This project was developed by transplanting tf-openpose to Swift.
Community cooperation is welcome.
- iOS11
- Xcode9
There are two learning models available for this project.
- OpenPose Caffe-Model
- tf-openpose Mobilenet Model (instance_normalization Disabled Version)
- infocom-tpo/tf-openpose .. Model Training and Converter
- MobileOpenPose.mlmodel .. Model Download
- BenchMark Hardware: iPad 2017
- OpenPose Caffe-Model
- processing time .. range 2-4 Sec.
- tf-openpose Mobilenet Model
- processing time .. Less than 1 sec
- OpenPose Caffe-Model
- UpSurge
- OpenCV
- Download of iOS Pack
- Opencv lightweight version
$ 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
- Bone Detecter
This app exports a video with detected bones to photo library.
You can shoot or select a video to detect bones.
Stickman Animator is an app to make animations of stickman from videos of people.
- Explanation by Japanese
SwiftOpenPose is available under the MIT license. See the LICENSE file for more info.
@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}
}