Running Google MoveNet Single Pose models on OpenVINO
MoveNet Single Pose tracking on OpenVINO
A convolutional neural network model that runs on RGB images and predicts human joint locations of a single person. Two variant: Lightning and Thunder, the latter being slower but more accurate. MoveNet uses an smart cropping based on detections from the previous frame when the input is a sequence of frames. This allows the model to devote its attention and resources to the main subject, resulting in much better prediction quality without sacrificing the speed.
For Blazepose, a challenger, please visit : openvino_blazepose
Install
You need OpenVINO 2021.3 (does not work with 2021.2) and OpenCV installed on your computer and to clone/download this repository.
Run
Usage:
> python3 MovenetOpenvino.py -h
usage: MovenetOpenvino.py [-h] [-i