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Copy file name to clipboardexpand all lines: .github/issue_template.md
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### Posting rules
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1.**No duplicated posts, only 1 new post opened a day, and up to 2 opened a week**. Otherwise, extrict user bans will occur.
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- Check the [FAQ](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/4_faq.md) section, other GitHub issues, and general documentation before posting. E.g., **low-speed, out-of-memory, output format, 0-people detected, installation issues, ...**).
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- Check the [FAQ](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/05_faq.md) section, other GitHub issues, and general documentation before posting. E.g., **low-speed, out-of-memory, output format, 0-people detected, installation issues, ...**).
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- Keep posting all your issues in the same post.
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- No bans if you are unsure whether the post is duplicated!
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2.**Fill all** the **Your System Configuration section** if you are facing an error or unexpected behavior. Some posts (e.g., feature requests) might not require it.
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- Portable demo or compiled library?
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10. If **speed performance** issue:
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- Report OpenPose timing speed based on [this link](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/5_maximizing_openpose_speed.md#profiling-speed).
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- Report OpenPose timing speed based on the [profiling documentation](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/06_maximizing_openpose_speed.md#profiling-speed).
Copy file name to clipboardexpand all lines: README.md
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[**OpenPose**](https://github.com/CMU-Perceptual-Computing-Lab/openpose) has represented the **first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images**.
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It is **authored by**[**Ginés Hidalgo**](https://www.gineshidalgo.com), [**Zhe Cao**](https://people.eecs.berkeley.edu/~zhecao), [**Tomas Simon**](http://www.cs.cmu.edu/~tsimon), [**Shih-En Wei**](https://scholar.google.com/citations?user=sFQD3k4AAAAJ&hl=en), [**Hanbyul Joo**](https://jhugestar.github.io), **and**[**Yaser Sheikh**](http://www.cs.cmu.edu/~yaser). It is **maintained by**[**Ginés Hidalgo**](https://www.gineshidalgo.com)**and**[**Yaadhav Raaj**](https://www.raaj.tech). 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 [has helped OpenPose in any way](doc/8_authors_and_contributors.md).
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It is **authored by**[**Ginés Hidalgo**](https://www.gineshidalgo.com), [**Zhe Cao**](https://people.eecs.berkeley.edu/~zhecao), [**Tomas Simon**](http://www.cs.cmu.edu/~tsimon), [**Shih-En Wei**](https://scholar.google.com/citations?user=sFQD3k4AAAAJ&hl=en), [**Hanbyul Joo**](https://jhugestar.github.io), **and**[**Yaser Sheikh**](http://www.cs.cmu.edu/~yaser). It is **maintained by**[**Ginés Hidalgo**](https://www.gineshidalgo.com)**and**[**Yaadhav Raaj**](https://www.raaj.tech). 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 [has helped OpenPose in any way](doc/09_authors_and_contributors.md).
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2.[Features](#features)
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3.[Related Work](#related-work)
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4.[Installation](#installation)
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5.[Quick Start](#quick-start)
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5.[Quick Start Overview](#quick-start-overview)
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6.[Send Us Feedback!](#send-us-feedback)
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7.[Citation](#citation)
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8.[License](#license)
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## Results
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### Bodyand Foot Estimation
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### Whole-body (Body, Foot, Face, and Hands) 2D Pose Estimation
<sup>Testing the <a href="https://www.youtube.com/watch?v=2DiQUX11YaY" target="_blank"><i>Crazy Uptown Funk flashmob in Sydney</i></a> video sequence with OpenPose</sup>
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<sup>Testing OpenPose: (Left) <a href="https://www.youtube.com/watch?v=2DiQUX11YaY" target="_blank"><i>Crazy Uptown Funk flashmob in Sydney</i></a> video sequence. (Center and right) Authors <a href="https://www.gineshidalgo.com" target="_blank">Ginés Hidalgo</a> and <a href="http://www.cs.cmu.edu/~tsimon" target="_blank">Tomas Simon</a> testing face and hands</sup>
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</p>
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### 3D Reconstruction Module (Body, Foot, Face, and Hands)
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### Whole-body 3D Pose Reconstruction and Estimation
<sup><a href="https://ziutinyat.github.io/" target="_blank">Tianyi Zhao</a> and <a href="https://www.gineshidalgo.com" target="_blank">Ginés Hidalgo</a> testing the <a href="https://github.com/CMU-Perceptual-Computing-Lab/openpose_unity_plugin" target="_blank">OpenPose Unity Plugin</a></sup>
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</p>
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### Runtime Analysis
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We show an inference time comparison between the 3 available pose estimation libraries (same hardware and conditions): OpenPose, Alpha-Pose (fast Pytorch version), and Mask R-CNN. The OpenPose runtime is constant, while the runtime of Alpha-Pose and Mask R-CNN grow linearly with the number of people. More details [**here**](https://arxiv.org/abs/1812.08008).
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-**OS**: Ubuntu (20, 18, 16, 14), Windows (10, 8), Mac OSX, Nvidia TX2.
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-**Hardware compatibility**: CUDA (Nvidia GPU), OpenCL (AMD GPU), and non-GPU (CPU-only) versions.
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-**Usage Alternatives**:
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-[**Command-line demo**](doc/1_demo.md) for built-in functionality.
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-[**C++ API**](examples/tutorial_api_cpp/) and [**Python API**](doc/3_python_api.md) for custom functionality. E.g., adding your custom inputs, pre-processing, post-posprocessing, and output steps.
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-[**Command-line demo**](doc/01_demo.md) for built-in functionality.
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-[**C++ API**](doc/04_cpp_api.md/) and [**Python API**](doc/03_python_api.md) for custom functionality. E.g., adding your custom inputs, pre-processing, post-posprocessing, and output steps.
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For further details, check the [major released features](doc/6_major_released_features.md) and [release notes](doc/7_release_notes.md) docs.
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For further details, check the [major released features](doc/07_major_released_features.md) and [release notes](doc/08_release_notes.md) docs.
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## Related Work
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-[**OpenPose training code**](https://github.com/CMU-Perceptual-Computing-Lab/openpose_train)
- OpenPose papers published in [**IEEE TPAMI** and **CVPR**](#citation). [Cite them](#citation) in your publications if it helps your research!
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- OpenPose papers published in **IEEE TPAMI and CVPR**. Cite them in your publications if OpenPose helps your research! (Links and more details in the [Citation](#citation) section below).
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## Installation
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If you want to use OpenPose without compiling or writing any code, simply [download and use the latest Windows portable version of OpenPose](doc/installation/0_index.md#windows-portable-demo)! Otherwise, you can also [build OpenPose from source](doc/installation/0_index.md#compiling-and-running-openpose-from-source).
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If you want to use OpenPose without installing or writing any code, simply [download and use the latest Windows portable version of OpenPose](doc/installation/0_index.md#windows-portable-demo)!
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See [doc/installation/0_index.md](doc/installation/0_index.md) for more details.
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Otherwise, you could [build OpenPose from source](doc/installation/0_index.md#compiling-and-running-openpose-from-source). See the [installation doc](doc/installation/0_index.md) for all the alternatives.
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## Quick Start
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Most users do not need to know C++ or Python, they can simply use the OpenPose Demo in their command-line tool (e.g., PowerShell/Terminal). E.g., this would run OpenPose on the webcam and display the body keypoints:
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## Quick Start Overview
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Simply use the OpenPose Demo from your favorite command-line tool (e.g., Windows PowerShell or Ubuntu Terminal). E.g., this example runs OpenPose on your webcam and displays the body keypoints:
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```
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# Ubuntu
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./build/examples/openpose/openpose.bin
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You can also add any of the available flags in any order. Do you also want to add face and/or hands? Add the `--face` and/or `--hand` flags. Do you also want to save the output keypoints on JSON files on disk? Add the `--write_json` flag, etc.
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You can also add any of the available flags in any order. E.g., the following example runs on a video (`--video {PATH}`), enables face (`--face`) and hands (`--hand`), and saves the output keypoints on JSON files on disk (`--write_json {PATH}`).
After [installing](#installation) OpenPose, check [doc/0_index.md](doc/0_index.md) for a quick overview of all the alternatives and tutorials.
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Optionally, you can also extend OpenPose's functionality from its Python and C++ APIs. After [installing](doc/installation/0_index.md) OpenPose, check its [official doc](doc/00_index.md) for a quick overview of all the alternatives and tutorials.
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## Send Us Feedback!
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Our library is open source for research purposes, and we want to continuously improve it! So let us know if you...
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1. Find any bug (in functionality or speed).
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2. Add some functionality on top of OpenPose which we might want to add.
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3. Know how to speed up or improve any part of OpenPose.
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4. Want to share your cool demo or project made on top of OpenPose (you can email it to us too!).
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Just create a new GitHub issue or a pull request and we will answer as soon as possible!
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Our library is open source for research purposes, and we want to improve it! So let us know (create a new GitHub issue or pull request, email us, etc.) if you...
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1. Find/fix any bug (in functionality or speed) or know how to speed up or improve any part of OpenPose.
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2. Want to add/show some cool functionality/demo/project made on top of OpenPose. We can add your project link to our [Community-based Projects](doc/10_community_projects.md) section or even integrate it with OpenPose!
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## Citation
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Please cite these papers in your publications if it helps your research. All of OpenPose is based on [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://arxiv.org/abs/1812.08008), while the hand and face detectors also use [Hand Keypoint Detection in Single Images using Multiview Bootstrapping](https://arxiv.org/abs/1704.07809) (the face detector was trained using the same procedure than the hand detector).
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Please cite these papers in your publications if OpenPose helps your research. All of OpenPose is based on [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://arxiv.org/abs/1812.08008), while the hand and face detectors also use [Hand Keypoint Detection in Single Images using Multiview Bootstrapping](https://arxiv.org/abs/1704.07809) (the face detector was trained using the same procedure than the hand detector).
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@article{8765346,
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author = {Z. {Cao} and G. {Hidalgo Martinez} and T. {Simon} and S. {Wei} and Y. A. {Sheikh}},
Copy file name to clipboardexpand all lines: doc/00_index.md
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==========================
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The OpenPose documentation is available in 2 different formats, choose your preferred one!
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- As a traditional website (recommended): [cmu-perceptual-computing-lab.github.io/openpose/web/html/doc](https://cmu-perceptual-computing-lab.github.io/openpose/web/html/doc/).
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- As markdown files: [github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/0_index.md](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/0_index.md).
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- As a traditional website (recommended): [cmu-perceptual-computing-lab.github.io/openpose/web/html/doc/](https://cmu-perceptual-computing-lab.github.io/openpose/web/html/doc/).
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- As markdown files: [github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/00_index.md](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/00_index.md).
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Most users can simply use the OpenPose Demo without reading any C++/Python code. Users that need to add additional functionality (new inputs, outputs, etc) should check the C++/Python APIs:
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- If you face issues with any of these steps, keep in mind to check the [FAQ](installation/4_faq.md) section.
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- If you face issues with any of these steps, keep in mind to check the [FAQ](installation/05_faq.md) section.
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- The first step for any software, [install it](installation/0_index.md)!
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-[OpenPose Demo](1_demo.md): Choose your input (e.g., images, video, webcam), set of algorithms (body, hand, face), output (e.g., display, JSON keypoint saving, image+keypoints), and run OpenPose from your terminal or PowerShell!
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-[OpenPose Demo](01_demo.md): Choose your input (e.g., images, video, webcam), set of algorithms (body, hand, face), output (e.g., display, JSON keypoint saving, image+keypoints), and run OpenPose from your terminal or PowerShell!
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- E.g.: Given an input video (`--video`), extract body (by default), face (`--face`) and hand (`--hand`) keypoints, save the keypoints in a JSON file (`--write_json`), and display (by default) the results in the screen. You can remove any of the flags to remove that particular functionality or add any other.
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# Ubuntu
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-[Output information](2_output.md): Learn about the output format, keypoint index ordering, etc.
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-[Output information](02_output.md): Learn about the output format, keypoint index ordering, etc.
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-[OpenPose Python API](3_python_api.md): Almost all the OpenPose functionality, but in Python!
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-[OpenPose Python API](03_python_api.md): Almost all the OpenPose functionality, but in Python! If you want to read a specific input, and/or add your custom post-processing function, and/or implement your own display/saving.
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-[OpenPose C++ API](../examples/tutorial_api_cpp/): If you want to read a specific input, and/or add your custom post-processing function, and/or implement your own display/saving.
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- You should be familiar with the [OpenPose Demo](1_demo.md) and the main OpenPose flags before trying to read the C++ or Python API examples. Otherwise, it will be way harder to follow.
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- For quick prototyping: You can easily **create your custom code** on [examples/user_code/](../examples/user_code/) and CMake will automatically compile it together with the whole OpenPose project. See [examples/user_code/README.md](../examples/user_code/README.md) for more details.
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-[OpenPose C++ API](04_cpp_api.md): If you want to read a specific input, and/or add your custom post-processing function, and/or implement your own display/saving.
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-[Maximizing OpenPose speed and benchmark](5_maximizing_openpose_speed.md): Check the OpenPose Benchmark as well as some hints to speed up and/or reduce the memory requirements for OpenPose.
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-[Maximizing OpenPose speed and benchmark](06_maximizing_openpose_speed.md): Check the OpenPose Benchmark as well as some hints to speed up and/or reduce the memory requirements for OpenPose.
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-[Calibration toolbox](advanced/calibration_module.md) and [3D OpenPose](advanced/3d_reconstruction_module.md): Calibrate your cameras for 3D OpenPose (or any other stereo vision tasks) and start obtaining 3D keypoints!
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