Realtime human head pose estimation with ONNXRuntime and OpenCV.

Perform Human Pose Estimation in OpenCV Using OpenPose MobileNet

Implementation of openpose with tensorflow & openCV for estimation of human poses & classification.

Explore and benchmark human pose estimation systems on the OpenCV AI Kit OAK-1 and OAK-D devices.

OpenCV inference implementation of Paper "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose "(https://arxiv.org/abs/1811.12004)

This project is about counting curls and making sure elbows are tucked in using YOLOv7 for pose estimation. I'm using OpenCV and YOLOv7 to detect the human body parts and then estimate the angle between each three points using the dot product.

Dockerfile and instructions for human pose estimation implementation using Caffe, OpenCV 3.1.0 and Python 2.7.

AI Fitness Coach with BlazePose: Real-Time Exercise Feedback This project implements an AI-powered fitness coaching system using MediaPipe's BlazePose and OpenCV for real-time human pose estimation. Designed to address the lack of automated exercise guidance

Real time Human Pose estimation using Tensorflow and OpenCV

Human Pose Estimation using Pre-Trained Model

A real-time multi-person human pose estimation system using TensorFlow MoveNet Multipose (Lightning). Built with OpenCV for video and webcam inference, it detects and visualizes keypoints and skeletal connections with confidence-based filtering, optimized for speed and multi-person scenarios.

Deep Learning based Human Pose Estimation using OpenCV ( Python )

This GitHub repository contains code for Human Pose Estimation using OpenCV's deep learning module. It uses machine learning algorithms to recognize and estimate the position of specific points in the human body in an image or live video feed.

Human Pose Estimation Project usign OpenCV

Code for running OpenPose code for human pose estimation using deep learning in OpenCV

Implementation for Human Pose Estimation using OpenCV and Python

The core of the system involves implementing pose estimation algorithms using OpenCV, which can accurately locate and track the positions of major joints in the human body. This involves utilizing pre-trained deep learning models, such as PoseNet or OpenPose, to efficiently identify keypoints.

This repository contains OpenCV-based applications for hand tracking, finger counting, and pose estimation. Python scripts use OpenCV's vision techniques to detect, track, and count fingers, as well as estimate body poses. The project focuses on applications like gesture recognition and human-computer interaction.

Project which involves the usage of pose estimations to predict the type of human activity. In this project the packages which are used are chainer, keras, opencv and python

Real time head pose estimation using MediaPipe and OpenCV, enabling dynamic tracking of a person's head orientation from video input for applications like augmented reality and human-computer interaction.

An interactive web application for real-time human pose estimation using a TensorFlow model, built with Streamlit and OpenCV. Features include image, video, and live camera pose detection, a user-friendly navigation menu, and a sidebar for enhanced usability.

This project combines MediaPipe and OpenCV for real-time pose estimation and facial expression recognition, enabling applications in fitness tracking, human-computer interaction, and emotion-aware interfaces, showcasing the potential for diverse interactive technologies.

AI-powered sports activity detection system using computer vision. Analyzes human movements and identifies sports activities through pose estimation. Built with Python, OpenCV, and machine learning. Real-time activity recognition for fitness and sports training applications.

A real-time human fall detection system using the YOLOv8 Pose Estimation model and OpenCV. This project uses body keypoints to detect whether a person has fallen, based on geometric heuristics from shoulder, hip, and ankle positions.

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Human Pose Estimation using OpenCV and TensorFlow, with a Streamlit interface. Upload images, adjust keypoint detection thresholds, and visualize human body parts with skeletons. The app processes pose estimation and allows users to download the output image. Ideal for learning OpenCV and deep learning integration.

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Human Pose Estimation in OpenCV

Detect human poses in real-time using OpenPose and write the detected video or image using OpenCV.

the aim of project is to identifying and locating key points of the human body on webcam.This involves detecting joints and limbs and estimating their spatial relationships. It's used in various applications like action recognition, healthcare, sports analytics, security, AR/VR, and human-computer interaction.