RTMPose is a machine learning model that detects human pose and returns a location and confidence for each of 133 joints.
This is based on the implementation of RTMPose_Body2d found here. This repository contains scripts for optimized on-device export suitable to run on Qualcomm® devices. More details on model performance accross various devices, can be found here.
Sign up to start using Qualcomm AI Hub and run these models on a hosted Qualcomm® device.
Install the package via pip:
pip install "qai-hub-models[rtmpose-body2d]" torch==2.4.1 -f https://download.openmmlab.com/mmcv/dist/cpu/torch2.4/index.html -f https://qaihub-public-python-wheels.s3.us-west-2.amazonaws.com/index.html
Once installed, run the following simple CLI demo:
python -m qai_hub_models.models.rtmpose_body2d.demo
More details on the CLI tool can be found with the --help
option. See
demo.py for sample usage of the model including pre/post processing
scripts. Please refer to our general instructions on using
models for more usage instructions.
This repository contains export scripts that produce a model optimized for on-device deployment. This can be run as follows:
python -m qai_hub_models.models.rtmpose_body2d.export
Additional options are documented with the --help
option. Note that the above
script requires access to Deployment instructions for Qualcomm® AI Hub.
- The license for the original implementation of RTMPose_Body2d can be found here.
- The license for the compiled assets for on-device deployment can be found here
- Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
- For questions or feedback please reach out to us.