NIWeek 2019 Deep Learning Object Detection using OpenVINO Inference Engine Demo

[thuyanhl]

Overview

This example demonstrates the use of Deep Learning APIs to perform Object Detection using both TensorFlow and OpenVINO Optimized Models. The TensorFlow model is converted to OpenVINO model using Model Optimizer. OpenVINO optimizes the TensorFlow model and provides faster inference showed by the OpenVINO Acceleration indicator.

Description

This example uses a pre-trained TensorFlow Object detection SSD_Mobilenet1_Coco model that has been fine tuned using IC defect images. It also shows the optimized model using OpenVINO’s Model Importer. The Optimized Model was optimized using the “convert2ir.py” script that ships with Vision Development Module 2019.

Both models are being loaded and ran using the Model Importer polymorphic API to detect the defects in the IC part presented. This example demonstrates the gain in execution time of the model with National Instrument’s Inference Engine using OpenVINO for the optimization.

For more details, refer to the “OpenVINO Deep Learning in NI Vision” PDF included in the folder.

Hardware and Software Requirements

LabVIEW 2018 64-bit and later

Vision Development Module 2019

Windows 10 64-bit with Intel 6^th generation processor or Linux RT 64-bit target

Steps to Implement or Execute Code

• Extract all three folders and place the OV and TF Model folders at the same level as the "NIWeek Deep Learning IC Demo (1900x1080).vi" from the NIWeek OpenVINO2018 folder.
• Open the Block Diagram of the “NIWeek Deep Learning IC Demo” VI and configure the Vision Acquisition Express VI to use your camera.
• Run the VI.
• Observe the OpenVINO acceleration indicator to see how much performance optimization is gained by using OpenVINO.

Additional Information or References

• Deep Learning Inference Engines Concept Help: https://zone.ni.com/reference/en-XX/help/370281AG-01/nivisionconcepts/deeplearning_techniques/
• Model Optimizer Developer Guide: https://docs.openvinotoolkit.org/latest/_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html
• Deep Learning 2019 Readme (with step by step instructions on how to set up environment to run convert2ir script) installed on disk: C:\Users\Public\Documents\National Instruments\model_optimizer\Readme.html
• Inference Engine Developer Guide: https://docs.openvinotoolkit.org/latest/_docs_IE_DG_Deep_Learning_Inference_Engine_DevGuide.html

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