Difference between revisions of "Full Body Pose Estimation for Sports Analysis - Getting Started"
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[[File:DispTEC2020 HW setup render.png|900px|thumb|center|Render showing a possible hardware setup.]] | [[File:DispTEC2020 HW setup render.png|900px|thumb|center|Render showing a possible hardware setup.]] | ||
| − | ==How to Get the Code | + | ==How to Get the Code== |
To get the code you only need to clone the repository of the full-body pose estimation library as follows: | To get the code you only need to clone the repository of the full-body pose estimation library as follows: | ||
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$git clone https://gitlab.com/RidgeRun/tec/disptec-2020 | $git clone https://gitlab.com/RidgeRun/tec/disptec-2020 | ||
| − | ==How to Install the Library | + | ==How to Install the Library== |
In order to install the library, you need to first install the dependencies listed below and then follow the instructions in the installation section. | In order to install the library, you need to first install the dependencies listed below and then follow the instructions in the installation section. | ||
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pip3 install dist/rrpose-0.0.1.tar.gz | pip3 install dist/rrpose-0.0.1.tar.gz | ||
| − | ==How to Use the Library | + | ==How to Use the Library== |
Here, we will briefly explain every part of a demo application to provide a better understanding of library usage. However, if you would like to get deeper into each module functionality, we recommend you visit the specific module's page in this wiki. | Here, we will briefly explain every part of a demo application to provide a better understanding of library usage. However, if you would like to get deeper into each module functionality, we recommend you visit the specific module's page in this wiki. | ||
Revision as of 14:49, 17 September 2020
 | WORK IN PROGRESS. Please Contact RidgeRun OR email to support@ridgerun.com if you have any questions. |
Contents
Introduction
This wiki is intended to guide the user in the first steps of getting the code and installation of the full-body pose estimation library. Additionally, a demo of an application is attached to explain the main concepts of how to use the library.
Required Hardware
The project requires the hardware shown in the next image. The use of the Nvidia Jetson TX2 and the Connect Tech Astro Carrier Board allows the synchronization by the hardware of the Leopard Imaging LI-OV10635-SER camera modules, which is required by the system to perform multi-view pose estimation.
You can position the cameras however you want. The more different the views captured, the more information the system will have to estimate the human pose. In the next image, you can appreciate the camera setup used by us for testing the system with limited space, shown using a 3D scene render. Please note, that even with the cameras facing the person in a similar way, they are far apart from one another and point from different angles.
How to Get the Code
To get the code you only need to clone the repository of the full-body pose estimation library as follows:
$git clone https://gitlab.com/RidgeRun/tec/disptec-2020
How to Install the Library
In order to install the library, you need to first install the dependencies listed below and then follow the instructions in the installation section.
Dependencies
- OpenCV >= 4
- Python >= 3.7
- Real-time 3D Multi-person Pose Estimation Library
Installation
1. Go to the cloned repository directory:
cd disptec-2020/
2. Install the Python requirements:
pip3 install -r requirements.txt
3. Generate the library package:
python3 setup.py sdist bdist_wheel
4. Install the rrpose library:
pip3 install dist/rrpose-0.0.1.tar.gz
How to Use the Library
Here, we will briefly explain every part of a demo application to provide a better understanding of library usage. However, if you would like to get deeper into each module functionality, we recommend you visit the specific module's page in this wiki.
(demo example code)
