In Collection: RetinaNet
Config: configs/retinanet/retinanet_x101_64x4d_fpn_mstrain_640-800_3x_coco.py
Metadata:
Epochs: 36
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.6
Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_x101_64x4d_fpn_mstrain_3x_coco/retinanet_x101_64x4d_fpn_mstrain_3x_coco_20210719_051838-022c2187.pth