AI on the Jetson Nano - Face and Eye Detection with Haar Cascades in OpenCV

Learn how to implement face and eye detection using Haar Cascades in OpenCV on the NVIDIA Jetson Nano. Explore the process of setting up the Raspberry Pi camera, accessing OpenCV's pre-trained XML files for face and eye detection, and applying grayscale conversion for improved accuracy. Discover techniques for drawing bounding boxes around detected faces and eyes, working with regions of interest (ROI), and testing the implementation on both still images and live webcam feeds. Gain practical experience in computer vision and AI applications while working with hardware specifically designed for edge computing and machine learning tasks.

Intro
Open Visual Studio
Raspberry Pi Camera
Starting Point
OpenCV Tree
GitHub
Face Detection
Face Cascade
Face XML
Eye XML
Grayscale
Find Faces
Box Faces
ROI Color
Eye Detection
List of Eyes
Eye Box
Testing
Eye Cascade
Webcam
CV to Circle
Eyes
Lesson Recap
Homework