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[Dygraph] add ResNet-vd, ResNet-34, ResNeXt-101 (PaddlePaddle#2071)
* add configs and modelzoo * remove trainreader of batchsize 2 * add vd r34 x101 * fix typo * add vd r34 x101 * add resnet dcn, clean code * fix x101 width in py2 * add faster mask rcnn dcn configs and modelzoo * fix dcn modelzoo * clean dcn configs code
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### Deformable ConvNets v2 | ||
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| 骨架网络 | 网络类型 | 卷积 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | Mask AP | 下载 | 配置文件 | | ||
| :------------------- | :------------- | :-----: |:--------: | :-----: | :-----------: |:----: | :-----: | :----------------------------------------------------------: | :----: | | ||
| ResNet50-FPN | Faster | c3-c5 | 2 | 1x | - | 41.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/faster_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/dcn/faster_rcnn_dcn_r50_fpn_1x_coco.yml) | | ||
| ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | - | 42.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/faster_rcnn_dcn_r50_vd_fpn_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x.yml) | | ||
| ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | - | 44.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/faster_rcnn_dcn_r101_vd_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x.yml) | | ||
| ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 45.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.pdparams) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) | | ||
| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | - | 41.9 | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/mask_rcnn_dcn_r50_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/dcn/mask_rcnn_dcn_r50_fpn_1x.yml) | | ||
| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | - | 42.9 | 38.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/mask_rcnn_dcn_r50_vd_fpn_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x.yml) | | ||
| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 44.6 | 39.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/mask_rcnn_dcn_r101_vd_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x.yml) | | ||
| ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 46.2 | 40.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) | | ||
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**注意事项:** | ||
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- Deformable卷积网络v2(dcn_v2)参考自论文[Deformable ConvNets v2](https://arxiv.org/abs/1811.11168). | ||
- `c3-c5`意思是在resnet模块的3到5阶段增加`dcn`. | ||
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## Citations | ||
``` | ||
@inproceedings{dai2017deformable, | ||
title={Deformable Convolutional Networks}, | ||
author={Dai, Jifeng and Qi, Haozhi and Xiong, Yuwen and Li, Yi and Zhang, Guodong and Hu, Han and Wei, Yichen}, | ||
booktitle={Proceedings of the IEEE international conference on computer vision}, | ||
year={2017} | ||
} | ||
@article{zhu2018deformable, | ||
title={Deformable ConvNets v2: More Deformable, Better Results}, | ||
author={Zhu, Xizhou and Hu, Han and Lin, Stephen and Dai, Jifeng}, | ||
journal={arXiv preprint arXiv:1811.11168}, | ||
year={2018} | ||
} | ||
``` |
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dygraph/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x_coco.yml
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_BASE_: [ | ||
'faster_rcnn_dcn_r50_fpn_1x_coco.yml', | ||
] | ||
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.tar | ||
weights: output/faster_rcnn_dcn_r101_fpn_1x_coco/model_final | ||
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ResNet: | ||
# index 0 stands for res2 | ||
depth: 101 | ||
variant: d | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
dcn_v2_stages: [1,2,3] | ||
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epoch: 12 | ||
LearningRate: | ||
base_lr: 0.02 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [8, 11] | ||
- !LinearWarmup | ||
start_factor: 0.1 | ||
steps: 1000 | ||
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TrainReader: | ||
batch_size: 2 |
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_BASE_: [ | ||
'../datasets/coco_detection.yml', | ||
'../runtime.yml', | ||
'../faster_rcnn/_base_/optimizer_1x.yml', | ||
'../faster_rcnn/_base_/faster_rcnn_r50_fpn.yml', | ||
'../faster_rcnn/_base_/faster_fpn_reader.yml', | ||
] | ||
weights: output/faster_rcnn_dcn_r50_fpn_1x_coco/model_final | ||
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ResNet: | ||
depth: 50 | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
dcn_v2_stages: [1,2,3] | ||
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epoch: 12 | ||
LearningRate: | ||
base_lr: 0.02 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [8, 11] | ||
- !LinearWarmup | ||
start_factor: 0.1 | ||
steps: 1000 | ||
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TrainReader: | ||
batch_size: 2 |
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dygraph/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x_coco.yml
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_BASE_: [ | ||
'faster_rcnn_dcn_r50_fpn_1x_coco.yml', | ||
] | ||
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar | ||
weights: output/faster_rcnn_dcn_r50_vd_fpn_2x_coco/model_final | ||
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ResNet: | ||
# index 0 stands for res2 | ||
depth: 50 | ||
variant: d | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
dcn_v2_stages: [1,2,3] | ||
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epoch: 24 | ||
LearningRate: | ||
base_lr: 0.02 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [16, 22] | ||
- !LinearWarmup | ||
start_factor: 0.1 | ||
steps: 1000 | ||
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TrainReader: | ||
batch_size: 2 |
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dygraph/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml
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_BASE_: [ | ||
'faster_rcnn_dcn_r50_fpn_1x_coco.yml', | ||
] | ||
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNeXt101_vd_64x4d_pretrained.tar | ||
weights: output/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco/model_final.pdparams | ||
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ResNet: | ||
# for ResNeXt: groups, base_width, base_channels | ||
depth: 101 | ||
groups: 64 | ||
base_width: 4 | ||
base_channels: 64 | ||
variant: d | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
dcn_v2_stages: [1,2,3] | ||
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epoch: 12 | ||
LearningRate: | ||
base_lr: 0.01 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [8, 11] | ||
- !LinearWarmup | ||
start_factor: 0.1 | ||
steps: 1000 |
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_BASE_: [ | ||
'mask_rcnn_dcn_r50_fpn_1x_coco.yml', | ||
] | ||
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.tar | ||
weights: output/mask_rcnn_dcn_r101_fpn_1x_coco/model_final.pdparams | ||
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ResNet: | ||
# index 0 stands for res2 | ||
depth: 101 | ||
variant: d | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
dcn_v2_stages: [1,2,3] | ||
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epoch: 12 | ||
LearningRate: | ||
base_lr: 0.01 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [8, 11] | ||
- !LinearWarmup | ||
start_factor: 0.1 | ||
steps: 1000 |
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_BASE_: [ | ||
'../datasets/coco_instance.yml', | ||
'../runtime.yml', | ||
'../mask_rcnn/_base_/optimizer_1x.yml', | ||
'../mask_rcnn/_base_/mask_rcnn_r50_fpn.yml', | ||
'../mask_rcnn/_base_/mask_fpn_reader.yml', | ||
] | ||
weights: output/mask_rcnn_dcn_r50_fpn_1x_coco/model_final | ||
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ResNet: | ||
depth: 50 | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
dcn_v2_stages: [1,2,3] | ||
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epoch: 12 | ||
LearningRate: | ||
base_lr: 0.01 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [8, 11] | ||
- !LinearWarmup | ||
start_factor: 0.1 | ||
steps: 1000 |
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_BASE_: [ | ||
'mask_rcnn_dcn_r50_fpn_1x_coco.yml', | ||
] | ||
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar | ||
weights: output/mask_rcnn_dcn_r50_vd_fpn_2x_coco/model_final | ||
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||
ResNet: | ||
# index 0 stands for res2 | ||
depth: 50 | ||
variant: d | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
dcn_v2_stages: [1,2,3] | ||
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epoch: 24 | ||
LearningRate: | ||
base_lr: 0.01 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [16, 22] | ||
- !LinearWarmup | ||
start_factor: 0.1 | ||
steps: 1000 |
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dygraph/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml
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_BASE_: [ | ||
'mask_rcnn_dcn_r50_fpn_1x_coco.yml', | ||
] | ||
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNeXt101_vd_64x4d_pretrained.tar | ||
weights: output/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco/model_final.pdparams | ||
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ResNet: | ||
# for ResNeXt: groups, base_width, base_channels | ||
depth: 101 | ||
variant: d | ||
groups: 64 | ||
base_width: 4 | ||
base_channels: 64 | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
dcn_v2_stages: [1,2,3] | ||
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epoch: 12 | ||
LearningRate: | ||
base_lr: 0.01 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [8, 11] | ||
- !LinearWarmup | ||
start_factor: 0.1 | ||
steps: 1000 |
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_BASE_: [ | ||
'faster_rcnn_r50_1x_coco.yml', | ||
] | ||
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pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.tar | ||
weights: output/faster_rcnn_r101_1x_coco/model_final | ||
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ResNet: | ||
# index 0 stands for res2 | ||
depth: 101 | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 |
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dygraph/configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.yml
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@@ -0,0 +1,14 @@ | ||
_BASE_: [ | ||
'faster_rcnn_r50_fpn_1x_coco.yml', | ||
] | ||
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pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.tar | ||
weights: output/faster_rcnn_r101_fpn_1x_coco/model_final | ||
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ResNet: | ||
# index 0 stands for res2 | ||
depth: 101 | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 |
25 changes: 25 additions & 0 deletions
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dygraph/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.yml
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@@ -0,0 +1,25 @@ | ||
_BASE_: [ | ||
'faster_rcnn_r50_fpn_1x_coco.yml', | ||
] | ||
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||
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.tar | ||
weights: output/faster_rcnn_r101_fpn_2x_coco/model_final | ||
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ResNet: | ||
# index 0 stands for res2 | ||
depth: 101 | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
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epoch: 24 | ||
LearningRate: | ||
base_lr: 0.01 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [16, 22] | ||
- !LinearWarmup | ||
start_factor: 0.3333333333333333 | ||
steps: 500 |
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dygraph/configs/faster_rcnn/faster_rcnn_r101_vd_1x_coco.yml
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_BASE_: [ | ||
'faster_rcnn_r50_1x_coco.yml', | ||
] | ||
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pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_vd_pretrained.tar | ||
weights: output/faster_rcnn_r101_vd_1x_coco/model_final | ||
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ResNet: | ||
# index 0 stands for res2 | ||
depth: 101 | ||
variant: d | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
|
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epoch: 12 | ||
LearningRate: | ||
base_lr: 0.01 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [8, 11] | ||
- !LinearWarmup | ||
start_factor: 0.3333333333333333 | ||
steps: 1000 |
25 changes: 25 additions & 0 deletions
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dygraph/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_1x_coco.yml
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_BASE_: [ | ||
'faster_rcnn_r50_fpn_1x_coco.yml', | ||
] | ||
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_vd_pretrained.tar | ||
weights: output/faster_rcnn_r101_vd_fpn_1x_coco/model_final.pdparams | ||
|
||
ResNet: | ||
# index 0 stands for res2 | ||
depth: 101 | ||
variant: d | ||
norm_type: bn | ||
freeze_at: 0 | ||
return_idx: [0,1,2,3] | ||
num_stages: 4 | ||
|
||
epoch: 12 | ||
LearningRate: | ||
base_lr: 0.01 | ||
schedulers: | ||
- !PiecewiseDecay | ||
gamma: 0.1 | ||
milestones: [8, 11] | ||
- !LinearWarmup | ||
start_factor: 0.3333333333333333 | ||
steps: 1000 |
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