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A Python Framework for eIQ on i.MX Processors

Project description

A Python Demo Framework for eIQ on i.MX Processors

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PyeIQ is written on top of eIQ™ ML Software Development Environment and provides a set of Python classes allowing the user to run Machine Learning applications in a simplified and efficiently way without spending time on cross-compilations, deployments or reading extensive guides.

  • Take as a disclaimer that PyeIQ should not be considered production-ready.

Official Releases

BSP Release PyeIQ Release PyeIQ Updates Board Date Status Notes
BSP tag imx Apr, 2020 Build PoC
tag imx May, 2020 Build
BSP tag imx Jun, 2020 Build Stable
tag imx Jun, 2020 Build
tag imx Aug, 2020 Build
BSP tag imx Nov, 2020 Build
BSP
BSP
tag imx Jul, 2021 Build Stable
tag imx Sep, 2021 Build
tag imx Dec, 2021 Build
tag imx Dec, 2021 Build

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PyeIQ v1 and v2 can be installed with "pip3 install eiq". For more details, please check pypi-eiq.

Major Changes

3.0.0

  • Remove all non-quantization models.
  • Change switch video demo (working on 8MPlus).
  • Add Covid19 detection demo

2.0.0

  • General major changes on project structure.
  • Split project into engine, modules, helpers, utils and apps.
  • Add base class to use on all demos avoiding repeated code.
  • Support for more demos and applications including Arm NN.
  • Support for building using Docker.
  • Support for download data from multiple servers.
  • Support for searching devices and build pipelines.
  • Support for appsink/appsrc for QM (not working on MPlus).
  • Support for camera and H.264 video.
  • Support for Full HD, HD and VGA resolutions.
  • Support video and image for all demos.
  • Add display info in the frame, such as: FPS, model and inference time.
  • Add manager tool to launch demos and applications.
  • Add document page for PyeIQ project.

1.0.0

  • Support demos based on TensorFlow Lite (2.1.0) and image classification.
  • Support inference running on GPU/NPU and CPU.
  • Support file and camera as input data.
  • Support SSD (Single Shot Detection).
  • Support downloads on the fly (models, labels, dataset, etc).
  • Support old eIQ demos from eiq_sample_apps CAF repository.
  • Support model training for host PC.
  • Support UI for switching inference between GPU/NPU/CPU on TensorFlow Lite.

Copyright and License

Copyright 2021 NXP. Free use of this software is granted under the terms of the BSD 3-Clause License. See LICENSE for details.

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