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PaddleDetection
未验证 提交 521a4a6a 编写于 作者: G Guanghua Yu 提交者： GitHub
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add config link in model zoo (#529) 

* add config link in model zoo

* fix link error

* add anchor free
上级 fb82692a
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configs/anchor_free/README.md
浏览文件 @ 521a4a6a
......@@ -22,15 +22,15 @@
#### COCO数据集上的mAP
| 网络结构 | 骨干网络 | 图片个数/GPU | 预训练模型 | mAP | FPS | 模型下载 |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|
| CornerNet-Squeeze | Hourglass104 | 14 | 无 | 34.5 | 35.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_hg104.tar) |
| CornerNet-Squeeze | ResNet50-vd | 14 | [faster\_rcnn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | 32.7 | 42.45 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_r50_vd_fpn.tar) |
| CornerNet-Squeeze-dcn | ResNet50-vd | 14 | [faster\_rcnn\_dcn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | 34.9 | 40.05 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_dcn_r50_vd_fpn.tar) |
| CornerNet-Squeeze-dcn-mixup-cosine* | ResNet50-vd | 14 | [faster\_rcnn\_dcn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | 38.2 | 40.05 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_dcn_r50_vd_fpn_mixup_cosine.pdparams) |
| FCOS | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 39.8 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_r50_fpn_1x.pdparams) |
| FCOS+multiscale_train | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 42.0 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_r50_fpn_multiscale_2x.pdparams) |
| FCOS+DCN | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 44.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_dcn_r50_fpn_1x.pdparams) |
| 网络结构 | 骨干网络 | 图片个数/GPU | 预训练模型 | mAP | FPS | 模型下载 | 配置文件 |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:----------:|
| CornerNet-Squeeze | Hourglass104 | 14 | 无 | 34.5 | 35.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_hg104.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/cornernet_squeeze_hg104.yml) |
| CornerNet-Squeeze | ResNet50-vd | 14 | [faster\_rcnn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | 32.7 | 42.45 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_r50_vd_fpn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/cornernet_squeeze_r50_vd_fpn.yml) |
| CornerNet-Squeeze-dcn | ResNet50-vd | 14 | [faster\_rcnn\_dcn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | 34.9 | 40.05 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_dcn_r50_vd_fpn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/cornernet_squeeze_dcn_r50_vd_fpn.yml) |
| CornerNet-Squeeze-dcn-mixup-cosine* | ResNet50-vd | 14 | [faster\_rcnn\_dcn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | 38.2 | 40.05 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_dcn_r50_vd_fpn_mixup_cosine.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/cornernet_squeeze_dcn_r50_vd_fpn_mixup_cosine.yml) |
| FCOS | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 39.8 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_r50_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/fcos_r50_fpn_1x.yml) |
| FCOS+multiscale_train | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 42.0 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_r50_fpn_multiscale_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/fcos_r50_fpn_multiscale_2x.yml) |
| FCOS+DCN | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 44.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_dcn_r50_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/fcos_dcn_r50_fpn_1x.yml) |
**注意:**
......
configs/anchor_free/cornernet_squeeze.yml → configs/anchor_free/cornernet_squeeze_hg104.yml
浏览文件 @ 521a4a6a
......@@ -7,7 +7,7 @@ save_dir: output
snapshot_iter: 10000
metric: COCO
pretrain_weights: NULL
weights: output/cornernet_squeeze/model_final
weights: output/cornernet_squeeze_hg104/model_final
num_classes: 80
stack: 2
......
configs/autoaugment/README.md
浏览文件 @ 521a4a6a
......@@ -17,7 +17,7 @@
## Model Zoo
| Backbone | Type | AutoAug policy | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :-------------:| :-------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50-vd-FPN | Faster | v1 | 2 | 3x | 22.800 | 39.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_aa_3x.tar) |
| ResNet101-vd-FPN | Faster | v1 | 2 | 3x | 17.652 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_aa_3x.tar) |
| Backbone | Type | AutoAug policy | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------:| :-------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-FPN | Faster | v1 | 2 | 3x | 22.800 | 39.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_aa_3x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/autoaugment/faster_rcnn_r50_vd_fpn_aa_3x.yml) |
| ResNet101-vd-FPN | Faster | v1 | 2 | 3x | 17.652 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_aa_3x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/autoaugment/faster_rcnn_r101_vd_fpn_aa_3x.yml) |
configs/gcnet/README.md
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## Model Zoo
| Backbone | Type | Context| Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :-------------: | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50-vd-FPN | Mask | GC(c3-c5, r16, add) | 2 | 2x | 15.31 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.tar) |
| ResNet50-vd-FPN | Mask | GC(c3-c5, r16, mul) | 2 | 2x | 15.35 | 40.7 | 36.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.tar) |
| Backbone | Type | Context| Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-FPN | Mask | GC(c3-c5, r16, add) | 2 | 2x | 15.31 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.yml) |
| ResNet50-vd-FPN | Mask | GC(c3-c5, r16, mul) | 2 | 2x | 15.35 | 40.7 | 36.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.yml) |
configs/hrnet/README.md
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## Model Zoo
| Backbone | Type | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| HRNetV2p_W18 | Faster | False | 2 | 1x | 17.509 | 36.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_1x.tar) |
| HRNetV2p_W18 | Faster | False | 2 | 2x | 17.509 | 38.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_2x.tar) |
| Backbone | Type | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| HRNetV2p_W18 | Faster | False | 2 | 1x | 17.509 | 36.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x.yml) |
| HRNetV2p_W18 | Faster | False | 2 | 2x | 17.509 | 38.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x.yml) |
configs/iou_loss/README.md
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## Model Zoo
| Backbone | Type | Loss Type | Loss Weight | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :------------- | :---: | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50-vd-FPN | Faster | GIOU | 10 | 2 | 1x | 22.94 | 39.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_giou_loss_1x.tar) |
| ResNet50-vd-FPN | Faster | DIOU | 12 | 2 | 1x | 22.94 | 39.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_diou_loss_1x.tar) |
| ResNet50-vd-FPN | Faster | CIOU | 12 | 2 | 1x | 22.95 | 39.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_ciou_loss_1x.tar) |
| Backbone | Type | Loss Type | Loss Weight | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---: | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :---: |
| ResNet50-vd-FPN | Faster | GIOU | 10 | 2 | 1x | 22.94 | 39.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_giou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_giou_loss_1x.yml) |
| ResNet50-vd-FPN | Faster | DIOU | 12 | 2 | 1x | 22.94 | 39.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_diou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_diou_loss_1x.yml) |
| ResNet50-vd-FPN | Faster | CIOU | 12 | 2 | 1x | 22.95 | 39.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_ciou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_ciou_loss_1x.yml) |
configs/libra_rcnn/README.md
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## Model Zoo
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50-vd-BFP | Faster | 2 | 1x | 18.247 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r50_vd_fpn_1x.tar) |
| ResNet101-vd-BFP | Faster | 2 | 1x | 14.865 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r101_vd_fpn_1x.tar) |
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-BFP | Faster | 2 | 1x | 18.247 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r50_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/libra_rcnn/libra_rcnn_r50_vd_fpn_1x.yml) |
| ResNet101-vd-BFP | Faster | 2 | 1x | 14.865 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/libra_rcnn/libra_rcnn_r101_vd_fpn_1x.yml) |
configs/rcnn_server_side_det/README.md
浏览文件 @ 521a4a6a
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## Model Zoo
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) |
| ResNet50-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 20.001 | 47.8 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) |
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_server_side_det/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) |
| ResNet50-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 20.001 | 47.8 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_server_side_det/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) |
configs/res2net/README.md
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## Model Zoo
| Backbone | Type | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| Res2Net50-FPN | Faster | False | 2 | 1x | 20.320 | 39.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_res2net50_vb_26w_4s_fpn_1x.tar) |
| Res2Net50-FPN | Mask | False | 2 | 2x | 16.069 | 40.7 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vb_26w_4s_fpn_2x.tar) |
| Res2Net50-vd-FPN | Mask | False | 2 | 2x | 15.816 | 40.9 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vd_26w_4s_fpn_2x.tar) |
| Res2Net50-vd-FPN | Mask | True | 2 | 2x | 14.478 | 43.5 | 38.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vd_26w_4s_fpn_dcnv2_1x.tar) |
| Backbone | Type | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| Res2Net50-FPN | Faster | False | 2 | 1x | 20.320 | 39.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_res2net50_vb_26w_4s_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_1x.yml) |
| Res2Net50-FPN | Mask | False | 2 | 2x | 16.069 | 40.7 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vb_26w_4s_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_2x.yml) |
| Res2Net50-vd-FPN | Mask | False | 2 | 2x | 15.816 | 40.9 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vd_26w_4s_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_2x.yml) |
| Res2Net50-vd-FPN | Mask | True | 2 | 2x | 14.478 | 43.5 | 38.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vd_26w_4s_fpn_dcnv2_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_dcnv2_1x.yml) |
docs/MODEL_ZOO.md
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......@@ -34,57 +34,57 @@ The backbone models pretrained on ImageNet are available. All backbone models ar
### Faster & Mask R-CNN
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50 | Faster | 1 | 1x | 12.747 | 35.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_1x.tar) |
| ResNet50 | Faster | 1 | 2x | 12.686 | 37.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_2x.tar) |
| ResNet50 | Mask | 1 | 1x | 11.615 | 36.5 | 32.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_1x.tar) |
| ResNet50 | Mask | 1 | 2x | 11.494 | 38.2 | 33.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_2x.tar) |
| ResNet50-vd | Faster | 1 | 1x | 12.575 | 36.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_1x.tar) |
| ResNet50-FPN | Faster | 2 | 1x | 22.273 | 37.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_1x.tar) |
| ResNet50-FPN | Faster | 2 | 2x | 22.297 | 37.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar) |
| ResNet50-FPN | Mask | 1 | 1x | 15.184 | 37.9 | 34.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_1x.tar) |
| ResNet50-FPN | Mask | 1 | 2x | 15.881 | 38.7 | 34.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar) |
| ResNet50-FPN | Cascade Faster | 2 | 1x | 17.507 | 40.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_r50_fpn_1x.tar) |
| ResNet50-FPN | Cascade Mask | 1 | 1x | - | 41.3 | 35.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_r50_fpn_1x.tar) |
| ResNet50-vd-FPN | Faster | 2 | 2x | 21.847 | 38.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) |
| ResNet50-vd-FPN | Mask | 1 | 2x | 15.825 | 39.8 | 35.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar) |
| CBResNet50-vd-FPN | Faster | 2 | 1x | - | 39.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr50_vd_dual_fpn_1x.tar) |
| ResNet101 | Faster | 1 | 1x | 9.316 | 38.3 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_1x.tar) |
| ResNet101-FPN | Faster | 1 | 1x | 17.297 | 38.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_1x.tar) |
| ResNet101-FPN | Faster | 1 | 2x | 17.246 | 39.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar) |
| ResNet101-FPN | Mask | 1 | 1x | 12.983 | 39.5 | 35.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_fpn_1x.tar) |
| ResNet101-vd-FPN | Faster | 1 | 1x | 17.011 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_1x.tar) |
| ResNet101-vd-FPN | Faster | 1 | 2x | 16.934 | 40.8 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar) |
| ResNet101-vd-FPN | Mask | 1 | 1x | 13.105 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar) |
| CBResNet101-vd-FPN | Faster | 2 | 1x | - | 42.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr101_vd_dual_fpn_1x.tar) |
| ResNeXt101-vd-64x4d-FPN | Faster | 1 | 1x | 8.815 | 42.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_1x.tar) |
| ResNeXt101-vd-64x4d-FPN | Faster | 1 | 2x | 8.809 | 41.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_2x.tar) |
| ResNeXt101-vd-64x4d-FPN | Mask | 1 | 1x | 7.689 | 42.9 | 37.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_1x.tar) |
| ResNeXt101-vd-64x4d-FPN | Mask | 1 | 2x | 7.859 | 42.6 | 37.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_2x.tar) |
| SENet154-vd-FPN | Faster | 1 | 1.44x | 3.408 | 42.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_se154_vd_fpn_s1x.tar) |
| SENet154-vd-FPN | Mask | 1 | 1.44x | 3.233 | 44.0 | 38.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_se154_vd_fpn_s1x.tar) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 44.7(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 46.5(multi-scale test) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) |
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :----: |
| ResNet50 | Faster | 1 | 1x | 12.747 | 35.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_1x.yml) |
| ResNet50 | Faster | 1 | 2x | 12.686 | 37.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_2x.yml) |
| ResNet50 | Mask | 1 | 1x | 11.615 | 36.5 | 32.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_1x.yml) |
| ResNet50 | Mask | 1 | 2x | 11.494 | 38.2 | 33.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_2x.yml) |
| ResNet50-vd | Faster | 1 | 1x | 12.575 | 36.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_vd_1x.yml) |
| ResNet50-FPN | Faster | 2 | 1x | 22.273 | 37.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Faster | 2 | 2x | 22.297 | 37.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_fpn_2x.yml) |
| ResNet50-FPN | Mask | 1 | 1x | 15.184 | 37.9 | 34.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Mask | 1 | 2x | 15.881 | 38.7 | 34.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_fpn_2x.yml) |
| ResNet50-FPN | Cascade Faster | 2 | 1x | 17.507 | 40.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Cascade Mask | 1 | 1x | - | 41.3 | 35.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_mask_rcnn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Faster | 2 | 2x | 21.847 | 38.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_vd_fpn_2x.yml) |
| ResNet50-vd-FPN | Mask | 1 | 2x | 15.825 | 39.8 | 35.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_vd_fpn_2x.yml) |
| CBResNet50-vd-FPN | Faster | 2 | 1x | - | 39.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr50_vd_dual_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_cbr50_vd_dual_fpn_1x.yml) |
| ResNet101 | Faster | 1 | 1x | 9.316 | 38.3 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_1x.yml) |
| ResNet101-FPN | Faster | 1 | 1x | 17.297 | 38.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_fpn_1x.yml) |
| ResNet101-FPN | Faster | 1 | 2x | 17.246 | 39.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_fpn_2x.yml) |
| ResNet101-FPN | Mask | 1 | 1x | 12.983 | 39.5 | 35.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r101_fpn_1x.yml) |
| ResNet101-vd-FPN | Faster | 1 | 1x | 17.011 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_vd_fpn_1x.yml) |
| ResNet101-vd-FPN | Faster | 1 | 2x | 16.934 | 40.8 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Mask | 1 | 1x | 13.105 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r101_vd_fpn_1x.yml) |
| CBResNet101-vd-FPN | Faster | 2 | 1x | - | 42.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr101_vd_dual_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_cbr101_vd_dual_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Faster | 1 | 1x | 8.815 | 42.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_x101_vd_64x4d_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Faster | 1 | 2x | 8.809 | 41.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_x101_vd_64x4d_fpn_2x.yml) |
| ResNeXt101-vd-64x4d-FPN | Mask | 1 | 1x | 7.689 | 42.9 | 37.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_x101_vd_64x4d_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Mask | 1 | 2x | 7.859 | 42.6 | 37.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_x101_vd_64x4d_fpn_2x.yml) |
| SENet154-vd-FPN | Faster | 1 | 1.44x | 3.408 | 42.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_se154_vd_fpn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_se154_vd_fpn_s1x.yml) |
| SENet154-vd-FPN | Mask | 1 | 1.44x | 3.233 | 44.0 | 38.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_se154_vd_fpn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_se154_vd_fpn_s1x.yml) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 44.7(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 46.5(multi-scale test) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) |
### Deformable ConvNets v2
| Backbone | Type | Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50-FPN | Faster | c3-c5 | 2 | 1x | 19.978 | 41.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_fpn_1x.tar) |
| ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | 19.222 | 42.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) |
| ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | 14.477 | 44.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r101_vd_fpn_1x.tar) |
| ResNeXt101-vd-64x4d-FPN | Faster | c3-c5 | 1 | 1x | 7.209 | 45.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |
| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | 14.53 | 41.9 | 37.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_fpn_1x.tar) |
| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | 14.832 | 42.9 | 38.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_vd_fpn_2x.tar) |
| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | 11.546 | 44.6 | 39.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r101_vd_fpn_1x.tar) |
| ResNeXt101-vd-64x4d-FPN | Mask | c3-c5 | 1 | 1x | 6.45 | 46.2 | 40.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |
| ResNet50-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 44.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_fpn_1x.tar) |
| ResNet101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 46.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_1x.tar) |
| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 47.3 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |
| SENet154-vd-FPN | Cascade Mask | c3-c5 | 1 | 1.44x | - | 51.9 | 43.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.tar) |
| ResNet200-vd-FPN-Nonlocal | CascadeClsAware Faster | c3-c5 | 1 | 2.5x | - | 51.7%(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) |
| CBResNet200-vd-FPN-Nonlocal | Cascade Faster | c3-c5 | 1 | 2.5x | - | 53.3%(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.tar) |
| Backbone | Type | Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :----: |
| ResNet50-FPN | Faster | c3-c5 | 2 | 1x | 19.978 | 41.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | 19.222 | 42.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | 14.477 | 44.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Faster | c3-c5 | 1 | 1x | 7.209 | 45.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | 14.53 | 41.9 | 37.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | 14.832 | 42.9 | 38.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | 11.546 | 44.6 | 39.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Mask | c3-c5 | 1 | 1x | 6.45 | 46.2 | 40.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| ResNet50-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 44.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 46.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 47.3 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| SENet154-vd-FPN | Cascade Mask | c3-c5 | 1 | 1.44x | - | 51.9 | 43.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.yml) |
| ResNet200-vd-FPN-Nonlocal | CascadeClsAware Faster | c3-c5 | 1 | 2.5x | - | 51.7%(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
| CBResNet200-vd-FPN-Nonlocal | Cascade Faster | c3-c5 | 1 | 2.5x | - | 53.3%(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
**Notes:**
......@@ -107,13 +107,18 @@ The backbone models pretrained on ImageNet are available. All backbone models ar
### GCNet
* See more details in [GCNet model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/gcnet/).
### Libra R-CNN
* See more details in [Libra R-CNN model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/libra_rcnn/).
### Auto Augmentation
* See more details in [Auto Augmentation model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/autoaugment/).
### Group Normalization
| Backbone | Type | Image/gpu | Lr schd | Box AP | Mask AP | Download |
| :------------------- | :------------- | :-----: | :-----: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50-FPN | Faster | 2 | 2x | 39.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_gn_2x.tar) |
| ResNet50-FPN | Mask | 1 | 2x | 40.1 | 35.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_gn_2x.tar) |
| Backbone | Type | Image/gpu | Lr schd | Box AP | Mask AP | Download | Configs |
| :------------------- | :------------- | :-----: | :-----: | :----: | :-----: | :----------------------------------------------------------: |:----: |
| ResNet50-FPN | Faster | 2 | 2x | 39.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_gn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn/faster_rcnn_r50_fpn_gn_2x.yml) |
| ResNet50-FPN | Mask | 1 | 2x | 40.1 | 35.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_gn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn/mask_rcnn_r50_fpn_gn_2x.yml) |
**Notes:**
......@@ -122,39 +127,39 @@ The backbone models pretrained on ImageNet are available. All backbone models ar
### YOLO v3
| Backbone | Pretrain dataset | Size | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download |
| :----------- | :--------: | :-----: | :-----: |:------------: |:----: | :-------: | :----: | :-------: |
| DarkNet53 (paper) | ImageNet | 608 | False | 8 | 270e | - | 33.0 | - |
| DarkNet53 (paper) | ImageNet | 416 | False | 8 | 270e | - | 31.0 | - |
| DarkNet53 (paper) | ImageNet | 320 | False | 8 | 270e | - | 28.2 | - |
| DarkNet53 | ImageNet | 608 | False | 8 | 270e | 45.571 | 38.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) |
| DarkNet53 | ImageNet | 416 | False | 8 | 270e | - | 37.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) |
| DarkNet53 | ImageNet | 320 | False | 8 | 270e | - | 34.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) |
| MobileNet-V1 | ImageNet | 608 | False | 8 | 270e | 78.302 | 29.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) |
| MobileNet-V1 | ImageNet | 416 | False | 8 | 270e | - | 29.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) |
| MobileNet-V1 | ImageNet | 320 | False | 8 | 270e | - | 27.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) |
| MobileNet-V3 | ImageNet | 608 | False | 8 | 270e | - | 31.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) |
| MobileNet-V3 | ImageNet | 416 | False | 8 | 270e | - | 29.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) |
| MobileNet-V3 | ImageNet | 320 | False | 8 | 270e | - | 27.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) |
| ResNet34 | ImageNet | 608 | False | 8 | 270e | 63.356 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) |
| ResNet34 | ImageNet | 416 | False | 8 | 270e | - | 34.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) |
| ResNet34 | ImageNet | 320 | False | 8 | 270e | - | 31.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) |
| ResNet50_vd | ImageNet | 608 | True | 8 | 270e | - | 39.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn.tar) |
| ResNet50_vd | Object365 | 608 | True | 8 | 270e | - | 41.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_pretrained_coco.tar) |
| Backbone | Pretrain dataset | Size | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs |
| :----------- | :--------: | :-----: | :-----: |:------------: |:----: | :-------: | :----: | :-------: | :----: |
| DarkNet53 (paper) | ImageNet | 608 | False | 8 | 270e | - | 33.0 | - | - |
| DarkNet53 (paper) | ImageNet | 416 | False | 8 | 270e | - | 31.0 | - | - |
| DarkNet53 (paper) | ImageNet | 320 | False | 8 | 270e | - | 28.2 | - | - |
| DarkNet53 | ImageNet | 608 | False | 8 | 270e | 45.571 | 38.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) |
| DarkNet53 | ImageNet | 416 | False | 8 | 270e | - | 37.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) |
| DarkNet53 | ImageNet | 320 | False | 8 | 270e | - | 34.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) |
| MobileNet-V1 | ImageNet | 608 | False | 8 | 270e | 78.302 | 29.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V1 | ImageNet | 416 | False | 8 | 270e | - | 29.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V1 | ImageNet | 320 | False | 8 | 270e | - | 27.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V3 | ImageNet | 608 | False | 8 | 270e | - | 31.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) |
| MobileNet-V3 | ImageNet | 416 | False | 8 | 270e | - | 29.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) |
| MobileNet-V3 | ImageNet | 320 | False | 8 | 270e | - | 27.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) |
| ResNet34 | ImageNet | 608 | False | 8 | 270e | 63.356 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) |
| ResNet34 | ImageNet | 416 | False | 8 | 270e | - | 34.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) |
| ResNet34 | ImageNet | 320 | False | 8 | 270e | - | 31.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) |
| ResNet50_vd | ImageNet | 608 | True | 8 | 270e | - | 39.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/dcn/yolov3_r50vd_dcn.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn.yml) |
| ResNet50_vd | Object365 | 608 | True | 8 | 270e | - | 41.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_pretrained_coco.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) |
### YOLO v3 on Pascal VOC
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download |
| :----------- | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: |
| DarkNet53 | 608 | 8 | 270e | 54.977 | 83.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) |
| DarkNet53 | 416 | 8 | 270e | - | 83.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) |
| DarkNet53 | 320 | 8 | 270e | - | 82.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) |
| MobileNet-V1 | 608 | 8 | 270e | 104.291 | 76.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) |
| MobileNet-V1 | 416 | 8 | 270e | - | 76.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) |
| MobileNet-V1 | 320 | 8 | 270e | - | 75.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) |
| ResNet34 | 608 | 8 | 270e | 82.247 | 82.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) |
| ResNet34 | 416 | 8 | 270e | - | 81.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) |
| ResNet34 | 320 | 8 | 270e | - | 80.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) |
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs |
| :----------- | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: |
| DarkNet53 | 608 | 8 | 270e | 54.977 | 83.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) |
| DarkNet53 | 416 | 8 | 270e | - | 83.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) |
| DarkNet53 | 320 | 8 | 270e | - | 82.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) |
| MobileNet-V1 | 608 | 8 | 270e | 104.291 | 76.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) |
| MobileNet-V1 | 416 | 8 | 270e | - | 76.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) |
| MobileNet-V1 | 320 | 8 | 270e | - | 75.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) |
| ResNet34 | 608 | 8 | 270e | 82.247 | 82.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) |
| ResNet34 | 416 | 8 | 270e | - | 81.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) |
| ResNet34 | 320 | 8 | 270e | - | 80.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) |
**Notes:**
......@@ -168,39 +173,39 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of
### RetinaNet
| Backbone | Image/gpu | Lr schd | Box AP | Download |
| :---------------: | :-----: | :-----: | :----: | :-------: |
| ResNet50-FPN | 2 | 1x | 36.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r50_fpn_1x.tar) |
| ResNet101-FPN | 2 | 1x | 37.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r101_fpn_1x.tar) |
| ResNeXt101-vd-FPN | 1 | 1x | 40.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_x101_vd_64x4d_fpn_1x.tar) |
| Backbone | Image/gpu | Lr schd | Box AP | Download | Configs |
| :---------------: | :-----: | :-----: | :----: | :-------: | :----: |
| ResNet50-FPN | 2 | 1x | 36.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_r50_fpn_1x.yml) |
| ResNet101-FPN | 2 | 1x | 37.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_r101_fpn_1x.yml) |
| ResNeXt101-vd-FPN | 1 | 1x | 40.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_x101_vd_64x4d_fpn_1x.yml) |
**Notes:** In RetinaNet, the base LR is changed to 0.01 for minibatch size 16.
### SSDLite
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download |
| :------: | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: |
| MobileNet_v3 small | 320 | 64 | 40w | - | 16.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobilenet_v3_ssdlite_small.tar) |
| MobileNet_v3 large | 320 | 64 | 40w | - | 22.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobilenet_v3_ssdlite_large.tar) |
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs |
| :------: | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: |
| MobileNet_v3 small | 320 | 64 | 40w | - | 16.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobilenet_v3_ssdlite_small.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_small.yml) |
| MobileNet_v3 large | 320 | 64 | 40w | - | 22.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobilenet_v3_ssdlite_large.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_large.yml) |
**Notes:** MobileNet_v3-SSDLite is trained in 8 GPU with total batch size as 512 and uses cosine decay strategy to train.
### SSD
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download |
| :------: | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: |
| VGG16 | 300 | 8 | 40w | 81.613 | 25.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300.tar) |
| VGG16 | 512 | 8 | 40w | 46.007 | 29.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512.tar) |
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs |
| :------: | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: |
| VGG16 | 300 | 8 | 40w | 81.613 | 25.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_300.yml) |
| VGG16 | 512 | 8 | 40w | 46.007 | 29.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_512.yml) |
**Notes:** VGG-SSD is trained in 4 GPU with total batch size as 32 and trained 400000 iters.
### SSD on Pascal VOC
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download |
| :----------- | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: |
| MobileNet v1 | 300 | 32 | 120e | 159.543 | 73.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar) |
| VGG16 | 300 | 8 | 240e | 117.279 | 77.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300_voc.tar) |
| VGG16 | 512 | 8 | 240e | 65.975 | 80.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512_voc.tar) |
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs |
| :----------- | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: |
| MobileNet v1 | 300 | 32 | 120e | 159.543 | 73.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_mobilenet_v1_voc.yml) |
| VGG16 | 300 | 8 | 240e | 117.279 | 77.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_300_voc.yml) |
| VGG16 | 512 | 8 | 240e | 65.975 | 80.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_512_voc.yml) |
**NOTE**: MobileNet-SSD is trained in 2 GPU with totoal batch size as 64 and trained 120 epoches. VGG-SSD is trained in 4 GPU with total batch size as 32 and trained 240 epoches. SSD training data augmentations: randomly color distortion,
randomly cropping, randomly expansion, randomly flipping.
......
docs/MODEL_ZOO_cn.md
浏览文件 @ 521a4a6a
......@@ -31,57 +31,57 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
### Faster & Mask R-CNN
| 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 | Mask AP | 下载 |
| :------------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: |
| ResNet50 | Faster | 1 | 1x | 12.747 | 35.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_1x.tar) |
| ResNet50 | Faster | 1 | 2x | 12.686 | 37.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_2x.tar) |
| ResNet50 | Mask | 1 | 1x | 11.615 | 36.5 | 32.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_1x.tar) |
| ResNet50 | Mask | 1 | 2x | 11.494 | 38.2 | 33.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_2x.tar) |
| ResNet50-vd | Faster | 1 | 1x | 12.575 | 36.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_1x.tar) |
| ResNet50-FPN | Faster | 2 | 1x | 22.273 | 37.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_1x.tar) |
| ResNet50-FPN | Faster | 2 | 2x | 22.297 | 37.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar) |
| ResNet50-FPN | Mask | 1 | 1x | 15.184 | 37.9 | 34.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_1x.tar) |
| ResNet50-FPN | Mask | 1 | 2x | 15.881 | 38.7 | 34.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar) |
| ResNet50-FPN | Cascade Faster | 2 | 1x | 17.507 | 40.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_r50_fpn_1x.tar) |
| ResNet50-FPN | Cascade Mask | 1 | 1x | - | 41.3 | 35.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_r50_fpn_1x.tar) |
| ResNet50-vd-FPN | Faster | 2 | 2x | 21.847 | 38.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) |
| ResNet50-vd-FPN | Mask | 1 | 2x | 15.825 | 39.8 | 35.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar) |
| CBResNet50-vd-FPN | Faster | 2 | 1x | - | 39.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr50_vd_dual_fpn_1x.tar) |
| ResNet101 | Faster | 1 | 1x | 9.316 | 38.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_1x.tar) |
| ResNet101-FPN | Faster | 1 | 1x | 17.297 | 38.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_1x.tar) |
| ResNet101-FPN | Faster | 1 | 2x | 17.246 | 39.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar) |
| ResNet101-FPN | Mask | 1 | 1x | 12.983 | 39.5 | 35.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_fpn_1x.tar) |
| ResNet101-vd-FPN | Faster | 1 | 1x | 17.011 | 40.5 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_1x.tar) |
| ResNet101-vd-FPN | Faster | 1 | 2x | 16.934 | 40.8 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar) |
| ResNet101-vd-FPN | Mask | 1 | 1x | 13.105 | 41.4 | 36.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar) |
| CBResNet101-vd-FPN | Faster | 2 | 1x | - | 42.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr101_vd_dual_fpn_1x.tar) |
| ResNeXt101-vd-FPN | Faster | 1 | 1x | 8.815 | 42.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_1x.tar) |
| ResNeXt101-vd-FPN | Faster | 1 | 2x | 8.809 | 41.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_2x.tar) |
| ResNeXt101-vd-FPN | Mask | 1 | 1x | 7.689 | 42.9 | 37.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_1x.tar) |
| ResNeXt101-vd-FPN | Mask | 1 | 2x | 7.859 | 42.6 | 37.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_2x.tar) |
| SENet154-vd-FPN | Faster | 1 | 1.44x | 3.408 | 42.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_se154_vd_fpn_s1x.tar) |
| SENet154-vd-FPN | Mask | 1 | 1.44x | 3.233 | 44.0 | 38.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_se154_vd_fpn_s1x.tar) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 44.7(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 46.5(multi-scale test) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) |
| 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 | Mask AP | 下载 | 配置文件 |
| :------------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: |
| ResNet50 | Faster | 1 | 1x | 12.747 | 35.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_1x.yml) |
| ResNet50 | Faster | 1 | 2x | 12.686 | 37.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_2x.yml) |
| ResNet50 | Mask | 1 | 1x | 11.615 | 36.5 | 32.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_1x.yml) |
| ResNet50 | Mask | 1 | 2x | 11.494 | 38.2 | 33.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_2x.yml) |
| ResNet50-vd | Faster | 1 | 1x | 12.575 | 36.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_vd_1x.yml) |
| ResNet50-FPN | Faster | 2 | 1x | 22.273 | 37.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Faster | 2 | 2x | 22.297 | 37.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_fpn_2x.yml) |
| ResNet50-FPN | Mask | 1 | 1x | 15.184 | 37.9 | 34.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Mask | 1 | 2x | 15.881 | 38.7 | 34.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_fpn_2x.yml) |
| ResNet50-FPN | Cascade Faster | 2 | 1x | 17.507 | 40.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Cascade Mask | 1 | 1x | - | 41.3 | 35.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_mask_rcnn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Faster | 2 | 2x | 21.847 | 38.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_vd_fpn_2x.yml) |
| ResNet50-vd-FPN | Mask | 1 | 2x | 15.825 | 39.8 | 35.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_vd_fpn_2x.yml) |
| CBResNet50-vd-FPN | Faster | 2 | 1x | - | 39.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr50_vd_dual_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_cbr50_vd_dual_fpn_1x.yml) |
| ResNet101 | Faster | 1 | 1x | 9.316 | 38.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_1x.yml) |
| ResNet101-FPN | Faster | 1 | 1x | 17.297 | 38.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_fpn_1x.yml) |
| ResNet101-FPN | Faster | 1 | 2x | 17.246 | 39.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_fpn_2x.yml) |
| ResNet101-FPN | Mask | 1 | 1x | 12.983 | 39.5 | 35.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r101_fpn_1x.yml) |
| ResNet101-vd-FPN | Faster | 1 | 1x | 17.011 | 40.5 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_vd_fpn_1x.yml) |
| ResNet101-vd-FPN | Faster | 1 | 2x | 16.934 | 40.8 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Mask | 1 | 1x | 13.105 | 41.4 | 36.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r101_vd_fpn_1x.yml) |
| CBResNet101-vd-FPN | Faster | 2 | 1x | - | 42.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr101_vd_dual_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_cbr101_vd_dual_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Faster | 1 | 1x | 8.815 | 42.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_x101_vd_64x4d_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Faster | 1 | 2x | 8.809 | 41.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_x101_vd_64x4d_fpn_2x.yml) |
| ResNeXt101-vd-FPN | Mask | 1 | 1x | 7.689 | 42.9 | 37.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_x101_vd_64x4d_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Mask | 1 | 2x | 7.859 | 42.6 | 37.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_x101_vd_64x4d_fpn_2x.yml) |
| SENet154-vd-FPN | Faster | 1 | 1.44x | 3.408 | 42.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_se154_vd_fpn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_se154_vd_fpn_s1x.yml) |
| SENet154-vd-FPN | Mask | 1 | 1.44x | 3.233 | 44.0 | 38.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_se154_vd_fpn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_se154_vd_fpn_s1x.yml) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 44.7(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 46.5(multi-scale test) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) |
### Deformable 卷积网络v2
| 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 |
| :------------------- | :------------- | :-----: |:--------: | :-----: | :-----------: |:----: | :-----: | :----------------------------------------------------------: |
| ResNet50-FPN | Faster | c3-c5 | 2 | 1x | 19.978 | 41.0 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_fpn_1x.tar) |
| ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | 19.222 | 42.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) |
| ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | 14.477 | 44.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r101_vd_fpn_1x.tar) |
| ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | 7.209 | 45.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |
| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | 14.53 | 41.9 | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_fpn_1x.tar) |
| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | 14.832 | 42.9 | 38.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_vd_fpn_2x.tar) |
| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | 11.546 | 44.6 | 39.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r101_vd_fpn_1x.tar) |
| ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | 6.45 | 46.2 | 40.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |
| ResNet50-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 44.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_fpn_1x.tar) |
| ResNet101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 46.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_1x.tar) |
| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 47.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |
| SENet154-vd-FPN | Cascade Mask | c3-c5 | 1 | 1.44x | - | 51.9 | 43.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.tar) |
| ResNet200-vd-FPN-Nonlocal | CascadeClsAware Faster | c3-c5 | 1 | 2.5x | - | 51.7%(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) |
| CBResNet200-vd-FPN-Nonlocal | Cascade Faster | c3-c5 | 1 | 2.5x | - | 53.3%(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.tar) |
| 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 | 19.978 | 41.0 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | 19.222 | 42.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | 14.477 | 44.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | 7.209 | 45.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | 14.53 | 41.9 | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | 14.832 | 42.9 | 38.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | 11.546 | 44.6 | 39.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | 6.45 | 46.2 | 40.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| ResNet50-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 44.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 46.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 47.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| SENet154-vd-FPN | Cascade Mask | c3-c5 | 1 | 1.44x | - | 51.9 | 43.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.yml) |
| ResNet200-vd-FPN-Nonlocal | CascadeClsAware Faster | c3-c5 | 1 | 2.5x | - | 51.7%(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
| CBResNet200-vd-FPN-Nonlocal | Cascade Faster | c3-c5 | 1 | 2.5x | - | 53.3%(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
**注意事项:**
......@@ -98,18 +98,23 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
* 详情见[Res2Net模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/res2net/)。
### IOU loss
* 目前模型库中包括GIOU loss和DIOU loss，详情加[IOU loss模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master//configs/iou_loss/).
* 目前模型库中包括GIOU loss和DIOU loss，详情见[IOU loss模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master//configs/iou_loss/).
### GCNet
* 详情见[GCNet模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/gcnet/).
### Libra R-CNN
* 详情见[Libra R-CNN模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/libra_rcnn/).
### Auto Augmentation
* 详情见[Auto Augmentation模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/autoaugment/).
### Group Normalization
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 | Box AP | Mask AP | 下载 |
| :------------------- | :------------- |:--------: | :-----: | :----: | :-----: | :----------------------------------------------------------: |
| ResNet50-FPN | Faster | 2 | 2x | 39.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_gn_2x.tar) |
| ResNet50-FPN | Mask | 1 | 2x | 40.1 | 35.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_gn_2x.tar) |
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 | Box AP | Mask AP | 下载 | 配置文件 |
| :------------------- | :------------- |:--------: | :-----: | :----: | :-----: | :----------------------------------------------------------: | :----: |
| ResNet50-FPN | Faster | 2 | 2x | 39.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_gn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn/faster_rcnn_r50_fpn_gn_2x.yml) |
| ResNet50-FPN | Mask | 1 | 2x | 40.1 | 35.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_gn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn/mask_rcnn_r50_fpn_gn_2x.yml) |
**注意事项:**
......@@ -118,39 +123,39 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
### YOLO v3
| 骨架网络 | 预训练数据集 | 输入尺寸 | 加入deformable卷积 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | 下载 |
| :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: | :-------: |
| DarkNet53 (paper) | ImageNet | 608 | 否 | 8 | 270e | - | 33.0 | - |
| DarkNet53 (paper) | ImageNet | 416 | 否 | 8 | 270e | - | 31.0 | - |
| DarkNet53 (paper) | ImageNet | 320 | 否 | 8 | 270e | - | 28.2 | - |
| DarkNet53 | ImageNet | 608 | 否 | 8 | 270e | 45.571 | 38.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) |
| DarkNet53 | ImageNet | 416 | 否 | 8 | 270e | - | 37.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) |
| DarkNet53 | ImageNet | 320 | 否 | 8 | 270e | - | 34.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) |
| MobileNet-V1 | ImageNet | 608 | 否 | 8 | 270e | 78.302 | 29.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) |
| MobileNet-V1 | ImageNet | 416 | 否 | 8 | 270e | - | 29.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) |
| MobileNet-V1 | ImageNet | 320 | 否 | 8 | 270e | - | 27.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) |
| MobileNet-V3 | ImageNet | 608 | 否 | 8 | 270e | - | 31.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) |
| MobileNet-V3 | ImageNet | 416 | 否 | 8 | 270e | - | 29.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) |
| MobileNet-V3 | ImageNet | 320 | 否 | 8 | 270e | - | 27.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) |
| ResNet34 | ImageNet | 608 | 否 | 8 | 270e | 63.356 | 36.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) |
| ResNet34 | ImageNet | 416 | 否 | 8 | 270e | - | 34.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) |
| ResNet34 | ImageNet | 320 | 否 | 8 | 270e | - | 31.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) |
| ResNet50_vd | ImageNet | 608 | 是 | 8 | 270e | - | 39.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn.tar) |
| ResNet50_vd | Object365 | 608 | 是 | 8 | 270e | - | 41.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_pretrained_coco.tar) |
| 骨架网络 | 预训练数据集 | 输入尺寸 | 加入deformable卷积 | 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 |
| :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: | :-------: | :-------: |
| DarkNet53 (paper) | ImageNet | 608 | 否 | 8 | 270e | - | 33.0 | - | - |
| DarkNet53 (paper) | ImageNet | 416 | 否 | 8 | 270e | - | 31.0 | - | - |
| DarkNet53 (paper) | ImageNet | 320 | 否 | 8 | 270e | - | 28.2 | - | - |
| DarkNet53 | ImageNet | 608 | 否 | 8 | 270e | 45.571 | 38.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) |
| DarkNet53 | ImageNet | 416 | 否 | 8 | 270e | - | 37.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) |
| DarkNet53 | ImageNet | 320 | 否 | 8 | 270e | - | 34.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) |
| MobileNet-V1 | ImageNet | 608 | 否 | 8 | 270e | 78.302 | 29.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V1 | ImageNet | 416 | 否 | 8 | 270e | - | 29.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V1 | ImageNet | 320 | 否 | 8 | 270e | - | 27.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V3 | ImageNet | 608 | 否 | 8 | 270e | - | 31.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) |
| MobileNet-V3 | ImageNet | 416 | 否 | 8 | 270e | - | 29.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) |
| MobileNet-V3 | ImageNet | 320 | 否 | 8 | 270e | - | 27.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) |
| ResNet34 | ImageNet | 608 | 否 | 8 | 270e | 63.356 | 36.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) |
| ResNet34 | ImageNet | 416 | 否 | 8 | 270e | - | 34.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) |
| ResNet34 | ImageNet | 320 | 否 | 8 | 270e | - | 31.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) |
| ResNet50_vd | ImageNet | 608 | 是 | 8 | 270e | - | 39.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn.yml) |
| ResNet50_vd | Object365 | 608 | 是 | 8 | 270e | - | 41.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_pretrained_coco.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) |
### YOLO v3 基于Pasacl VOC数据集
| 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | 下载 |
| :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: |
| DarkNet53 | 608 | 8 | 270e | 54.977 | 83.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) |
| DarkNet53 | 416 | 8 | 270e | - | 83.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) |
| DarkNet53 | 320 | 8 | 270e | - | 82.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) |
| MobileNet-V1 | 608 | 8 | 270e | 104.291 | 76.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) |
| MobileNet-V1 | 416 | 8 | 270e | - | 76.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) |
| MobileNet-V1 | 320 | 8 | 270e | - | 75.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) |
| ResNet34 | 608 | 8 | 270e | 82.247 | 82.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) |
| ResNet34 | 416 | 8 | 270e | - | 81.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) |
| ResNet34 | 320 | 8 | 270e | - | 80.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) |
| 骨架网络 | 输入尺寸 | 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 |
| :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: |
| DarkNet53 | 608 | 8 | 270e | 54.977 | 83.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) |
| DarkNet53 | 416 | 8 | 270e | - | 83.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) |
| DarkNet53 | 320 | 8 | 270e | - | 82.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) |
| MobileNet-V1 | 608 | 8 | 270e | 104.291 | 76.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) |
| MobileNet-V1 | 416 | 8 | 270e | - | 76.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) |
| MobileNet-V1 | 320 | 8 | 270e | - | 75.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) |
| ResNet34 | 608 | 8 | 270e | 82.247 | 82.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) |
| ResNet34 | 416 | 8 | 270e | - | 81.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) |
| ResNet34 | 320 | 8 | 270e | - | 80.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) |
**注意事项:**
......@@ -160,39 +165,39 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
### RetinaNet
| 骨架网络 | 每张GPU图片个数 | 学习率策略 | Box AP | 下载 |
| :---------------: | :-----: | :-----: | :----: | :-------: |
| ResNet50-FPN | 2 | 1x | 36.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r50_fpn_1x.tar) |
| ResNet101-FPN | 2 | 1x | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r101_fpn_1x.tar) |
| ResNeXt101-vd-FPN | 1 | 1x | 40.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_x101_vd_64x4d_fpn_1x.tar) |
| 骨架网络 | 每张GPU图片个数 | 学习率策略 | Box AP | 下载 | 配置文件 |
| :---------------: | :-----: | :-----: | :----: | :-------: | :----: |
| ResNet50-FPN | 2 | 1x | 36.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_r50_fpn_1x.yml) |
| ResNet101-FPN | 2 | 1x | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_r101_fpn_1x.yml) |
| ResNeXt101-vd-FPN | 1 | 1x | 40.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_x101_vd_64x4d_fpn_1x.yml) |
**注意事项:** RetinaNet系列模型中，在总batch size为16下情况下，初始学习率改为0.01。
### SSDLite
| 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略|推理时间(fps) | Box AP | 下载 |
| :----------: | :--: | :-----: | :-----: |:------------: |:----: | :-------: |
| MobileNet_v3 small | 320 | 64 | 40w | - | 16.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobilenet_v3_ssdlite_small.tar) |
| MobileNet_v3 large | 320 | 64 | 40w | - | 22.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobilenet_v3_ssdlite_large.tar) |
| 骨架网络 | 输入尺寸 | 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 |
| :----------: | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: |
| MobileNet_v3 small | 320 | 64 | 40w | - | 16.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobilenet_v3_ssdlite_small.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_small.yml) |
| MobileNet_v3 large | 320 | 64 | 40w | - | 22.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobilenet_v3_ssdlite_large.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_large.yml) |
**注意事项:** MobileNet_v3-SSDLite 使用学习率余弦衰减策略在8卡GPU下总batch size为512。
### SSD
| 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略|推理时间(fps) | Box AP | 下载 |
| :----------: | :--: | :-----: | :-----: |:------------: |:----: | :-------: |
| VGG16 | 300 | 8 | 40万 | 81.613 | 25.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300.tar) |
| VGG16 | 512 | 8 | 40万 | 46.007 | 29.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512.tar) |
| 骨架网络 | 输入尺寸 | 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 |
| :----------: | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: |
| VGG16 | 300 | 8 | 40万 | 81.613 | 25.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_300.yml) |
| VGG16 | 512 | 8 | 40万 | 46.007 | 29.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_512.yml) |
**注意事项:** VGG-SSD在总batch size为32下训练40万轮。
### SSD 基于Pascal VOC数据集
| 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | 下载 |
| :----------- | :--: | :-----: | :-----: | :------------: |:----: | :-------: |
| MobileNet v1 | 300 | 32 | 120e | 159.543 | 73.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar) |
| VGG16 | 300 | 8 | 240e | 117.279 | 77.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300_voc.tar) |
| VGG16 | 512 | 8 | 240e | 65.975 | 80.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512_voc.tar) |
| 骨架网络 | 输入尺寸 | 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 |
| :----------- | :--: | :-----: | :-----: | :------------: | :----: | :-------: | :----: |
| MobileNet v1 | 300 | 32 | 120e | 159.543 | 73.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_mobilenet_v1_voc.yml) |
| VGG16 | 300 | 8 | 240e | 117.279 | 77.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_300_voc.yml) |
| VGG16 | 512 | 8 | 240e | 65.975 | 80.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_512_voc.yml) |
**注意事项:** MobileNet-SSD在2卡，总batch size为64下训练120周期。VGG-SSD在总batch size为32下训练240周期。数据增强包括：随机颜色失真，随机剪裁，随机扩张，随机翻转。
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- 测试方式:
- 为了方便比较不同模型的推理速度，输入采用同样大小的图片，为 3x640x640，采用 `demo/000000014439_640x640.jpg` 图片。
- Batch Size=1
- 去掉前10轮warmup时间，测试100轮的平均时间，单位ms/image，包括输入数据拷贝至GPU的时间、计算时间、数据拷贝只CPU的时间。
- 去掉前10轮warmup时间，测试100轮的平均时间，单位ms/image，包括输入数据拷贝至GPU的时间、计算时间、数据拷贝至CPU的时间。
- 采用Fluid C++预测引擎: 包含Fluid C++预测、Fluid-TensorRT预测，下面同时测试了Float32 (FP32) 和Float16 (FP16)的推理速度。
- 测试时开启了 FLAGS_cudnn_exhaustive_search=True，使用exhaustive方式搜索卷积计算算法。
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2.启动训练模型
```bash
python tools/train.py -c configs/obj365/cascade_rcnn_dcnv2_se154_vd_fpn_gn.yml
python tools/train.py -c configs/obj365/cascade_rcnn_dcnv2_se154_vd_fpn_gn_cas.yml
```
3.模型预测结果
| 模型 | 验证集 mAP | 下载链接 |
| :-----------------: | :--------: | :----------------------------------------------------------: |
| CACascadeRCNN SE154 | 31.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcnv2_se154_vd_fpn_gn_cas_obj365.tar) |
| 模型 | 验证集 mAP | 下载链接 | 配置文件 |
| :-----------------: | :--------: | :----------------------------------------------------------: | :--------: |
| CACascadeRCNN SE154 | 31.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcnv2_se154_vd_fpn_gn_cas_obj365.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/obj365/cascade_rcnn_dcnv2_se154_vd_fpn_gn_cas.yml) |
## 模型效果
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We provide some models implemented by PaddlePaddle to detect objects in specific scenarios, users can download the models and use them in these scenarios.
| Task | Algorithm | Box AP | Download |
|:---------------------|:---------:|:------:| :-------------------------------------------------------------------------------------: |
| Vehicle Detection | YOLOv3 | 54.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/vehicle_yolov3_darknet.tar) |
| Pedestrian Detection | YOLOv3 | 51.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar) |
| Task | Algorithm | Box AP | Download | Configs |
|:---------------------|:---------:|:------:| :-------------------------------------------------------------------------------------: |:------:|
| Vehicle Detection | YOLOv3 | 54.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/vehicle_yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/contrib/VehicleDetection/vehicle_yolov3_darknet.yml) |
| Pedestrian Detection | YOLOv3 | 51.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/contrib/PedestrianDetection/pedestrian_yolov3_darknet.yml) |
## Vehicle Detection
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我们提供了针对不同场景的基于PaddlePaddle的检测模型，用户可以下载模型进行使用。
| 任务 | 算法 | 精度(Box AP) | 下载 |
|:---------------------|:---------:|:------:| :---------------------------------------------------------------------------------: |
| 车辆检测 | YOLOv3 | 54.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/vehicle_yolov3_darknet.tar) |
| 行人检测 | YOLOv3 | 51.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar) |
| 任务 | 算法 | 精度(Box AP) | 下载 | 配置文件 |
|:---------------------|:---------:|:------:| :---------------------------------------------------------------------------------: | :------:|
| 车辆检测 | YOLOv3 | 54.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/vehicle_yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/contrib/VehicleDetection/vehicle_yolov3_darknet.yml) |
| 行人检测 | YOLOv3 | 51.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/contrib/PedestrianDetection/pedestrian_yolov3_darknet.yml) |
## 车辆检测（Vehicle Detection）
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#### WIDER-FACE数据集上的mAP
| 网络结构 | 类型 | 输入尺寸 | 图片个数/GPU | 学习率策略 | Easy Set | Medium Set | Hard Set | 下载 |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|
| BlazeFace | 原始版本 | 640 | 8 | 32w | **0.915** | **0.892** | **0.797** | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) |
| BlazeFace | Lite版本 | 640 | 8 | 32w | 0.909 | 0.885 | 0.781 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) |
| BlazeFace | NAS版本 | 640 | 8 | 32w | 0.837 | 0.807 | 0.658 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) |
| BlazeFace | NAS_V2版本 | 640 | 8 | 32W | 0.870 | 0.837 | 0.685 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas2.tar)
| FaceBoxes | 原始版本 | 640 | 8 | 32w | 0.878 | 0.851 | 0.576 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) |
| FaceBoxes | Lite版本 | 640 | 8 | 32w | 0.901 | 0.875 | 0.760 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) |
| 网络结构 | 类型 | 输入尺寸 | 图片个数/GPU | 学习率策略 | Easy Set | Medium Set | Hard Set | 下载 | 配置文件 |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:|
| BlazeFace | 原始版本 | 640 | 8 | 32w | **0.915** | **0.892** | **0.797** | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface.yml) |
| BlazeFace | Lite版本 | 640 | 8 | 32w | 0.909 | 0.885 | 0.781 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface.yml) |
| BlazeFace | NAS版本 | 640 | 8 | 32w | 0.837 | 0.807 | 0.658 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_nas.yml) |
| BlazeFace | NAS_V2版本 | 640 | 8 | 32W | 0.870 | 0.837 | 0.685 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas2.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_nas_v2.yml) |
| FaceBoxes | 原始版本 | 640 | 8 | 32w | 0.878 | 0.851 | 0.576 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/faceboxes.yml) |
| FaceBoxes | Lite版本 | 640 | 8 | 32w | 0.901 | 0.875 | 0.760 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/faceboxes_lite.yml) |
**注意:**
- 我们使用`tools/face_eval.py`中多尺度评估策略得到`Easy/Medium/Hard Set`里的mAP。具体细节请参考[在WIDER-FACE数据集上评估](#在WIDER-FACE数据集上评估)。
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#### mAP in WIDER FACE
| Architecture | Type | Size | Img/gpu | Lr schd | Easy Set | Medium Set | Hard Set | Download |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|
| BlazeFace | Original | 640 | 8 | 32w | **0.915** | **0.892** | **0.797** | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) |
| BlazeFace | Lite | 640 | 8 | 32w | 0.909 | 0.885 | 0.781 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) |
| BlazeFace | NAS | 640 | 8 | 32w | 0.837 | 0.807 | 0.658 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) |
| BlazeFace | NAS_V2 | 640 | 8 | 32W | 0.870 | 0.837 | 0.685 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas2.tar)
| FaceBoxes | Original | 640 | 8 | 32w | 0.878 | 0.851 | 0.576 | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) |
| FaceBoxes | Lite | 640 | 8 | 32w | 0.901 | 0.875 | 0.760 | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) |
| Architecture | Type | Size | Img/gpu | Lr schd | Easy Set | Medium Set | Hard Set | Download | Configs |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:|
| BlazeFace | Original | 640 | 8 | 32w | **0.915** | **0.892** | **0.797** | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface.yml) |
| BlazeFace | Lite | 640 | 8 | 32w | 0.909 | 0.885 | 0.781 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface.yml) |
| BlazeFace | NAS | 640 | 8 | 32w | 0.837 | 0.807 | 0.658 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_nas.yml) |
| BlazeFace | NAS_V2 | 640 | 8 | 32W | 0.870 | 0.837 | 0.685 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas2.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_nas_v2.yml) |
| FaceBoxes | Original | 640 | 8 | 32w | 0.878 | 0.851 | 0.576 | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/faceboxes.yml) |
| FaceBoxes | Lite | 640 | 8 | 32w | 0.901 | 0.875 | 0.760 | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/faceboxes_lite.yml) |
**NOTES:**
- Get mAP in `Easy/Medium/Hard Set` by multi-scale evaluation in `tools/face_eval.py`.
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OIDV5模型训练结果如下。
| 模型结构 | Public/Private Score | 下载链接 |
| :-----------------: | :--------: | :----------------------------------------------------------: |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | 0.62690/0.59459 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/oidv5_cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) |
| 模型结构 | Public/Private Score | 下载链接 | 配置文件 |
| :-----------------: | :--------: | :----------------------------------------------------------: | :--------: |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | 0.62690/0.59459 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/oidv5_cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/oidv5/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
此外，为验证模型的性能，团队基于该模型结构，也训练了针对COCO2017和Objects365 Dataset的模型，模型和验证集指标如下表。
此外，为验证模型的性能，PaddleDetection基于该模型结构，也训练了针对COCO2017和Objects365 Dataset的模型，模型和验证集指标如下表。
| 模型结构 | 数据集 | 验证集mAP | 下载链接 |
| :-----------------: | :--------: | :--------: | :----------------------------------------------------------: |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | COCO2017 | 51.7% | [模型](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | Objects365 | 34.5% | [模型](https://paddlemodels.bj.bcebos.com/object_detection/obj365_cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) |
| 模型结构 | 数据集 | 验证集mAP | 下载链接 | 配置文件 |
| :-----------------: | :--------: | :--------: | :----------------------------------------------------------: | :--------: |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | COCO2017 | 51.7% | [模型](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/obj365/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | Objects365 | 34.5% | [模型](https://paddlemodels.bj.bcebos.com/object_detection/obj365_cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/obj365/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
COCO和Objects365 Dataset数据格式相同，目前只支持预测和评估。
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......@@ -34,18 +34,18 @@ PaddleDetection实现版本中使用了 [Bag of Freebies for Training Object Det
```bash
export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
python tools/train.py -c configs/dcn/yolov3_r50vd_dcn_iouloss_obj365_pretrained_coco.yml
python tools/train.py -c configs/dcn/yolov3_r50vd_dcn_db_iouloss_obj365_pretrained_coco.yml
```
更多模型参数请使用``python tools/train.py --help``查看，或参考[训练、评估及参数说明](../tutorials/GETTING_STARTED_cn.md)文档
### 模型效果
| 模型 | 预训练模型 | 验证集 mAP | P4预测速度 | 下载 |
| :--------------------------------------: | :----------------------------------------------------------: | :--------: | :------------------------------------: | :----------------------------------------------------------: |
| YOLOv3 DarkNet | [DarkNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar) | 38.9 | 原生：88.3ms<br>tensorRT-FP32: 42.5ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) |
| YOLOv3 ResNet50_vd DCN | [ImageNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar) | 39.1 | 原生：74.4ms<br>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_imagenet.tar) |
| YOLOv3 ResNet50_vd DCN | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.5 | 原生：74.4ms<br>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_v2.tar) |
| YOLOv3 ResNet50_vd DCN DropBlock | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.8 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock.tar) |
| YOLOv3 ResNet50_vd DCN DropBlock IoULoss | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.2 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock_iouloss.tar) |
| YOLOv3 ResNet50_vd DCN DropBlock IoU-Aware | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.6 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_db_iouaware_obj365_pretrained_coco.pdparams) |
| 模型 | 预训练模型 | 验证集 mAP | P4预测速度 | 下载 | 配置文件 |
| :--------------------------------------: | :----------------------------------------------------------: | :--------: | :------------------------------------: | :----------------------------------------------------------: | :--------: |
| YOLOv3 DarkNet | [DarkNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar) | 38.9 | 原生：88.3ms<br>tensorRT-FP32: 42.5ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) |
| YOLOv3 ResNet50_vd DCN | [ImageNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar) | 39.1 | 原生：74.4ms<br>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_imagenet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn.yml) |
| YOLOv3 ResNet50_vd DCN | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.5 | 原生：74.4ms<br>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_v2.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) |
| YOLOv3 ResNet50_vd DCN DropBlock | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.8 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_db_obj365_pretrained_coco.yml) |
| YOLOv3 ResNet50_vd DCN DropBlock IoULoss | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.2 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock_iouloss.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_db_iouloss_obj365_pretrained_coco.yml) |
| YOLOv3 ResNet50_vd DCN DropBlock IoU-Aware | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.6 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_db_iouaware_obj365_pretrained_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_db_iouaware_obj365_pretrained_coco.yml) |
docs/tutorials/QUICK_STARTED_cn.md
浏览文件 @ 521a4a6a
......@@ -13,7 +13,7 @@ export CUDA_VISIBLE_DEVICES=0
## 数据准备
数据集参考[Kaggle数据集](https://www.kaggle.com/mbkinaci/fruit-images-for-object-detection)，其中训练数据集240张图片，测试数据集60张图片，数据类别为3类：苹果，橘子，香蕉。[下载链接](https://dataset.bj.bcebos.com/PaddleDetection_demo/fruit-detection.tar)。数据下载后分别解压即可, 数据准备脚本位于[download_fruit.py](../../dataset/fruit/download_fruit.py)。下载数据方式如下：
数据集参考[Kaggle数据集](https://www.kaggle.com/mbkinaci/fruit-images-for-object-detection)，其中训练数据集240张图片，测试数据集60张图片，数据类别为3类：苹果，橘子，香蕉。[下载链接](https://dataset.bj.bcebos.com/PaddleDetection_demo/fruit-detection.tar)。数据下载后分别解压即可, 数据准备脚本位于[download_fruit.py](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dataset/fruit/download_fruit.py)。下载数据方式如下：
```bash
python dataset/fruit/download_fruit.py
......
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