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<img src=".github/Logo_main_black.png", width="300">
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| **`Linux`** |
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|[](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose)|
OpenPose represents the **first real-time multi-person system to jointly detect human body, hand, and facial keypoints (in total 130 keypoints) on single images**.
<p align="center">
<img src="doc/media/pose_face_hands.gif", width="480">
</p>
**Functionality**:
- **Real-time multi-person keypoint detection**.
- 15 or **18-keypoint body estimation**. **Running time invariant to number of detected people**.
- **2x21-keypoint hand** estimation. Currently, **running time depends** on **number of detected people**.
- **70-keypoint face** estimation. Currently, **running time depends** on **number of detected people**.
- **Input**: Image, video, webcam, and IP camera. Included C++ demos to add your custom input.
- **Output**: Basic image + keypoint display/saving (PNG, JPG, AVI, ...), keypoint saving (JSON, XML, YML, ...), and/or keypoints as array class.
- Available: command-line demo, C++ wrapper, and C++ API.
- **OS**: Ubuntu (14, 16), Windows (8, 10), Nvidia TX2.
## Latest Features
- Sep 2017: **CMake** installer and **IP camera** support!
- Jul 2017: [**Windows portable demo**](doc/installation.md#installation---demo)!
- Jul 2017: **Hands** released!
- Jun 2017: **Face** released!
For further details, check [all released features](doc/released_features.md) and [release notes](doc/release_notes.md).
## Contents
1. [Latest Features](#latest-features)
2. [Results](#results)
3. [Installation, Reinstallation and Uninstallation](#installation-reinstallation-and-uninstallation)
4. [Quick Start](#quick-start)
5. [Output](#output)
6. [Speeding Up OpenPose and Benchmark](#speeding-up-openpose-and-benchmark)
7. [Send Us Failure Cases and Feedback!](#send-us-failure-cases-and-feedback)
8. [Authors and Contributors](#authors-and-contributors)
9. [Citation](#citation)
10. [License](#license)
## Results
### Body Estimation
<p align="center">
<img src="doc/media/dance.gif", width="360">
</p>
### Body, Face, and Hands Estimation
<p align="center">
<img src="doc/media/pose_face.gif", width="360">
</p>
### Body and Hands Estimation
<p align="center">
<img src="doc/media/pose_hands.gif", width="360">
</p>
## Installation, Reinstallation and Uninstallation
See [doc/installation.md](doc/installation.md) for instructions on how to build from source or how to download our portable binaries.
## Quick Start
Most users do not need the [OpenPose C++ API](#openpose-c-api), but they can simply use the basic [Demo](#demo) and/or [OpenPose Wrapper](#openpose-wrapper).
- **Demo**: To easily process images/video/webcam and display/save the results. See [doc/demo_overview.md](doc/demo_overview.md). E.g. run OpenPose in a video with:
```
# Ubuntu
./build/examples/openpose/openpose.bin --video examples/media/video.avi
:: Windows - Portable Demo
bin\OpenPoseDemo.exe --video examples\media\video.avi
```
- **OpenPose Wrapper**: If you want to read a specific input, and/or add your custom post-processing function, and/or implement your own display/saving, check the `Wrapper` tutorial on [examples/tutorial_wrapper/](examples/tutorial_wrapper/). You can create your custom code on [examples/user_code/](examples/user_code/) and quickly compile it by using `make all` in the OpenPose folder (assuming Makefile installer).
- **OpenPose C++ API**: See [doc/library_introduction.md](doc/library_introduction.md).
- **Adding an extra module**: Check [doc/library_add_new_module.md](./library_add_new_module.md).
- **Standalone face or hand detector**:
- **Face** keypoint detection **without body** keypoint detection: If you want to speed it up (but also reduce amount of detected faces), check the OpenCV-face-detector approach in [doc/standalone_face_or_hand_keypoint_detector.md](doc/standalone_face_or_hand_keypoint_detector.md).
- **Use your own face/hand detector**: You can use the hand and/or face keypoint detectors with your own face or hand detectors, rather than using the body detector. E.g. useful for camera views at which the hands are visible but not the body (OpenPose detector would fail). See [doc/standalone_face_or_hand_keypoint_detector.md](doc/standalone_face_or_hand_keypoint_detector.md).
- **Library dependencies**: OpenPose uses default Caffe and OpenCV, as well as any Caffe dependency. The demos additionally use GFlags. It could easily be ported to other deep learning frameworks (Tensorflow, Torch, ...). Feel free to make a pull request if you implement any of those!
## Output
Output (format, keypoint index ordering, etc.) in [doc/output.md](doc/output.md).
## Speeding Up OpenPose and Benchmark
Check the OpenPose Benchmark and some hints to speed up OpenPose on [doc/faq.md#speed-up-and-benchmark](doc/faq.md#speed-up-and-benchmark).
## Send Us Failure Cases and Feedback!
Our library is open source for research purposes, and we want to continuously improve it! So please, let us know if...
1. ... you find videos or images where OpenPose does not seems to work well. Feel free to send them to openposecmu@gmail.com (email only for failure cases!), we will use them to improve the quality of the algorithm!
2. ... you find any bug (in functionality or speed).
3. ... you added some functionality to some class or some new Worker<T> subclass which we might potentially incorporate.
4. ... you know how to speed up or improve any part of the library.
5. ... you have a request about possible functionality.
6. ... etc.
Just comment on GitHub or make a pull request and we will answer as soon as possible! Send us an email if you use the library to make a cool demo or YouTube video!
## Authors and Contributors
OpenPose is authored by [Gines Hidalgo](https://www.gineshidalgo.com/), [Zhe Cao](http://www.andrew.cmu.edu/user/zhecao), [Tomas Simon](http://www.cs.cmu.edu/~tsimon/), [Shih-En Wei](https://scholar.google.com/citations?user=sFQD3k4AAAAJ&hl=en), [Hanbyul Joo](http://www.cs.cmu.edu/~hanbyulj/), and [Yaser Sheikh](http://www.cs.cmu.edu/~yaser/). Currently, it is being maintained by [Gines Hidalgo](https://www.gineshidalgo.com/), [Bikramjot Hanzra](https://www.linkedin.com/in/bikz05), and [Yaadhav Raaj](https://www.linkedin.com/in/yaadhavraaj). The [original CVPR 2017 repo](https://github.com/ZheC/Multi-Person-Pose-Estimation) includes Matlab and Python versions, as well as the training code. The body pose estimation work is based on [the original ECCV 2016 demo](https://github.com/CMU-Perceptual-Computing-Lab/caffe_rtpose).
In addition, OpenPose would not be possible without the [CMU Panoptic Studio dataset](http://domedb.perception.cs.cmu.edu/).
We would also like to thank all the people who helped OpenPose in any way. The main contributors are listed in [doc/contributors.md](doc/contributors.md).
## Citation
Please cite these papers in your publications if it helps your research (the face keypoint detector was trained using the same procedure described in [Simon et al. 2017]):
@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}
}
@inproceedings{simon2017hand,
author = {Tomas Simon and Hanbyul Joo and Iain Matthews and Yaser Sheikh},
booktitle = {CVPR},
title = {Hand Keypoint Detection in Single Images using Multiview Bootstrapping},
year = {2017}
}
@inproceedings{wei2016cpm,
author = {Shih-En Wei and Varun Ramakrishna and Takeo Kanade and Yaser Sheikh},
booktitle = {CVPR},
title = {Convolutional pose machines},
year = {2016}
}
## License
OpenPose is freely available for fr
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openpose源码 （464个子文件） 
video.avi 1.33MB
getModels.bat 2KB download_3rdparty_and_models.bat 1KB getCaffe3rdparty.bat 613B getFreeglut.bat 612B getOpenCV.bat 598B getCaffe.bat 597B Cuda.cmake 12KB Utils.cmake 2KB FindCuDNN.cmake 2KB FindGFlags.cmake 2KB FindGlog.cmake 1KB FindCaffe.cmake 525B FindSpinnaker.cmake 433B COPYING 34KB 2_user_synchronous.cpp 34KB 1_user_asynchronous_output.cpp 31KB 3_user_asynchronous.cpp 31KB pointGrey.cpp 30KB openpose.cpp 29KB 1_custom_post_processing.cpp 28KB 3d.cpp 24KB handExtractorCaffe.cpp 23KB bodyPartConnectorBase.cpp 20KB renderer.cpp 18KB poseExtractorCaffe.cpp 18KB poseParameters.cpp 17KB faceExtractorCaffe.cpp 16KB keypoint.cpp 15KB fileStream.cpp 15KB array.cpp 14KB poseExtractor.cpp 14KB producer.cpp 12KB 4_user_input_processing_output_and_datum.cpp 11KB handDetector.cpp 11KB 2_user_processing_function.cpp 11KB flagsToOpenPose.cpp 11KB 3_user_input_processing_and_output.cpp 11KB 2_extract_pose_or_heatmat_from_image.cpp 10KB fileSystem.cpp 10KB 1_extract_from_image.cpp 9KB poseGpuRenderer.cpp 9KB 1_openpose_read_and_display.cpp 9KB openCv.cpp 8KB reconstruction3D.cpp 8KB gui.cpp 8KB bodyPartConnectorCaffe.cpp 8KB netCaffe.cpp 8KB nmsBase.cpp 8KB rectangle.cpp 8KB datum.cpp 7KB resizeAndMergeCaffe.cpp 7KB errorAndLog.cpp 7KB profiler.cpp 7KB faceDetector.cpp 7KB point.cpp 6KB nmsCaffe.cpp 6KB resizeAndMergeBase.cpp 6KB gpuRenderer.cpp 5KB maximumCaffe.cpp 5KB guiInfoAdder.cpp 5KB webcamReader.cpp 5KB scaleAndSizeExtractor.cpp 5KB cameraParameters.cpp 5KB string.cpp 4KB imageDirectoryReader.cpp 4KB handFromJsonTest.cpp 4KB jsonOfstream.cpp 4KB cocoJsonSaver.cpp 4KB videoCaptureReader.cpp 4KB cuda.cpp 4KB frameDisplayer.cpp 4KB handGpuRenderer.cpp 4KB renderer.cpp 4KB faceGpuRenderer.cpp 3KB handExtractor.cpp 3KB faceExtractor.cpp 3KB videoSaver.cpp 3KB maximumBase.cpp 3KB keypointScaler.cpp 3KB poseParametersRender.cpp 3KB heatMapSaver.cpp 3KB faceDetectorOpenCV.cpp 2KB poseCpuRenderer.cpp 2KB wrapperStructPose.cpp 2KB cvMatToOpInput.cpp 2KB poseRenderer.cpp 2KB cvMatToOpOutput.cpp 2KB imageSaver.cpp 2KB keypointSaver.cpp 1KB handDetectorFromTxt.cpp 1KB renderPose.cpp 1KB renderHand.cpp 1KB wrapperStructOutput.cpp 1KB fileSaver.cpp 1KB personIdExtractor.cpp 1KB handCpuRenderer.cpp 1KB renderFace.cpp 1KB ipCameraReader.cpp 1012B opOutputToCvMat.cpp 928B共 464 条
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