Skip to content

Latest commit

 

History

History
95 lines (76 loc) · 2.77 KB

README.md

File metadata and controls

95 lines (76 loc) · 2.77 KB

exercise-pose-analyzer

Demo

Demo on YouTube - 1
Demo on YouTube - 2
Demo on YouTube - 3

Usage

Install Docker and Kitematic

Pull docker image

$ docker pull jgravity/tensorflow-opencv:odin
$ docker run -it --name odin jgravity/tensorflow-opencv:odin bin/bash

Use nvidia-docker instead of docker to use GPU

Download/Install code

# git clone https://github.com/PJunhyuk/exercise-pose-analyzer
# cd exercise-pose-analyzer
# chmod u+x ./compile.sh && ./compile.sh && cd models/coco && chmod u+x download_models_wget.sh && ./download_models_wget.sh && cd -

Download sample videos in testset

# cd testset && chmod u+x ./download_testset_wget.sh && ./download_testset_wget.sh && cd -

Just get pose of people

# python video_pose.py -f '{video_file_name}'

Qualified supporting video type: mov, mp4

Analyze shoulder press

# python exercise_analyzer.py -f '{video_file_name}' -e 'sp'
Arguments

-f, --videoFile = Path to Video File
-w, --videoWidth = Width of Output Video
-o, --videoType = Extension of Output Video -e, --exerciseType = Type of Exersize

  • -e 'sp': shoulder press
  • -e 'dc': dumbbell curl

Dependencies

Use Docker jgravity/tensorflow-opencv,

or install

  • python 3.5.3
  • opencv 3.1.0
  • jupyter 4.2.1
  • git 2.1.4
  • tensorflow 1.3.0
  • pip packages
    • scipy 0.19.1
    • scikit-image 0.13.1
    • matplotlib 2.0.2
    • pyYAML 3.12
    • easydict 1.7
    • Cython 0.27.1
    • munkres 1.0.12
    • moviepy 0.2.3.2
    • dlib 19.7.0
    • imageio 2.1.2

Reference

Citation

@inproceedings{insafutdinov2017cvpr,
    title = {ArtTrack: Articulated Multi-person Tracking in the Wild},
    booktitle = {CVPR'17},
    url = {http://arxiv.org/abs/1612.01465},
    author = {Eldar Insafutdinov and Mykhaylo Andriluka and Leonid Pishchulin and Siyu Tang and Evgeny Levinkov and Bjoern Andres and Bernt Schiele}
}

@article{insafutdinov2016eccv,
    title = {DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model},
    booktitle = {ECCV'16},
    url = {http://arxiv.org/abs/1605.03170},
    author = {Eldar Insafutdinov and Leonid Pishchulin and Bjoern Andres and Mykhaylo Andriluka and Bernt Schiele}
}

Code

pose-tensorflow - Human Pose estimation with TensorFlow framework
people-counting-classification - Odin: People counting and classification in videos based on pose estimation Edit