init repo

CITATION.cff

@@ -0,0 +1,8 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite it as below."
+authors:
+  - name: "MMPose Contributors"
+title: "OpenMMLab Pose Estimation Toolbox and Benchmark"
+date-released: 2020-08-31
+url: "https://github.com/open-mmlab/mmpose"
+license: Apache-2.0

LICENSE

@@ -1,17 +1,18 @@
-BSD 2-Clause License
+Poseur for non-commercial purposes
+(For commercial use, contact [email protected] for obtaining a commerical license.)
 
-Copyright (c) 2022, Advanced Intelligent Machines (AIM)
+Copyright (c) 2019 the authors
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without
 modification, are permitted provided that the following conditions are met:
 
-1. Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
 
-2. Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
+* Redistributions in binary form must reproduce the above copyright notice,
+  this list of conditions and the following disclaimer in the documentation
+  and/or other materials provided with the distribution.
 
 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
@@ -22,4 +23,4 @@ DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
 SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
-OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

MANIFEST.in

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+include requirements/*.txt
+include mmpose/.mim/model-index.yml
+recursive-include mmpose/.mim/configs *.py *.yml
+recursive-include mmpose/.mim/tools *.py *.sh
+recursive-include mmpose/.mim/demo *.py

README.md

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+# Poseur: Direct Human Pose Regression with Transformers
+
+
+> [**Poseur: Direct Human Pose Regression with Transformers**](https://arxiv.org/pdf/2201.07412.pdf),            
+> Weian Mao\*, Yongtao Ge\*, Chunhua Shen, Zhi Tian, Xinlong Wang, Zhibin Wang, Anton van den Hengel  
+> In: European Conference on Computer Vision (ECCV), 2022   
+> *arXiv preprint ([arXiv 2201.07412](https://arxiv.org/pdf/2201.07412))*  
+> (\* equal contribution)
+
+# Introduction
+This is a preview for Poseur, which currently including Poseur with R-50 backbone for both training and inference. More models with various backbones will be released soon. This project is bulit upon [MMPose](https://github.com/open-mmlab/mmpose) with commit ID [eeebc652842a9724259ed345c00112641d8ee06d](https://github.com/open-mmlab/mmpose/commit/eeebc652842a9724259ed345c00112641d8ee06d).
+
+# Installation & Quick Start
+First, follow the [MMPose instruction](mmpose_README.md) to install the project and set up the datasets (MS-COCO).
+
+For training on COCO, run:
+```
+./tools/dist_train.sh \
+configs/body/2d_kpt_sview_rgb_img/poseur/coco/poseur_r50_coco_256x192.py 8 \
+--work-dir work_dirs/poseur_r50_coco_256x192
+```
+
+For evaluation on COCO, run the following command lines:
+```
+wget https://cloudstor.aarnet.edu.au/plus/s/UXr1Dn9w6ja4fM9/download -O poseur_256x192_r50_6dec_coco.pth
+./tools/dist_test.sh configs/body/2d_kpt_sview_rgb_img/poseur/coco/poseur_r50_coco_256x192.py \
+    poseur_256x192_r50_6dec_coco.pth 4 \
+    --eval mAP \
+    --cfg-options model.filp_fuse_type=\'type2\'
+```
+
+## Models
+### COCO Keypoint Detection Results
+
+Name | AP | AP.5| AP.75 |download
+--- |:---:|:---:|:---:|:---:
+[Poseur_R50_COCO_256x192](configs/body/2d_kpt_sview_rgb_img/poseur/coco/poseur_r50_coco_256x192.py)| 75.5  | 90.7 |82.6 | [model](https://cloudstor.aarnet.edu.au/plus/s/chF3VKQT4RDoEqC/download)
+
+
+*Disclaimer:*
+
+- Due to the update of MMPose, the result of R50 is slightly higher than our original paper.
+
+# Citations
+Please consider citing our papers in your publications if the project helps your research. BibTeX reference is as follows.
+```BibTeX
+@article{mao2022poseur,
+  title={Poseur: Direct human pose regression with transformers},
+  author={Mao, Weian and Ge, Yongtao and Shen, Chunhua and Tian, Zhi and Wang, Xinlong and Wang, Zhibin and Hengel, Anton van den},
+  journal={arXiv preprint arXiv:2201.07412},
+  year={2022}
+}
+```
+
+## License
+
+For academic use, this project is licensed under the 2-clause BSD License. For commercial use, please contact [Chunhua Shen](mailto:[email protected]).