SwiftOpenPose

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tf-openpose Based iOS Project

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최종 버전 다운로드 (.zip)

- CaffeToMLModel.md
- openpose_minimum.md
- - .gitignore
  - README.md
- iTunesArtwork.png
- swiftopenpose_result.png
- coco_pose.py
- - LaunchScreen.storyboard
  - Main.storyboard
- - hadou.bin
  - hadou.jpg
  - person1.bin
  - person1.jpg
- - AppDelegate.swift
  - Common.swift
  - Estimator.swift
  - OpenCVWrapper.h
  - OpenCVWrapper.mm
  - ViewController.swift
- Info.plist
- SwiftOpenPose-Bridging-Header.h
- - contents.xcworkspacedata
- project.pbxproj
- contents.xcworkspacedata
.gitignore
LICENCE
Podfile
Podfile.lock
README.md

// repository documentation

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# SwiftOpenPose

This project was developed by transplanting [tf-openpose](https://github.com/ildoonet/tf-openpose) to Swift.  
Community cooperation is welcome.

![swiftopenpose_result](https://raw.githubusercontent.com/infocom-tpo/SwiftOpenPose/master/images/swiftopenpose_result.png)

## Environment
* iOS11
* Xcode9

## Training Model

There are two learning models available for this project.

* OpenPose Caffe-Model
  * [Convert from OpenPose Caffe-Model to MLModel](doc/CaffeToMLModel.md)
* tf-openpose Mobilenet Model (instance_normalization Disabled Version)
  * [infocom-tpo/tf-openpose](https://github.com/infocom-tpo/tf-openpose/tree/master/convert) .. Model Training and Converter
  * [MobileOpenPose.mlmodel](https://s3-ap-northeast-1.amazonaws.com/swiftopenpose/MobileOpenPose.mlmodel) .. Model Download

## Performance comparison

* BenchMark Hardware: iPad 2017
  * OpenPose Caffe-Model
    * processing time .. range 2-4 Sec.
  * tf-openpose Mobilenet Model
    * processing time .. Less than 1 sec

## Dependencies Library

* [UpSurge](https://github.com/aleph7/Upsurge)
* [OpenCV](https://opencv.org/releases.html)
  * Download of iOS Pack
  * [Opencv lightweight version](doc/openpose_minimum.md)

## Installation

```
$ git clone https://github.com/infocom-tpo/SwiftOpenPose.git
$ cd SwiftOpenPose
$ pod install
$ curl -o SwiftOpenPose/Resources/MobileOpenPose.mlmodel \
https://s3-ap-northeast-1.amazonaws.com/swiftopenpose/MobileOpenPose.mlmodel
```

## Examples

* [Bone Detecter](examples/BoneDetecter)  
This app exports a video with detected bones to photo library.  
You can shoot or select a video to detect bones.

![before1](https://raw.githubusercontent.com/infocom-tpo/SwiftOpenPose/master/examples/BoneDetecter/images/before1.gif)
![after1](https://raw.githubusercontent.com/infocom-tpo/SwiftOpenPose/master/examples/BoneDetecter/images/after1.gif)

## iTunes Store App

[Stickman Animator](https://itunes.apple.com/jp/app/stickman-animator/id1337589939?mt=8)

Stickman Animator is an app to make animations of stickman from videos of people.

## Blogs

* Explanation by Japanese
  * [AI初心者がOpenPoseのモバイル実装に取り組んだ話](https://qiita.com/otmb/items/b924b5f600db1ce11037)

## Reference

* [OpenPose](https://github.com/CMU-Perceptual-Computing-Lab/openpose)
* [tf-openpose](https://github.com/ildoonet/tf-openpose)
* [OpenPose Caffe Model Convert to CoreML Model](https://gist.github.com/otmb/7b2e1caf3330b97c82dc217af5844ad5)
* [エネルギー波を繰り出す女子高生](https://www.pakutaso.com/20151016274post-6129.html)

## Development By Infocom TPO

[Infocom TPO](https://lab.infocom.co.jp/)

## License

SwiftOpenPose is available under the MIT license. See the LICENSE file for more info.

## Citation

```
@inproceedings{cao2017realtime,
  author = {Zhe Cao and Tomas Simon and Shih-En Wei and Yaser Sheikh},
  booktitle = {CVPR},
  title = {Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields},
  year = {2017}
}
```

SwiftOpenPose

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