slowfast项目压缩文件

# ViTDet: Exploring Plain Vision Transformer Backbones for Object Detection Yanghao Li, Hanzi Mao, Ross Girshick†, Kaiming He† [[`arXiv`](https://arxiv.org/abs/2203.16527)] [[`BibTeX`](#CitingViTDet)] In this repository, we provide configs and models in Detectron2 for ViTDet as well as MViTv2 and Swin backbones with our implementation and settings as described in [ViTDet](https://arxiv.org/abs/2203.16527) paper. ## Pretrained Models ### COCO #### Mask R-CNN <table><tbody> <!-- START TABLE --> <!-- TABLE HEADER --> <th valign="bottom">Name</th> <th valign="bottom">pre-train</th> <th valign="bottom">train<br/>time<br/>(s/im)</th> <th valign="bottom">inference<br/>time<br/>(s/im)</th> <th valign="bottom">train<br/>mem<br/>(GB)</th> <th valign="bottom">box<br/>AP</th> <th valign="bottom">mask<br/>AP</th> <th valign="bottom">model id</th> <th valign="bottom">download</th> <!-- TABLE BODY --> <!-- ROW: mask_rcnn_vitdet_b_100ep --> <tr><td align="left"><a href="configs/COCO/mask_rcnn_vitdet_b_100ep.py">ViTDet, ViT-B</a></td> <td align="center">IN1K, MAE</td> <td align="center">0.314</td> <td align="center">0.079</td> <td align="center">10.9</td> <td align="center">51.6</td> <td align="center">45.9</td> <td align="center">325346929</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/mask_rcnn_vitdet_b/f325346929/model_final_61ccd1.pkl">model</a></td> </tr> <!-- ROW: mask_rcnn_vitdet_l_100ep --> <tr><td align="left"><a href="configs/COCO/mask_rcnn_vitdet_l_100ep.py">ViTDet, ViT-L</a></td> <td align="center">IN1K, MAE</td> <td align="center">0.603</td> <td align="center">0.125</td> <td align="center">20.9</td> <td align="center">55.5</td> <td align="center">49.2</td> <td align="center">325599698</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/mask_rcnn_vitdet_l/f325599698/model_final_6146ed.pkl">model</a></td> </tr> <!-- ROW: mask_rcnn_vitdet_b_75ep --> <tr><td align="left"><a href="configs/COCO/mask_rcnn_vitdet_h_75ep.py">ViTDet, ViT-H</a></td> <td align="center">IN1K, MAE</td> <td align="center">1.098</td> <td align="center">0.178</td> <td align="center">31.5</td> <td align="center">56.7</td> <td align="center">50.2</td> <td align="center">329145471</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/mask_rcnn_vitdet_h/f329145471/model_final_7224f1.pkl">model</a></td> </tr> </tbody></table> #### Cascade Mask R-CNN <table><tbody> <!-- START TABLE --> <!-- TABLE HEADER --> <th valign="bottom">Name</th> <th valign="bottom">pre-train</th> <th valign="bottom">train<br/>time<br/>(s/im)</th> <th valign="bottom">inference<br/>time<br/>(s/im)</th> <th valign="bottom">train<br/>mem<br/>(GB)</th> <th valign="bottom">box<br/>AP</th> <th valign="bottom">mask<br/>AP</th> <th valign="bottom">model id</th> <th valign="bottom">download</th> <!-- TABLE BODY --> <!-- ROW: cascade_mask_rcnn_swin_b_in21k_50ep --> <tr><td align="left"><a href="configs/COCO/cascade_mask_rcnn_swin_b_in21k_50ep.py">Swin-B</a></td> <td align="center">IN21K, sup</td> <td align="center">0.389</td> <td align="center">0.077</td> <td align="center">8.7</td> <td align="center">53.9</td> <td align="center">46.2</td> <td align="center">342979038</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/cascade_mask_rcnn_swin_b_in21k/f342979038/model_final_246a82.pkl">model</a></td> </tr> <!-- ROW: cascade_mask_rcnn_swin_l_in21k_50ep --> <tr><td align="left"><a href="configs/COCO/cascade_mask_rcnn_swin_l_in21k_50ep.py">Swin-L</a></td> <td align="center">IN21K, sup</td> <td align="center">0.508</td> <td align="center">0.097</td> <td align="center">12.6</td> <td align="center">55.0</td> <td align="center">47.2</td> <td align="center">342979186</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/cascade_mask_rcnn_swin_l_in21k/f342979186/model_final_7c897e.pkl">model</a></td> </tr> <!-- ROW: cascade_mask_rcnn_mvitv2_b_in21k_100ep --> <tr><td align="left"><a href="configs/COCO/cascade_mask_rcnn_mvitv2_b_in21k_100ep.py">MViTv2-B</a></td> <td align="center">IN21K, sup</td> <td align="center">0.475</td> <td align="center">0.090</td> <td align="center">8.9</td> <td align="center">55.6</td> <td align="center">48.1</td> <td align="center">325820315</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/cascade_mask_rcnn_mvitv2_b_in21k/f325820315/model_final_8c3da3.pkl">model</a></td> </tr> </tr> <!-- ROW: cascade_mask_rcnn_mvitv2_l_in21k_50ep --> <tr><td align="left"><a href="configs/COCO/cascade_mask_rcnn_mvitv2_l_in21k_50ep.py">MViTv2-L</a></td> <td align="center">IN21K, sup</td> <td align="center">0.844</td> <td align="center">0.157</td> <td align="center">19.7</td> <td align="center">55.7</td> <td align="center">48.3</td> <td align="center">325607715</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/cascade_mask_rcnn_mvitv2_l_in21k/f325607715/model_final_2141b0.pkl">model</a></td> </tr> </tr> <!-- ROW: cascade_mask_rcnn_mvitv2_h_in21k_36ep --> <tr><td align="left"><a href="configs/COCO/cascade_mask_rcnn_mvitv2_h_in21k_36ep.py">MViTv2-H</a></td> <td align="center">IN21K, sup</td> <td align="center">1.655</td> <td align="center">0.285</td> <td align="center">18.4*</td> <td align="center">55.9</td> <td align="center">48.3</td> <td align="center">326187358</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/cascade_mask_rcnn_mvitv2_h_in21k/f326187358/model_final_2234d7.pkl">model</a></td> </tr> <!-- ROW: cascade_mask_rcnn_vitdet_b_100ep --> <tr><td align="left"><a href="configs/COCO/cascade_mask_rcnn_vitdet_b_100ep.py">ViTDet, ViT-B</a></td> <td align="center">IN1K, MAE</td> <td align="center">0.362</td> <td align="center">0.089</td> <td align="center">12.3</td> <td align="center">54.0</td> <td align="center">46.7</td> <td align="center">325358525</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/cascade_mask_rcnn_vitdet_b/f325358525/model_final_435fa9.pkl">model</a></td> </tr> <!-- ROW: cascade_mask_rcnn_vitdet_l_100ep --> <tr><td align="left"><a href="configs/COCO/cascade_mask_rcnn_vitdet_l_100ep.py">ViTDet, ViT-L</a></td> <td align="center">IN1K, MAE</td> <td align="center">0.643</td> <td align="center">0.142</td> <td align="center">22.3</td> <td align="center">57.6</td> <td align="center">50.0</td> <td align="center">328021305</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/cascade_mask_rcnn_vitdet_l/f328021305/model_final_1a9f28.pkl">model</a></td> </tr> <!-- ROW: cascade_mask_rcnn_vitdet_h_75ep --> <tr><td align="left"><a href="configs/COCO/cascade_mask_rcnn_vitdet_h_75ep.py">ViTDet, ViT-H</a></td> <td align="center">IN1K, MAE</td> <td align="center">1.137</td> <td align="center">0.196</td> <td align="center">32.9</td> <td align="center">58.7</td> <td align="center">51.0</td> <td align="center">328730692</td> <td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/ViTDet/COCO/cascade_mask_rcnn_vitdet_h/f328730692/model_final_f05665.pkl">model</a></td> </tr> </tbody></table> ### LVIS #### Mask R-CNN <table><tbody> <!-- START TABLE --> <!-- TABLE HEADER --> <th valign="bottom">Name</th> <th valign="bottom">pre-train</th> <th valign="bottom">train<br/>time<br/>(s/im)</th> <th valign="bottom">inference<br/>time<br/>(s/im)</th> <th valign="bottom">train<br/>mem<br/>(GB)</th> <th valign="bottom">box<br/>AP</th> <th valign="bottom">mask<br/>AP</th> <th valign="bottom">model id</th> <th valign="bottom">download</th> <!-- TABLE BODY --> <!-- ROW: mask_rcnn_vitdet_b_100ep --> <tr><td align="left"><a href="configs/LVIS/mask_rcnn_vitdet_b_100ep.py">ViTDet, ViT-B</a></td> <td align="center">IN1K, MAE</td> <td align="center">0.317</td> <td align="center">0.085</td> <td align="center">14.4</td> <td align="center">40.2</td> <td align="cent