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Qualcomm® AI Hub Models

Ultralytics YOLOv11 is a machine learning model that predicts bounding boxes, segmentation masks and classes of objects in an image.

This is based on the implementation of YOLOv11-Segmentation 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.

Example & Usage

Install the package via pip:

pip install "qai_hub_models[yolov11_seg]"

Once installed, run the following simple CLI demo:

python -m qai_hub_models.models.yolov11_seg.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.

Export for on-device deployment

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.yolov11_seg.export

Additional options are documented with the --help option. Note that the above script requires access to Deployment instructions for Qualcomm® AI Hub.

License

  • The license for the original implementation of YOLOv11-Segmentation can be found here.
  • The license for the compiled assets for on-device deployment can be found here

References

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