
Learn to implement face recognition and identification on Jetson Nano using OpenCV and face_recognition library. Covers training for new faces, identifying unknowns, and practical applications.

Learn to install and use facial recognition library for OpenCV on Jetson Nano, enabling face detection and identification in frames. Enhance your AI project with advanced computer vision capabilities.

Learn to detect faces and eyes in video using Haar Cascades with OpenCV on the Jetson Nano. Practical implementation of computer vision techniques for real-time facial feature recognition.

Learn to track objects using OpenCV on Jetson Nano, controlling a camera with servos to keep the target centered. Implement computer vision and robotics skills for real-time object tracking applications.

Learn to control servos with the Jetson Nano using PCA9685, including setup, programming, and movement control. Gain hands-on experience in robotics and automation with this practical tutorial.

Learn to track objects using contours in OpenCV on the Jetson Nano. Explore masking, fine-tuning, and bounding rectangles for effective object detection and tracking in AI applications.

Learn to track objects in OpenCV using HSV color space, including image conversion, parameter setting with trackbars, and creating foreground/background masks for effective color-based object tracking.

Learn to create and manipulate live moving watermarks in OpenCV using threshold and masking techniques for video feeds on the Jetson Nano.

Explore thresholding and masking techniques in OpenCV to manipulate image foregrounds and backgrounds independently, enhancing your AI skills on the Jetson Nano platform.

Learn to create Region of Interest in OpenCV using mouse events and clicks, enhancing image processing capabilities for AI applications on Jetson Nano.

Learn to work with Region of Interest (ROI) in OpenCV on Jetson Nano, including setting up rectangles, creating and colorizing ROIs, and animating cuts for enhanced image processing capabilities.

Learn to build a self-leveling platform using Arduino, BNO055 sensor, and servos. Hands-on tutorial covers circuit assembly, mechanical construction, and servo control for tilt stabilization.

Learn to work with Region of Interest (ROI) in OpenCV for AI applications on Jetson Nano, including live video processing and practical examples.

Learn to read and write video files using OpenCV on the Jetson Nano, enabling efficient video processing and manipulation for AI applications.

Learn to resize and organize image windows in OpenCV for efficient AI image processing on the Jetson Nano, enhancing your ability to analyze intermediate stages of processing.

Learn to launch and view Raspberry Pi camera and webcam streams on Jetson Nano using OpenCV. Covers setup, camera settings, and basic image processing techniques for AI applications.

Learn to achieve stable and responsive tilt measurements using accelerometers, gyros, and a complimentary filter for accurate pitch and roll approximation in IMU applications.

Learn to approximate pitch and roll using a 3-axis accelerometer in this hands-on tutorial. Explore practical applications, limitations, and implementation techniques for tilt measurement in Arduino projects.

Learn to calibrate the BNO055 9-axis inertial measurement sensor for accurate data collection in Arduino projects. Covers setup, data printing, and visualization using Serial Plotter.

Explore ESP32's DAC capabilities through hands-on experiments, creating oscilloscope art and a fruit-based musical instrument while learning about voltage control and waveform generation.

Learn to build and control a Mecanum wheel robot car using ESP32 boards, featuring ESP-NOW communication, joystick control, TFT display, and NeoPixel LEDs. Gain hands-on experience with advanced robotics concepts.