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liuyebo
2024-08-27 14:42:45 +08:00
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paddle_detection/configs/faster_rcnn/README.md Normal file
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# Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
## Model Zoo
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 |
| :------------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
| ResNet50 | Faster | 1 | 1x | ---- | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_1x_coco.yml) |
| ResNet50-vd | Faster | 1 | 1x | ---- | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_1x_coco.yml) |
| ResNet101 | Faster | 1 | 1x | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_1x_coco.pdparams) | [配置文件](./faster_rcnn_r101_1x_coco.yml) |
| ResNet34-FPN | Faster | 1 | 1x | ---- | 37.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r34_fpn_1x_coco.yml) |
| ResNet34-FPN-MultiScaleTest | Faster | 1 | 1x | ---- | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_multiscaletest_1x_coco.pdparams) | [配置文件](./faster_rcnn_r34_fpn_multiscaletest_1x_coco.yml) |
| ResNet34-vd-FPN | Faster | 1 | 1x | ---- | 38.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_vd_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r34_vd_fpn_1x_coco.yml) |
| ResNet50-FPN | Faster | 1 | 1x | ---- | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_fpn_1x_coco.yml) |
| ResNet50-FPN | Faster | 1 | 2x | ---- | 40.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_r50_fpn_2x_coco.yml) |
| ResNet50-vd-FPN | Faster | 1 | 1x | ---- | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_fpn_1x_coco.yml) |
| ResNet50-vd-FPN | Faster | 1 | 2x | ---- | 40.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_fpn_2x_coco.yml) |
| ResNet101-FPN | Faster | 1 | 2x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_r101_fpn_2x_coco.yml) |
| ResNet101-vd-FPN | Faster | 1 | 1x | ---- | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r101_vd_fpn_1x_coco.yml) |
| ResNet101-vd-FPN | Faster | 1 | 2x | ---- | 43.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_r101_vd_fpn_2x_coco.yml) |
| ResNeXt101-vd-FPN | Faster | 1 | 1x | ---- | 43.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) |
| ResNeXt101-vd-FPN | Faster | 1 | 2x | ---- | 44.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) |
| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
| Swin-Tiny-FPN | Faster | 2 | 1x | ---- | 42.6 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_swin_tiny_fpn_1x_coco.yml) |
| Swin-Tiny-FPN | Faster | 2 | 2x | ---- | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_swin_tiny_fpn_2x_coco.yml) |
| Swin-Tiny-FPN | Faster | 2 | 3x | ---- | 45.3 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_3x_coco.pdparams) | [配置文件](../swin/faster_rcnn_swin_tiny_fpn_3x_coco.yml) |
## Citations
```
@article{Ren_2017,
title={Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Sun, Jian},
year={2017},
month={Jun},
}
```

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paddle_detection/configs/faster_rcnn/_base_/faster_fpn_reader.yml Normal file
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worker_num: 2
TrainReader:
sample_transforms:
- Decode: {}
- RandomResize: {target_size: [[640, 1333], [672, 1333], [704, 1333], [736, 1333], [768, 1333], [800, 1333]], interp: 2, keep_ratio: True}
- RandomFlip: {prob: 0.5}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: 32}
batch_size: 1
shuffle: true
drop_last: true
collate_batch: false
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: 32}
batch_size: 1
shuffle: false
drop_last: false
TestReader:
sample_transforms:
- Decode: {}
- Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: 32}
batch_size: 1
shuffle: false
drop_last: false

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architecture: FasterRCNN
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
FasterRCNN:
backbone: ResNet
rpn_head: RPNHead
bbox_head: BBoxHead
# post process
bbox_post_process: BBoxPostProcess
ResNet:
# index 0 stands for res2
depth: 50
norm_type: bn
freeze_at: 0
return_idx: [2]
num_stages: 3
RPNHead:
anchor_generator:
aspect_ratios: [0.5, 1.0, 2.0]
anchor_sizes: [32, 64, 128, 256, 512]
strides: [16]
rpn_target_assign:
batch_size_per_im: 256
fg_fraction: 0.5
negative_overlap: 0.3
positive_overlap: 0.7
use_random: True
train_proposal:
min_size: 0.0
nms_thresh: 0.7
pre_nms_top_n: 12000
post_nms_top_n: 2000
topk_after_collect: False
test_proposal:
min_size: 0.0
nms_thresh: 0.7
pre_nms_top_n: 6000
post_nms_top_n: 1000
BBoxHead:
head: Res5Head
roi_extractor:
resolution: 14
sampling_ratio: 0
aligned: True
bbox_assigner: BBoxAssigner
with_pool: true
BBoxAssigner:
batch_size_per_im: 512
bg_thresh: 0.5
fg_thresh: 0.5
fg_fraction: 0.25
use_random: True
BBoxPostProcess:
decode: RCNNBox
nms:
name: MultiClassNMS
keep_top_k: 100
score_threshold: 0.05
nms_threshold: 0.5

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paddle_detection/configs/faster_rcnn/_base_/faster_rcnn_r50_fpn.yml Normal file
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architecture: FasterRCNN
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
FasterRCNN:
backbone: ResNet
neck: FPN
rpn_head: RPNHead
bbox_head: BBoxHead
# post process
bbox_post_process: BBoxPostProcess
ResNet:
# index 0 stands for res2
depth: 50
norm_type: bn
freeze_at: 0
return_idx: [0,1,2,3]
num_stages: 4
FPN:
out_channel: 256
RPNHead:
anchor_generator:
aspect_ratios: [0.5, 1.0, 2.0]
anchor_sizes: [[32], [64], [128], [256], [512]]
strides: [4, 8, 16, 32, 64]
rpn_target_assign:
batch_size_per_im: 256
fg_fraction: 0.5
negative_overlap: 0.3
positive_overlap: 0.7
use_random: True
train_proposal:
min_size: 0.0
nms_thresh: 0.7
pre_nms_top_n: 2000
post_nms_top_n: 1000
topk_after_collect: True
test_proposal:
min_size: 0.0
nms_thresh: 0.7
pre_nms_top_n: 1000
post_nms_top_n: 1000
BBoxHead:
head: TwoFCHead
roi_extractor:
resolution: 7
sampling_ratio: 0
aligned: True
bbox_assigner: BBoxAssigner
BBoxAssigner:
batch_size_per_im: 512
bg_thresh: 0.5
fg_thresh: 0.5
fg_fraction: 0.25
use_random: True
TwoFCHead:
out_channel: 1024
BBoxPostProcess:
decode: RCNNBox
nms:
name: MultiClassNMS
keep_top_k: 100
score_threshold: 0.05
nms_threshold: 0.5

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paddle_detection/configs/faster_rcnn/_base_/faster_rcnn_swin_reader.yml Normal file
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worker_num: 2
TrainReader:
sample_transforms:
- Decode: {}
- RandomResizeCrop: {resizes: [400, 500, 600], cropsizes: [[384, 600], ], prob: 0.5}
- RandomResize: {target_size: [[480, 1333], [512, 1333], [544, 1333], [576, 1333], [608, 1333], [640, 1333], [672, 1333], [704, 1333], [736, 1333], [768, 1333], [800, 1333]], keep_ratio: True, interp: 2}
- RandomFlip: {prob: 0.5}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: 32}
batch_size: 2
shuffle: true
drop_last: true
collate_batch: false
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: 32}
batch_size: 1
shuffle: false
drop_last: false
TestReader:
inputs_def:
image_shape: [-1, 3, 640, 640]
sample_transforms:
- Decode: {}
- Resize: {interp: 2, target_size: 640, keep_ratio: True}
- Pad: {size: 640}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_size: 1
shuffle: false
drop_last: false

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architecture: FasterRCNN
# pretrain_weights: # rewrite in SwinTransformer.pretrained in ppdet/modeling/backbones/swin_transformer.py
FasterRCNN:
backbone: SwinTransformer
neck: FPN
rpn_head: RPNHead
bbox_head: BBoxHead
bbox_post_process: BBoxPostProcess
SwinTransformer:
arch: 'swin_T_224'
ape: false
drop_path_rate: 0.1
patch_norm: true
out_indices: [0, 1, 2, 3]
pretrained: https://paddledet.bj.bcebos.com/models/pretrained/swin_tiny_patch4_window7_224_22kto1k_pretrained.pdparams
FPN:
out_channel: 256
RPNHead:
anchor_generator:
aspect_ratios: [0.5, 1.0, 2.0]
anchor_sizes: [[32], [64], [128], [256], [512]]
strides: [4, 8, 16, 32, 64]
rpn_target_assign:
batch_size_per_im: 256
fg_fraction: 0.5
negative_overlap: 0.3
positive_overlap: 0.7
use_random: True
train_proposal:
min_size: 0.0
nms_thresh: 0.7
pre_nms_top_n: 2000
post_nms_top_n: 1000
topk_after_collect: True
test_proposal:
min_size: 0.0
nms_thresh: 0.7
pre_nms_top_n: 1000
post_nms_top_n: 1000
BBoxHead:
head: TwoFCHead
roi_extractor:
resolution: 7
sampling_ratio: 0
aligned: True
bbox_assigner: BBoxAssigner
BBoxAssigner:
batch_size_per_im: 512
bg_thresh: 0.5
fg_thresh: 0.5
fg_fraction: 0.25
use_random: True
TwoFCHead:
out_channel: 1024
BBoxPostProcess:
decode: RCNNBox
nms:
name: MultiClassNMS
keep_top_k: 100
score_threshold: 0.05
nms_threshold: 0.5

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worker_num: 2
TrainReader:
sample_transforms:
- Decode: {}
- RandomResize: {target_size: [[640, 1333], [672, 1333], [704, 1333], [736, 1333], [768, 1333], [800, 1333]], interp: 2, keep_ratio: True}
- RandomFlip: {prob: 0.5}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: -1}
batch_size: 1
shuffle: true
drop_last: true
collate_batch: false
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: -1}
batch_size: 1
shuffle: false
drop_last: false
TestReader:
sample_transforms:
- Decode: {}
- Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: -1}
batch_size: 1
shuffle: false
drop_last: false

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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
OptimizerBuilder:
optimizer:
momentum: 0.9
type: Momentum
regularizer:
factor: 0.0001
type: L2

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paddle_detection/configs/faster_rcnn/_base_/optimizer_swin_1x.yml Normal file
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epoch: 12
LearningRate:
base_lr: 0.0001
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [8, 11]
- !LinearWarmup
start_factor: 0.1
steps: 1000
OptimizerBuilder:
clip_grad_by_norm: 1.0
optimizer:
type: AdamW
weight_decay: 0.05
param_groups:
- params: ['absolute_pos_embed', 'relative_position_bias_table', 'norm']
weight_decay: 0.0

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paddle_detection/configs/faster_rcnn/faster_rcnn_r101_1x_coco.yml Normal file
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_BASE_: [
'faster_rcnn_r50_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams
weights: output/faster_rcnn_r101_1x_coco/model_final
ResNet:
# index 0 stands for res2
depth: 101
norm_type: bn
freeze_at: 0
return_idx: [2]
num_stages: 3

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paddle_detection/configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.yml Normal file
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_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams
weights: output/faster_rcnn_r101_fpn_1x_coco/model_final
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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paddle_detection/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.yml Normal file
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_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams
weights: output/faster_rcnn_r101_fpn_2x_coco/model_final
ResNet:
# index 0 stands for res2
depth: 101
norm_type: bn
freeze_at: 0
return_idx: [0,1,2,3]
num_stages: 4
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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paddle_detection/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_1x_coco.yml Normal file
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_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams
weights: output/faster_rcnn_r101_vd_fpn_1x_coco/model_final
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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paddle_detection/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_2x_coco.yml Normal file
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_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams
weights: output/faster_rcnn_r101_vd_fpn_2x_coco/model_final
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: 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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paddle_detection/configs/faster_rcnn/faster_rcnn_r34_fpn_1x_coco.yml Normal file
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_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_pretrained.pdparams
weights: output/faster_rcnn_r34_fpn_1x_coco/model_final
ResNet:
# index 0 stands for res2
depth: 34
norm_type: bn
freeze_at: 0
return_idx: [0,1,2,3]
num_stages: 4

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paddle_detection/configs/faster_rcnn/faster_rcnn_r34_fpn_multiscaletest_1x_coco.yml Normal file
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_BASE_: [
'faster_rcnn_r34_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_pretrained.pdparams
weights: output/faster_rcnn_r34_fpn_multiscaletest_1x_coco/model_final
EvalReader:
sample_transforms:
- Decode: {}
# - Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True}
- MultiscaleTestResize: {origin_target_size: [800, 1333], target_size: [700 , 900], use_flip: False}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
TestReader:
sample_transforms:
- Decode: {}
# - Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True}
- MultiscaleTestResize: {origin_target_size: [800, 1333], target_size: [700 , 900], use_flip: False}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}

15
paddle_detection/configs/faster_rcnn/faster_rcnn_r34_vd_fpn_1x_coco.yml Normal file
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@@ -0,0 +1,15 @@
_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_vd_pretrained.pdparams
weights: output/faster_rcnn_r34_vd_fpn_1x_coco/model_final
ResNet:
# index 0 stands for res2
depth: 34
variant: d
norm_type: bn
freeze_at: 0
return_idx: [0,1,2,3]
num_stages: 4

8
paddle_detection/configs/faster_rcnn/faster_rcnn_r50_1x_coco.yml Normal file
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@@ -0,0 +1,8 @@
_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'_base_/optimizer_1x.yml',
'_base_/faster_rcnn_r50.yml',
'_base_/faster_reader.yml',
]
weights: output/faster_rcnn_r50_1x_coco/model_final

8
paddle_detection/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.yml Normal file
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@@ -0,0 +1,8 @@
_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'_base_/optimizer_1x.yml',
'_base_/faster_rcnn_r50_fpn.yml',
'_base_/faster_fpn_reader.yml',
]
weights: output/faster_rcnn_r50_fpn_1x_coco/model_final

15
paddle_detection/configs/faster_rcnn/faster_rcnn_r50_fpn_2x_coco.yml Normal file
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@@ -0,0 +1,15 @@
_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
weights: output/faster_rcnn_r50_fpn_2x_coco/model_final
epoch: 24
LearningRate:
base_lr: 0.01
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [16, 22]
- !LinearWarmup
start_factor: 0.1
steps: 1000

14
paddle_detection/configs/faster_rcnn/faster_rcnn_r50_vd_1x_coco.yml Normal file
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@@ -0,0 +1,14 @@
_BASE_: [
'faster_rcnn_r50_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams
weights: output/faster_rcnn_r50_vd_1x_coco/model_final
ResNet:
# index 0 stands for res2
depth: 50
variant: d
norm_type: bn
freeze_at: 0
return_idx: [2]
num_stages: 3

14
paddle_detection/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_1x_coco.yml Normal file
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@@ -0,0 +1,14 @@
_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams
weights: output/faster_rcnn_r50_vd_fpn_1x_coco/model_final
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

25
paddle_detection/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_2x_coco.yml Normal file
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@@ -0,0 +1,25 @@
_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams
weights: output/faster_rcnn_r50_vd_fpn_2x_coco/model_final
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
epoch: 24
LearningRate:
base_lr: 0.01
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [16, 22]
- !LinearWarmup
start_factor: 0.1
steps: 1000

29
paddle_detection/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml Normal file
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@@ -0,0 +1,29 @@
_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'_base_/optimizer_1x.yml',
'_base_/faster_rcnn_r50_fpn.yml',
'_base_/faster_fpn_reader.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams
weights: output/faster_rcnn_r50_vd_fpn_ssld_1x_coco/model_final
ResNet:
depth: 50
variant: d
norm_type: bn
freeze_at: 0
return_idx: [0,1,2,3]
num_stages: 4
lr_mult_list: [0.05, 0.05, 0.1, 0.15]
epoch: 12
LearningRate:
base_lr: 0.01
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [8, 11]
- !LinearWarmup
start_factor: 0.1
steps: 1000

29
paddle_detection/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml Normal file
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@@ -0,0 +1,29 @@
_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'_base_/optimizer_1x.yml',
'_base_/faster_rcnn_r50_fpn.yml',
'_base_/faster_fpn_reader.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams
weights: output/faster_rcnn_r50_vd_fpn_ssld_2x_coco/model_final
ResNet:
depth: 50
variant: d
norm_type: bn
freeze_at: 0
return_idx: [0,1,2,3]
num_stages: 4
lr_mult_list: [0.05, 0.05, 0.1, 0.15]
epoch: 24
LearningRate:
base_lr: 0.01
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [12, 22]
- !LinearWarmup
start_factor: 0.1
steps: 1000

8
paddle_detection/configs/faster_rcnn/faster_rcnn_swin_tiny_fpn_1x_coco.yml Normal file
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@@ -0,0 +1,8 @@
_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'_base_/optimizer_swin_1x.yml',
'_base_/faster_rcnn_swin_tiny_fpn.yml',
'_base_/faster_rcnn_swin_reader.yml',
]
weights: output/faster_rcnn_swin_tiny_fpn_1x_coco/model_final

16
paddle_detection/configs/faster_rcnn/faster_rcnn_swin_tiny_fpn_2x_coco.yml Normal file
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@@ -0,0 +1,16 @@
_BASE_: [
'faster_rcnn_swin_tiny_fpn_1x_coco.yml',
]
weights: output/faster_rcnn_swin_tiny_fpn_2x_coco/model_final
epoch: 24
LearningRate:
base_lr: 0.0001
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [16, 22]
- !LinearWarmup
start_factor: 0.1
steps: 1000

17
paddle_detection/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.yml Normal file
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@@ -0,0 +1,17 @@
_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams
weights: output/faster_rcnn_x101_vd_64x4d_fpn_1x_coco/model_final
ResNet:
# for ResNeXt: groups, base_width, base_channels
depth: 101
groups: 64
base_width: 4
variant: d
norm_type: bn
freeze_at: 0
return_idx: [0,1,2,3]
num_stages: 4

28
paddle_detection/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml Normal file
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@@ -0,0 +1,28 @@
_BASE_: [
'faster_rcnn_r50_fpn_1x_coco.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams
weights: output/faster_rcnn_x101_vd_64x4d_fpn_2x_coco/model_final
ResNet:
# for ResNeXt: groups, base_width, base_channels
depth: 101
groups: 64
base_width: 4
variant: d
norm_type: bn
freeze_at: 0
return_idx: [0,1,2,3]
num_stages: 4
epoch: 24
LearningRate:
base_lr: 0.01
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [16, 22]
- !LinearWarmup
start_factor: 0.1
steps: 1000