There are 3 repositories under pose-detection topic.
Custom nodes that extend the capabilities of Comfyui
[ECCV 2022] Official implementation of the paper "SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos"
Quickly add MediaPipe Pose Estimation and Detection to your iOS app. Enable powerful features in your app powered by the body or hand.
AI-based pose tracking and repetitions counter to help everyone do the workout.
Official code for "Action Transformer: A Self-attention Model for Short-time Pose-based Human Action Recognition", Pattern Recognition (2022).
Use Deepstream python API to extract the model output tensor and customize the post-processing of YOLO-Pose
This repository contains a collection of Android applications developed using Google ML Kit, demonstrating the power and versatility of machine learning features in mobile development. Each project is crafted using Java and Kotlin, showcasing various use cases and practical implementations.
Pose Detection and Machine Learning for real-time body posture analysis during exercise to provide audiovisual feedback on improvement of form.
The purpose of this project is to detect the squat angles which will be helpful for the fitness instructors to provide corrective advice where appropriate.
A flutter plugin that uses MLKit on iOS/Android platforms to enable body pose and mask detection using Pose Detection and Selfie Segmentation APIs for both static images and live camera stream.
A MediaPipe Solver library, converting Moetion (inspired by Kalidokit) for use in Unity
MyPT : 인공지능 트레이너 | 2021 군장병 공개 SW 해커톤 (🏆공군참모총장상)
The official implementation of paper: "Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning"
Use Tensorflow Lite + OpenCV to do object detection, classification, and Pose detection.
An AI-powered fitness tracker that uses real-time pose estimation to count reps, monitor form, and provide instant feedback for exercises like squats, push-ups, and bicep curls. Designed for accuracy, motivation, and adaptability
Add motion-based magic to your React Native apps! ThinkSys Mediapipe Plugin offers real-time pose detection for iOS, with easy integration, customizable options, and endless possibilities for fitness, healthcare, and more.
A native android application for pose estimation and detection using mlkit. The app can detect poses and recognize the pose made by the user.
Interfaces web application
AI Android application crafted with Kotlin that harnesses the power of MediaPipe Pose Landmark Detection to deliver real-time feedback on exercise form while accurately counting repetitions
Обнаружение точек лица, рук и всего тела с использованием DL алгоритмов
Quickly add MediaPipe Pose Estimation and Detection to your React Native app. Enable powerful features in your app powered by the body or hand.
BlazePose: Body Segmentation for TFJS and NodeJS
A gesture recognition system powered by OpenPose, k-nearest neighbours, and local outlier factor.
A simple React application to detect persons and their pose landmarks
This repository contains code for collecting pose data of various yoga poses using the MediaPipe Pose model. The collected data includes the angles of different body joints in each yoga pose.
A Flutter app that utilises TensorFlow's MoveNet model for pose detection, in order to count a user's reps and detect the correctness of their pose, with additional modules for BMI calculation and nutrition.
Classify human poses with help of yolo pose model.
Combining the Google ML Kit with live camera and also video recording using CameraX API
Multiple-person pose detection in Unity Engine.
This repository contains an implementation of a deep learning approach for yoga pose classification using Convolutional Neural Networks (CNN) and MediaPipe for body keypoint detection. The project aims to classify various yoga poses with high accuracy and low latency, making it suitable for real-world applications.
Face tracking based on DeepSort algorithm for Windows
Realtime pose landmark detection with BlazePoseBarracuda in Unity
Monitor Your Workout through a Webcam/IP Camera. No equipment is required, other than a camera and a laptop. This application could potentially replace a personal trainer, making it the idea app for workout.