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Add obj365 pretrained weights (#8500)
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* add obj365 pretrained weights, test=document_fix
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lyuwenyu authored Aug 14, 2023
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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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