A useful application for the COVID19 era to control the human temperature and issue alarms in case of fever.
Use Python, OpenCV libraries and the PYNQ frame to implement the computer vision on Arty Z7-20 Xilinx Zynq SoC platform.
Face Detection is really awesome! This is a tutorial about making a very cheap face detection system.
Ripe fruit identification using an Ultra96 board and OpenCV.
Determine a solar power plant's power output using data from the Cloud Motion Vector (CMV) Sensor System and a model of the power plant.
AI-powered system that utilizes webcam input to recognize and interpret head and face movements, translating these gestures into game action
Getting Started with Infinite-ISP, the open source image signal processor on AMD Kria KV260 AI Starter kit.
Creating a high performance edge processing node using the Ultra96, MIPI and DisplayPort.
I used a potentiometer to control a game's avatar.
Detect faces and read emotions in pictures with Raspberry Pi Camera using Google Cloud Vision.
Experiential advertising platform. Using the Ricoh Theta 360 camera.
Playing Google Chrome Dino game automatically with image processing and simulating key strokes with pynput module
EdgeAI made simple - Exploring Image Processing (Image Classification) on microcontrollers with Arduino Portenta, Edge Impulse, and OpenMV.
In early June Avnet announced the ZUBoard, featuring the ZUB1CG, the smallest device in the AMD-Xilinx Zynq UltraScale+ MPSoC family.
Creating a minimal MIPI imaging system on a Spartan XC7S15 device with no processors.
The following tutorial will introduce you with the concept of face and eye detection using python and OpenCV.
Smart Robot help to protect building residents in high rise apartment's access and common area with SanitizerOnDemand and DeliverySecured.
I built a real-time AI system with XIAO ESP32S3 Sense and ESP32C3 that detects people and renders them as dynamic particle energy fields.
PYNQ is an open-source project that makes it easy to design embedded systems using Python for FPGA.
The robot is designed to operate by itself without manual control, and also pick up and drop an object using the forklifting concept.
The implemented image segment uses K-Mean clustering algorithm for FPGA Devices, and it has been designed with a standard Xilinx AXI4 stream
Machine Learning and image manipulation to compare model performances
Creating a low-cost imager solution using a Xilinx Spartan S7 and Arm Cortex-M1.
A machine vision-based blob analysis method is explained to track an object in real-time using MATLAB and webcam.
