MasakazuTobeta / SMPR

SMPR

Code repository for the paper SMPR: Single-Stage Multi-Person Pose Regression, by Junqi Lin, Huixin Miao, Junjie Cao, Zhixun Su and Risheng Liu.

Results

Results on COCO test-dev.

Backbone	mAP	AP^{50}	AP^{75}	AP^{M}	AP^{L}
ResNet50	62.6	85.9	68.6	56.1	71.7
ResNet50 (multi-testing)	65.3	87.9	72.1	59.8	73.3
HRNet-w32	68.2	88.7	75.3	63.3	75.4
HRNet-w32 (multi-testing)	70.2	89.7	77.5	65.9	77.2

Getting Started

conda create -n mmdet python=3.7

conda activate mmdet

conda install pytorch=1.4.0 cudatoolkit=10.1 torchvision=0.5.0

pip install cython

git clone https://github.com/cocodataset/cocoapi.git

cd cocoapi/PythonAPI

python setup.py build_ext --inplace

python setup.py build_ext install

pip install -r requirements.txt

pip install Pillow==6.2.2

pip install -v -e .

Data preprocessing

put train2017 and val2017 in data/coco

put person_keypoints_train2017.json and person_keypoints_val2017.json in data/coco/annotations

cd data/coco/annotations

% generate 'person_keypoints_train2017_pesudobox.json'

python pesudo_box_train.py

% generate 'person_keypoints_val2017_pesudobox.json'

python pesudo_box_val.py

Pretrained Models

You can download the trained model on Baidu Yun，with the extraction code：aaaa

Inference

You can now evaluate the models on the COCO val2017 split:

./tools/dist_test.sh configs/SMPR/ResNet_50.py work_dirs/r50.pth 4 --eval keypoints --options "jsonfile_prefix=./work_dirs/r50"

Citation

@misc{SMPR2020,
Author = {Junqi Lin and Huixin Miao and Junjie Cao and Zhixun Su and Risheng Liu},
Title = {SMPR: Single-Stage Multi-Person Pose Regression},
Year = {2020},
Eprint = {arXiv:2006.15576},
}

Acknowledgment

We would like to thank MMDetection team for producing this great object detection toolbox!

License

This project is released under the Apache 2.0 license.