An Android Java Native App to count push up using K-NN Algorithm with dataset and Mediapipe pose to model the human into 3d skeleton of points and lines
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Updated
Feb 13, 2024 - Java
An Android Java Native App to count push up using K-NN Algorithm with dataset and Mediapipe pose to model the human into 3d skeleton of points and lines
Efficient yoga pose estimation is a critical enabler for enhancing precision and performance in wellness and fitness applications. Advancements in computer vision and machine learning are driving remarkable progress in this domain.
ergoSmart is an AI-powered posture coach using React.js, TensorFlow.js, and MediaPipe Pose for real-time webcam-based posture analysis and personalized feedback.
Тестовое задание на Frontend разработчика (React)
Designed and implemented a posture corrector that delivers real-time feedback on user posture, achieving an improvement of 32% in posture alignment. • Leveraged Mediapipe for precise real-time detection of 32 key human body joints. Established precise joint angle threshold to further refine posture correction, tailored to specific exercises.
Deep learning based human face, hand and body joints landmarks predictor. Do have a fun trial :)
Controlling the DJI Tello drone, Based on body pose estimates! (Mechatronic Class Project)
Knee bend exercise detector that counts the successful rep count only if the user bends the knee for more than 8 seconds by using Mediapipe and OpenCV . The condition for the knee to be in a bent stage is that the angle between the hip, knee, and ankle should be smaller than 140 degree.
App for exercise curling biceps that can help you to estimate the calories burned and track your exercise history.
Interview Buster is an AI-powered tool designed to help job seekers enhance their non-verbal communication skills. By leveraging advanced computer vision techniques, it provides personalized feedback on body language, including facial expressions, head posture, eye contact, hand gestures, and body poses, ultimately boosting interview success rates.
Offline Body Movement Analysis in the Browser
A game using web camera, where player need to show the time with his arms.
I worked on this short project for which estimates the angles between the joints and gives a frequency count of the number of times a person works out using that particular pose. Used MediaPipe and OpenCV, this was pretty straightforward
This project integrates MediaPipe Solutions with Node.js and Express for real-time computer vision tasks. It showcases examples of image segmentation, hand and face detection, and pose detection, with a combined example for all three types of landmark detection.
A self contained example demonstrating how to use Mediapipe Pose Landmarker with Max's `jweb`
Mediapipe+MySQL+SportDetect: Sit-ups, pull-ups, standing broad jump
Исходные файлы приложения "Трекинг упражнений", разработанного для курсовой работы по курсу 01.03.04 - "Методы искуственного интеллекта", кафедры КИК, НИТУ МИСиС, 2021-2022 уч. год.
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