BlazePose - Super fast human pose detection on Tensorflow 2.x
-
Updated
Oct 29, 2021 - Python
BlazePose - Super fast human pose detection on Tensorflow 2.x
Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements.
Application to visualize blazepose and learn proper forms of muscle training excercises
Blaze Pose and YOLOv8 powered robot for real-time person tracking and fall-risk assessment. An Arduino-controlled mobile platform provides assistance to the tracked individual.
Yoga pose classification model based on pose estimation (BlazePose 3D)
This is a real-time pose estimation project that detects 33 human body landmarks in images, videos, and live webcam streams. Built using MediaPipe, OpenCV, and Streamlit, this project provides an interactive and efficient way to analyze human movements using Blaze Pose detection method.
Add a description, image, and links to the blazepose topic page so that developers can more easily learn about it.
To associate your repository with the blazepose topic, visit your repo's landing page and select "manage topics."