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Add obj365 pretrained weights #8500

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Aug 14, 2023
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Add obj365 pretrained weights #8500

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5a50cca
add obj365 pretrained weights
lyuwenyu Aug 1, 2023
223e510
add obj365 pretrained weights
lyuwenyu Aug 1, 2023
2769ee8
add obj365 pretrained weights
lyuwenyu Aug 1, 2023
80ff53d
add obj365 pretrained weights, test=document_fix
lyuwenyu Aug 1, 2023
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14 changes: 13 additions & 1 deletion configs/rtdetr/README.md
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Expand Up @@ -20,7 +20,7 @@ RT-DETR是第一个实时端到端目标检测器。具体而言，我们设计

## 基础模型

| Model | Epoch | backbone | input shape | $AP^{val}$ | $AP^{val}_{50}$| Params(M) | FLOPs(G) | T4 TensorRT FP16(FPS) | Pretrained Model | config |
| Model | Epoch | Backbone | Input shape | $AP^{val}$ | $AP^{val}_{50}$| Params(M) | FLOPs(G) | T4 TensorRT FP16(FPS) | Pretrained Model | config |
|:--------------:|:-----:|:----------:| :-------:|:--------------------------:|:---------------------------:|:---------:|:--------:| :---------------------: |:------------------------------------------------------------------------------------:|:-------------------------------------------:|
| RT-DETR-R18 | 6x | ResNet-18 | 640 | 46.5 | 63.8 | 20 | 60 | 217 | [download](https://bj.bcebos.com/v1/paddledet/models/rtdetr_r18vd_dec3_6x_coco.pdparams) | [config](./rtdetr_r18vd_6x_coco.yml)
| RT-DETR-R34 | 6x | ResNet-34 | 640 | 48.9 | 66.8 | 31 | 92 | 161 | [download](https://bj.bcebos.com/v1/paddledet/models/rtdetr_r34vd_dec4_6x_coco.pdparams) | [config](./rtdetr_r34vd_6x_coco.yml)
Expand All @@ -37,6 +37,18 @@ RT-DETR是第一个实时端到端目标检测器。具体而言，我们设计
| RT-DETR-Swin | 3x | Swin_L_384 | 640 | 56.2 | 73.5 | [download](https://bj.bcebos.com/v1/paddledet/models/rtdetr_swin_L_384_3x_coco.pdparams) | [config](./rtdetr_swin_L_384_3x_coco.yml)
| RT-DETR-FocalNet | 3x | FocalNet_L_384 | 640 | 56.9 | 74.3 | [download](https://bj.bcebos.com/v1/paddledet/models/rtdetr_focalnet_L_384_3x_coco.pdparams) | [config](./rtdetr_focalnet_L_384_3x_coco.yml)


## Objects365预训练模型
| Model | Epoch | Dataset | Input shape | $AP^{val}$ | $AP^{val}_{50}$ | T4 TensorRT FP16(FPS) | Weight | Logs
|:---:|:---:|:---:| :---:|:---:|:---:|:---:|:---:|:---:|
RT-DETR-R50 | 1x | Objects365 | 640 | 35.1 | 46.2 | 108 | [download](https://bj.bcebos.com/v1/paddledet/models/rtdetr_r50vd_1x_objects365.pdparams) | [log](https://github.com/lyuwenyu/RT-DETR/issues/8)
RT-DETR-R50 | 2x | COCO + Objects365 | 640 | 55.3 | 73.4 | 108 | [download](https://bj.bcebos.com/v1/paddledet/models/rtdetr_r50vd_2x_coco_objects365.pdparams) | [log](https://github.com/lyuwenyu/RT-DETR/issues/8)

**Notes:**
- `COCO + Objects365` 代表使用Objects365预训练权重，在COCO上finetune的结果



**注意事项:**
- RT-DETR 基础模型均使用4个GPU训练。
- RT-DETR 在COCO train2017上训练，并在val2017上评估。
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