OpenCV 3 + Python 3 + 940nm High Luminous Intensity Retroreflectors = Magic!

An implementation for the generation, detection, and pose estimation of aruco markers using Python 3.

A django based facial recognition system

Download, Compile, Build, and Install OpenCV 3.2.0 with Extra Modules on RPI running Raspberry Pi OS

OpenCV is a cross-platform library using which we can develop real-time computer vision applications. It mainly focuses on image processing, video capture and analysis including features like face detection and object detection. In this tutorial, we explain how you can use OpenCV in your applications.OpenCV-Python is a library of Python bindings…

Face Recognition System Uses for multi Face Detection. It is a Real time Detection System that can be Easily Port on any Hardware Devices due to its written in python. The Model First Train the Faces and after that Predict the output with more than 85%+ confidence due to its model classifier training with good algorithms so that predict with mor…

With this project you can measure height and width of an object with a normal & simple camera. I find out that I can use another object as a main measure and then use it to measure other objects in the camera.

A computer program that will allow you to read and resize images and videos.

my bachelor's degree thesis project about controlling a DJI Tello drone

MediaPipe Python Wheel installer for RaspberryPi OS aarch64, Ubuntu aarch64, Debian aarch64 and Jetson Nano.

Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-contrib-python-headless packages.

AutoSelfie is an advanced , Python-based project designed to automate the process of taking perfect selfies using the power of OpenCV and its contrib modules.This innovative solution streamlines the selfie-taking experience by utilizing computer vision techniques to ensure that every shot is flawlessly captured without any manual intervention.

AutoSelfie is an advanced , Python-based project designed to automate the process of taking perfect selfies using the power of OpenCV and its contrib modules.This innovative solution streamlines the selfie-taking experience by utilizing computer vision techniques to ensure that every shot is flawlessly captured without any manual intervention.

Using the Tkinter GUI and OpenCV to filter and get the upper and lower HSV ranges from camera video capture