| # SOTA COCO Object Detection with PE |
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| ## Getting started |
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| Please refer to [INSTALL.md](../INSTALL.md) for installation and dataset preparation instructions. |
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| Also install [Deformable Attention](models/ops/make.sh) ops. |
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| ## Results and Fine-tuned Models |
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| <table><tbody> |
| <!-- START TABLE --> |
| <!-- TABLE HEADER --> |
| <th valign="bottom">detector</th> |
| <th valign="bottom">vision encoder</th> |
| <th valign="bottom">box<br/>AP</th> |
| <th valign="bottom">box(TTA)<br/>AP</th> |
| <th valign="bottom">download</th> |
| <!-- TABLE BODY --> |
| <!-- ROW: DETA --> |
| <tr><td align="left">DETA</td> |
| <td align="center">PE spatial G</td> |
| <td align="center"> 65.2 </td> |
| <td align="center"> 66.0 </td> |
| <td align="center"><a href="https://huggingface.co/facebook/PE-Detection/resolve/main/deta_coco_1824pix.pth">model</a></td> |
| </tr> |
| </tbody></table> |
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| ## Training |
| We apply a four-stage training, Objects365(12ep, 1024pix), Objects365(6ep, 1536pix), COCO(12ep, 1728pix), COCO(3ep, 1824pix) |
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| ``` |
| sbatch scripts/pretrain_spatial_Gwin384_o365ep12_1024pix_16node.sh |
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| sbatch scripts/pretrain_continue_spatial_Gwin384_o365ep6_1536pix_16node.sh |
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| sbatch scripts/finetune_spatial_Gwin384_cocoep12_1728pix_8node.sh |
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| sbatch scripts/finetune_further_spatial_Gwin384_cocoep3_1824pix_8node.sh |
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| ``` |
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| ## Evaluation |
| ``` |
| bash scripts/eval_1824pix.sh --resume deta_coco_1824pix.pth |
| ``` |
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| ## Evaluation with TTA (Test-Time Augmentation) |
| ``` |
| sbatch scripts/eval_tta_slurm_1824pix.sh --resume deta_coco_1824pix.pth |
| ``` |
| Note: If you get 65.9 AP, it is probably caused by different package versions, trying different hyperparameters like `--quad_scale 0.4` will give 66.0 AP. |
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