Track human poses in real-time with Tinker Edge T

[Tinker Board 2]

Requirements
- Tinker Board T
- Image version >= Tinker_Edge_T-Mendel-Chef-V1.0.0-20200221 [link]
- USB camera

We have built Google Coral PoseNet on Tinker Edge T image. You can refer to the following introduction for how to use it. 

The PoseNet we used here is posenet_mobilenet_v1_075_481_641_quant_decoder_edgetpu.tflite.

First of all, you need to have a USB camera connected to Tinker Edge T such as the following one.



Then, you can power on Tinker Edge T and launch the terminal console by clicking on the red box as shown in the following figure using mouse.



In the terminal console, issue the following commands to go the the directory /usr/share/project-posenet and run a simple camera example that streams the camera image through posenet and draws the pose on top as an overlay.

$ cd /usr/share/project-posenet
$ python3 pose_camera.py --videosrc=/dev/video2

Bash

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The argument --videosrc is to specify from where to stream the camera image. Here the node /dev/video2 is for USB camera we just connected. For more argument information, you can run with -h as the following to get more information.
 

$ python3 pose_camera.py -h

usage: pose_camera.py [-h] [--mirror] [--model MODEL]

                     [--res {480x360,640x480,1280x720}] [--videosrc VIDEOSRC]

                     [--h264]

optional arguments:
 -h, --help            show this help message and exit

 --mirror              flip video horizontally (default: False)

 --model MODEL         .tflite model path. (default: None)

 --res {480x360,640x480,1280x720}

                       Resolution (default: 640x480)

 --videosrc VIDEOSRC   Which video source to use (default: /dev/video0)

 --h264                Use video/x-h264 input (default: False)

Bash

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In the end, you should see something as the following and you have successfully run the example.

You could change the  pre-trained model by following step. Find more pre-trained model from below link.

https://github.com/google-coral/project-posenet/tree/master/models/resnet

https://github.com/google-coral/project-posenet/tree/master/models/mobilenet

python3 pose_camera.py --videosrc=/dev/video2 –-model={choose the pre-trained model you want to use}

  
For more information, please refer to https://github.com/google-coral/project-posenet.