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_ssd_app is a sample application that draws object names and frames on the model on the camera.
External libraries required for operation
No special mention.
Directory path of the sample app
The C/C++ source code is stored below.
${SDK_DIR}/src/adamapp/yuv_ssd_app
The Python source code is stored below.
${SDK_DIR}/src/adamapp-py/yuv_ssd_app
Use of AI model conversion tool
Before building the sample app, you need to use the AI model conversion tool.
The yuv_ssd_app sample application has the following files, so you can check the operation without using the AI model conversion tool.
${SDK_DIR}/src/adamapp/yuv_ssd_app/data/cnn/mobilenet_priorbox_fp32.bin
${SDK_DIR}/src/adamapp/yuv_ssd_app/data/cnn/mobilenetv1_ssd_cavalry.bin
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 yolov5 sample model.
AI model convert tool: Tensorflow - Technology Partner FAQ (En) - Confluence (atlassian.net)
How to build the sample app (C/C++)
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/yuv_ssd_app/data/cnn/mobilenet_cavalry.bin
make.
$ cd src/adamapp/yuv_ssd_app $ make
It is successful if the .ext file is created in ${SDK_DIR}/src/adamapp/yuv_ssd_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 build the sample app (Python)
See here for building with Python.
How to use the sample app
When you show a TV monitor, sofa, etc. on the camera, the object name and frame are drawn on the corresponding model. Try it yourself.
