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 ${SDK_DIR}.

Operation overview

web_template_app is a sample app with display and setting functions often required for WEB UI apps.

Also, an AI model the same as other sample app yuv_ssd_app is used.

External libraries required for operation

To build with C/C++, need below:

libjpeg

To build with Python, need below:

Numpy
OpenCV

The use of external libraries will be explained later.

Directory path of the sample app

The C/C++ source code is stored below.

${SDK_DIR}/src/adamapp/web_template_app

The Python source code is stored below.

${SDK_DIR}/src/adamapp-py/web_template_app

How to build the sample app (C/C++)

See here for building with C/C++.

However, the header file to be used must be stored below.
Please refer to ADD_INCLUDE_PATH in Makefile for details.

${SDK_DIR}/src/adamapp/web_template_app\external\include\libjpeg-turbo-1.5.3

You can confirm that it works by storing the file below.

jconfig.h
jerror.h
jmorecfg.h
jpeglib.h

Display comments for developers

In the C/C++ version,
【to enable】
make clean
make CFLAG=BASIC_MSG

【to disable】
make clean
make

How to build the sample app (Python)

See here for building with Python.

How to use the sample app

This shows how to use the sample app. Screenshots here include comments for developers.

・Setting the detection area

Click the "Detection Area" tab and click anywhere on the live image. Below, the detection areas are set for 1 (white): bicycle and 2 (blue): person.

・Confirm that it is detected

Click the "Live" tab and check "show alarm history" on the bottom left. When a person appears in the live image, you can confirm that the alarm name: Person (Detection Area 2) is detected in the list on the right and remains in the history.