This digital signage app dynamically outputs advertisements based on facial detection and age/gender inference using the Intel Neural Compute Stick 2.
The example does face detection on a camera frame using face-detection-retail.0004, crops the detected faces, then does age and gender inference using the age-gender network. The example outputs different advertisements based on user's demographics using the age-gender-recognition model. All models can be found on the Open Model Zoo. This sample uses pre-compiled IRs, so the model optimizer is not utilized.
Images in the advertisement_images directory are subject to the licenses.txt file within the directory.
To run the example code do the following :
- Open a terminal and change directory to the sample base directory
- Type the following command in the terminal:
make all
After building the example you can run the example code by doing the following :
- Open a terminal and change directory to the sample base directory
- Type the following command in the terminal:
make run
When the application runs normally, another window should pop up and show the feed from the webcam/usb cam. The program should perform inferences on faces on frames taken from the webcam/usb cam.
This program requires:
- 1 NCS1/NCS2 device
- OpenVINO 2020.1 Toolkit
- A webcam (laptop or USB)
Note: All development and testing has been done on Ubuntu 16.04 on an x86-64 machine. ARM devices may be supported, but has not been verified.
Provided Makefile has various targets that help with the above mentioned tasks.
Runs the sample application.
Shows available targets.
Builds and/or gathers all the required files needed to run the application.
Gathers all of the required data need to run the sample.
Builds all of the dependencies needed to run the sample.
Checks required packages that aren't installed as part of the OpenVINO installation.
Checks required packages that are able to be uninstalled.
Removes all the temporary files that are created by the Makefile.