Real time Face Detection on Brainy Pi

In recent years, the field of computer vision has witnessed remarkable progress due to advancements in deep learning and hardware capabilities. One of the applications of computer vision is live face detection using opencv haar-cascade model, which has become increasingly popular for various purposes such as security, identification, and emotion recognition. Brainy Pi, a single-board computer, AI enabled SBC that can be used for various AIoT projects. In this blog, we will explore how to perform Real time Face Detection on Brainy Pi using a USB camera. We will discuss the required hardware and software, and step-by-step instructions to implement the face detection algorithm on the Brainy Pi platform.

Components Required

1. Brainy pi

2. Monitor (doesn’t have to be touch screen)

3. Keyboard mouse

4. Type C Adapter for BrainyPi

5. USB Camera

Running Real time Face Detection on Brainy Pi

1. Clone the Repository

git clone https://github.com/brainypi/brainypi-real-time.git
cd brainypi-real-time/face-detection

2. Run the applications

python3 liveFaceDet.py

It will start the camera and start detecting faces.

Resources Consumed

• Before running the application

• After running the application

Conclusion

We have implemented Real time application on Brainy Pi successfully and observed the performance !! It can be optimized by running inference in C++ or using other light-weight AI frameworks.