PyeIQ v1.0 for BSP 5.4.3_2.0.0 Release

[#1]

Welcome to PyeIQ

PyeIQ gathers everything needed by itself. It provides a simplified way to run ML applications, which avoids the user spending time on preparing the environment.

PyeIQ Version	Release Date	Notes
tag_v1.0	Apr 29, 2020	-
tag_v2.0	-	Planned for June

i.MX Board	BSP Release	Building Status
8 QM	5.4.3_2.0.0	passing
8 MPlus	5.4.3_2.0.0	passing

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Getting Started with PyeIQ

1. Easy Installation

• If you prefer to build the package by yourself go to Appendix Section or follow the README file at the PyeIQ repo.
  

1.1 Copy the PyeIQ pre-built package attached to the board, and then install it by using pip3 tool:

1.2 Check the installation by starting an interactive shell:

1.3 Import PyeIQ and see the version:

The output is the PyeIQ latest version installed in the system.

• (Optional) Install the following package to show downloading status:

2. Easy Running

All demos and applications are automatically installed in /opt/eiq.

2.1 To run the demos:

2.2 To run the applications:

2.3 Use help if needed:

3. List of Available Demos and Applications

Demo/App Name	Demo/App Type	i.MX Board	BSP Release	BSP Framework	Inference	Status	Notes
Label Image	File Based	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	passing	-
Label Image Switch	File Based	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	passing	-
Object Detection	SSD/Camera	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	passing	Need better model.
Object Detection OpenCV	SSD/Camera	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	passing	Need better model.
Object Detection N. GS.	SSD/Camera	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	-	Pending issues.
Object Detection Yolov3	SSD/File	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	-	Pending issues.
Object Detection Yolov3	SSD/Camera	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	-	Pending issues.
Fire Detection	File Based	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	passing	-
Fire Detection	Camera	QM, MPlus	5.4.3_2.0.0	TensorFlow Lite 2.1.0	GPU, NPU	passing	-
Fire Detection	Camera	-	5.4.3_2.0.0	PyArmNN 19.08	-	-	Requires 19.11
Coral Posenet	Camera	-	-	-	-	-	Ongoing
NEO DLR	Camera	-	-	-	-	-	Ongoing

4. Examples

4.1 Fire Detection Image

4.1.1 Non-fire

Running Fire Detect Image:

    Output:

INFO: Created TensorFlow Lite delegate for NNAPI.                                                                       
Applied NNAPI delegate.                                                                                                 
Inference time: 0:00:00.264853                                                                                          
Non-Fire  

4.1.2 Fire

Running Fire Detect Image:

Output:

INFO: Created TensorFlow Lite delegate for NNAPI.                                                                       
Applied NNAPI delegate.                                                                                                 
Inference time: 0:00:00.193055                                                                                          
Fire   

4.2 Fire Detection Camera

Running Fire Detect Camera:

Output:

PyeIQ also supports training for Fire Detection demo, please refer to PyeIQ - Training and Conversion Support (Keras/TensorFlow Lite) .

4.3 Label Image Switch

Running Switch Label Image:

Output:

Cores Comparison (CPU, GPU and NPU)

• Check the following graphical plot for Switch Label Image demo:

• Check the following graphical plot for the other demos:

We are currently working to reduce the inference time on Fire Detection demos.

Appendix Section

The procedures described in this document target a GNU/Linux Distribution Ubuntu 18.04.

1. Software Requirements

1.1 Install the following packages in the GNU/Linux system:

1.2 Then, use pip3 tool to install the virtualenv tool:

2. Building the PyeIQ Package

2.1 Clone the repository:

2.2 Use virtualenv tool to create an isolated Python environment:

2.3 Generate the PyeIQ package:

2.4 Copy the package to the board:

2.5 To deactivate the virtual environment:

Contact

Feel free to contact us about any issue/bug you might have it. Your feedback is very welcome so we can improve the next version

• Alifer Moraes
• diegodorta
• marcofranchi

[Harrison_Choi]

Hello 

I cannot see the detailed command and description 

for example, when I see your explanation in box, most things are empty

Please check it again