Metadata-Version: 2.1
Name: eiq
Version: 2.2.0
Summary: A Python Framework for eIQ on i.MX Processors
Home-page: https://source.codeaurora.org/external/imxsupport/pyeiq/
Author: Alifer Moraes, Diego Dorta, Marco Franchi
License: BDS-3-Clause
Description: <p align="center">
          <img src="https://raw.githubusercontent.com/diegohdorta/models/master/media/pyeiq.png" height="191" width="176">
        </p>
        
        ##  **A Python Demo Framework for eIQ on i.MX Processors**
        
        ![pip3][eiqpackage]
        [![PyPI version](https://badge.fury.io/py/eiq.svg)](https://badge.fury.io/py/eiq)
        ![GitHub issues][license]
        [![Downloads](https://pepy.tech/badge/eiq)](pepy_total)
        [![Downloads](https://pepy.tech/badge/eiq/month)](pepy_month)
        [![Downloads](https://pepy.tech/badge/eiq/week)](pepy_week)
        ![Total Lines][total_lines]
        ![Repo Size][repo_size]
        ![Closed Issues][closed_issues]
        ![Open Issues][open_issues]
        [![Gitter][gitter-image]][gitter-url]
        
        PyeIQ is written on top of [eIQ™ ML Software Development Environment][eiq] 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**.
        * Go to the documentation page for further details [pyeiq.dev][page].
        
        ### Official Releases
        
        | BSP Release                  | PyeIQ Release       | PyeIQ Updates    | Board          | Date      | Status             | Notes   |
        |------------------------------|---------------------|------------------|----------------|-----------|--------------------|---------|
        | ![BSP][release_5.4.3_2.0.0]  | ![tag][tag_v100]    |                  | ![imx][boards] | Apr, 2020 | ![Build][passing]  | PoC     |
        |                              |                     | ![tag][tag_v101] | ![imx][boards] | May, 2020 | ![Build][passing]  |         |
        | ![BSP][release_5.4.24_2.1.0] | ![tag][tag_v200]    |                  | ![imx][boards] | Jun, 2020 | ![Build][passing]  | Stable  |
        |                              |                     | ![tag][tag_v201] | ![imx][boards] | Jun, 2020 | ![Build][passing]  |         |
        |                              |                     | ![tag][tag_v210] | ![imx][boards] | Aug, 2020 | ![Build][passing]  |         |
        | ![BSP][release_5.4.47_2.2.0] |                     | ![tag][tag_v220] | ![imx][boards] | Nov, 2020 | ![Build][passing]  |         |
        
        ![blue][tag_blue]
        ![yellow][tag_yellow]
        ![red][tag_red]
        
        ### Major Changes
        
        **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 2020 NXP Semiconductors. Free use of this software is granted under
        the terms of the BSD 3-Clause License.
        See [LICENSE](https://github.com/diegohdorta/pyeiq/blob/master/LICENSE.md)
        for details.
        
        [release_5.4.3_2.0.0]: https://img.shields.io/badge/-5.4.3__2.0.0-blueviolet
        [release_5.4.24_2.1.0]: https://img.shields.io/badge/-5.4.24__2.1.0-blueviolet
        [release_5.4.47_2.2.0]: https://img.shields.io/badge/-5.4.47__2.2.0-blueviolet
        
        [tag_blue]: https://img.shields.io/badge/-new-blue
        [tag_yellow]: https://img.shields.io/badge/-features-yellow
        [tag_red]: https://img.shields.io/badge/-bug%20fixes-red
        
        [tag_v100]: https://img.shields.io/badge/-v1.0.0-blue
        [tag_v101]: https://img.shields.io/badge/-v1.0.1-red
        [tag_v110]: https://img.shields.io/badge/-v1.1.0-red
        
        [tag_v200]: https://img.shields.io/badge/-v2.0.0-blue
        [tag_v201]: https://img.shields.io/badge/-v2.0.1-red
        [tag_v210]: https://img.shields.io/badge/-v2.1.0-yellow
        [tag_v220]: https://img.shields.io/badge/-v2.2.0-red
        
        [boards]: https://img.shields.io/badge/-8QM%2C%208MPlus-lightgrey
        [passing]: https://img.shields.io/badge/Build-passing-success
        
        [page]: https://pyeiq.dev/
        [eiq]: https://www.nxp.com/design/software/development-software/eiq-ml-development-environment:EIQ
        [eiqpackage]: https://img.shields.io/badge/pip3%20install-eiq-green
        [pypirepo]: https://pypi.org/project/eiq/#description
        [pypicaf]: https://source.codeaurora.org/external/imxsupport/pyeiq/
        [license]: https://img.shields.io/badge/License-BSD%203--Clause-blue
        [pepy_total]: https://pepy.tech/project/eiq
        [pepy_month]: https://pepy.tech/project/eiq/month
        [pepy_week]: https://pepy.tech/project/eiq/week
        [gitter-url]: https://gitter.im/pyeiq-imx/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge
        [gitter-image]: https://badges.gitter.im/pyeiq-imx/community.svg
        
        
        [total_lines]: https://img.shields.io/tokei/lines/github/diegohdorta/pyeiq
        [repo_size]: https://img.shields.io/github/repo-size/diegohdorta/pyeiq
        [closed_issues]: https://img.shields.io/github/issues-closed-raw/diegohdorta/pyeiq
        [open_issues]: https://img.shields.io/github/issues-raw/diegohdorta/pyeiq
        
Keywords: ml,eiq,demos,apps
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Information Technology
Classifier: Natural Language :: English
Classifier: Operating System :: Other OS
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
