Metadata-Version: 2.1
Name: eiq
Version: 1.0.0
Summary: eIQ package provides classes and scripts to manage the eIQ Samples Apps.
Home-page: https://source.codeaurora.org/external/imxsupport/pyeiq/
Author: Alifer Moraes, Diego Dorta, Marco Franchi
Author-email: diego.dorta@nxp.com
License: BDS-3-Clause
Description: # Welcome to PyeIQ
        
        PyeIQ provide high level classes to allow the user execute eIQ applications and demos.
        
        
        | i.MX Board | BSP Release | Building Status |
        |------------|-------------|-----------------|
        | 8 QM       | 5.4         | ![build](https://img.shields.io/travis/asciidoctor/jekyll-asciidoc/master.svg "Build") |
        | 8 MPlus    | 5.4         | ![build](https://img.shields.io/travis/asciidoctor/jekyll-asciidoc/master.svg "Build") |
        | 8 M Mini   | 5.4         |         -        |
        
        ## Getting Started with PyeIQ
        
        Before installing PyeIQ, ensure all dependencies are installed. Most of them are
        common dependencies found in any _GNU/Linux Distribution_; package names will be
        different, but it shouldn't be difficult to search using whatever package management
        tool that's used by your distribution.
        
        The procedures described in this document target a GNU/Linux Distribution Ubuntu 18.04.
        
        ### Software Requirements
        
        1. Install the following packages in the GNU/Linux system:
        ```console
        ~# apt install python3 python3-pip
        ```
        
        2. Then, use _pip3_ tool to install the [_Virtualenv_](https://virtualenv.pypa.io/en/latest/) tool:
        ```console
        ~$ pip3 install virtualenv
        ```
        
        ### Building the PyeIQ Package
        
        1. Clone the PyeIQ repository from CAF.
        
        2. Use _Virtualenv_ tool to create an isolated Python environment:
        ```console
        ~/pyeiq$ virtualenv env
        ~/pyeiq$ source env/bin/activate
        ```
           * Generate the PyeIQ package:
           ```console
           (env) ~/pyeiq# python3 setup.py sdist bdist_wheel
           ```
          * Copy the package to the board:
          ```console
          (env) ~/pyeiq$ scp dist/eiq-<version>.tar.gz root@<boards_IP>:~
          ```
        
        3. To deactivate the virtual environment:
        ```console
        (env) ~/pyeiq$ deactivate
        ~/pyeiq$
        ```
        
        ### Deploy the PyeIQ Package
        
        1. Install the PyeIQ Wheel file in the board:
        ```console
        root@imx8qmmek:~# pip3 install eiq-<version>.tar.gz
        ```
        
        2. Check the installation:
            * Start an interactive shell mode with Python3:
            ```console
            root@imx8qmmek:~# python3
            ```
        
            * Check the PyeIQ latest version:
            ```console
            >>> import eiq
            >>> eiq.__version__
            ```
        
            * The output is the PyeIQ latest version installed in the system.
        
        ## Running the Demos
        
        All the demos are installed in the `/opt/eiq/demos` folder. Follow a list of the
        available demos in PyeIQ:
        
        |  Demo/App Name                    |  Demo/App Type   | i.MX Board | BSP Release | BSP Framework           | Inference | Status |  Notes                                      |
        |-----------------------------------|------------------|------------|-------------|-------------------------|-----------|--------|---------------------------------------------|
        | Label Image                       | File Based       | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | ![build](https://img.shields.io/travis/asciidoctor/jekyll-asciidoc/master.svg "Build")       | -
        | Label Image Switch                | File Based       | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | ![build](https://img.shields.io/travis/asciidoctor/jekyll-asciidoc/master.svg "Build")       | -
        | Object Detection                  | SSD/Camera Based | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | ![build](https://img.shields.io/travis/asciidoctor/jekyll-asciidoc/master.svg "Build")       | Works with low accuracy. Need better model. |
        | Object Detection OpenCV           | SSD/Camera Based | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | ![build](https://img.shields.io/travis/asciidoctor/jekyll-asciidoc/master.svg "Build")       | Higher accuracy than above one.             |
        | Object Detection Native GStreamer | SSD/Camera Based | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | -       | Fixing undetermined GStreamer hangs.        |
        | Object Detection Yolov3           | SSD/File Based   | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | -       | Pending issues.                             |
        | Object Detection Yolov3           | SSD/Camera Based | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | -       | Pending issues.                             |
        | Fire Detection                    | File Based       | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | ![build](https://img.shields.io/travis/asciidoctor/jekyll-asciidoc/master.svg "Build")       | -                                            |
        | Fire Detection                    | Camera Based     | QM, MPlus  | _5.4_       | TensorFlow Lite _2.1.0_ | GPU, NPU  | ![build](https://img.shields.io/travis/asciidoctor/jekyll-asciidoc/master.svg "Build")       | -                                            |
        | Fire Detection                    | Camera Based     | -           | _5.4_       | PyArmNN _19.08_         | -          | -       | Requires _19.11_                            |
        | Coral Posenet                     |  Camera Based    | -           | -            | -                        | -          | -       | Ongoing                                     |
        | NEO DLR                           | Camera Based     | -           | -            | -                        | -          | -       | Ongoing                                     |
        
        1. To run the demos:
            * Choose the demo and execute it:
            ```bash
            root@imx8qmmek:~# cd /opt/eiq/demos/
            root@imx8qmmek:~/opt/eiq/demos/# python3 <demo>.py
            ```
            * Use help if needed:
            ```bash
            root@imx8qmmek:~/opt/eiq/demos/# python3 <demo>.py --help
           ```
        
        ## Copyright and License
        
        © 2020 NXP Semiconductors.
        
        Free use of this software is granted under the terms of the BSD 3-Clause License.
        
Keywords: SOME,MEANINGFULL,KEYWORDS
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
