Table of contents
Introduction
This explanation assumes that the i-PRO camera application development environment has been completed.
If you are not ready to build the development environment, please refer to here to complete it.
Also, in this tutorial, the SDK installation directory is described as を${SDK_DIR}.
Operation overview
yuv_pose_app is a sample application that draws the skeleton on the model on the camera.
External libraries required for operation
No special mention.
Directory path of the sample app
No C/C++ source code.
The Python source code is stored below.
${SDK_DIR}/src/adamapp-py/yuv_pose_app
Use of AI model conversion tool
Before building the sample app, you need to use the AI model conversion tool.
Get the AI model conversion tool from below and build the environment.
AI model convert tool - Technology Partner FAQ (En) - Confluence (atlassian.net)
It may take several days from the time you make an inquiry to the time it is provided.
After building the environment, refer to the following and convert the sample model.
AI model convert tool: Tensorflow - Technology Partner FAQ (En) - Confluence (atlassian.net)
The setting.conf used for conversion is stored below.
${SDK_DIR}/src/adamapp-py/yuv_pose_app/setting.conf
Here, the model converted file is explained as "tf_pose_estimation_cavalry.bin".
How to build the sample app (Python)
Load the build environment settings file in the SDK installation directory.
$ cd ${SDK_DIR}
$ source setup_env.sh ipro-ambaCV2X
Set the build environment according to each environment.
Here, specify ipro-ambaCV2X.
Next, place the model-converted mobilenet_cavalry.bin file in the sample app directory with the following configuration.
${SDK_DIR}/src/adamapp-py/yuv_pose_app/data/cnn/mobilenet_cavalry.bin
make.
$ cd src/adamapp-py/yuv_pose_app $ make
It is successful if the .ext file is created in ${SDK_DIR}/src/adamapp-py/yuv_pose_app.
Install it on the camera (eg, you can install from the green frame in the image below). Select the created .ext file and install it.
Open the app screen (red frame button in the image below).
If the image of the camera is displayed, it is successful.
How to use the sample app
Please see the picture of the camera and the person.
Mosaic processing is applied around the face.
Appendix
How to change preferences
This application has some preferneces which a user is able to change.
When changing some preferneces, push "AppPrefs" button in "ADAM OPERATION UI" html page.
Resoultion:
Resolution to get YUV images. Specfify HD(1280x720) or FHD(1920x1080).
However, by the ability of the camera, it may not work with the specified value.Frame rate:
Frame rate to get YUV images. Specify 1 or more.
However, by the ability of the camera, it may not work with the specified value.
How to change AI model
The posture estimation model uses the following.
https://github.com/ZheC/tf-pose-estimation
Please download the pb file.
https://github.com/ZheC/tf-pose-estimation/blob/master/models/graph/mobilenet_thin_432x368/graph_freeze.pbUse CV tool to convert.
Please use the setting.conf in the folder for conversion.
Please refer to the following for how to obtain the CV tool.
Ja: https://dev-partner.i-pro.com/space/TPFAQ/961545224
En: https://dev-partner-en.i-pro.com/space/TPFAQEN/967804089Place the converted model file (.bin) in the data/cnn folder.