eIQ Sample Apps - Overview

Document created by Diego Dorta Employee on Jun 19, 2019Last modified by Vanessa Maegima on Jul 30, 2019
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   The eIQ Sample Apps repository hosts Machine Learning applications demos based on the eIQ ML Software Development Environment. The following examples were tested and used for training purposes. To be understandable each application contains a read-me file allowing the user to get started with the eIQ demos.


   The eIQ samples apps target the latest eIQ release and are split in labs sections. Before starting with the examples, read the introduction part:


  1. Object Recognition using Arm NN

    This section contains samples for running inference and predicting different objects. It also includes an extension that can recognize any given camera input/object.

  2. Handwritten Digit Recognition

    This section focuses on a comparison of inference time between different models for handwritten digits recognition.

  3. Object Recognition using OpenCV DNN

    This section uses OpenCV DNN module for running inference and detecting objects from an image. It also includes an extension that can detect any given camera input/object.

  4. Face Recognition using TensorFlow Lite

    This section uses a model for running inference and recognizing faces:

  5. TF Lite Quantization

    This tutorial demonstrates how to convert a Tensorflow model to TensorFlow Lite using quantization.

  6. TensorFlow Transfer Learning

    This lab will take an existing TensorFlow image classification model and re-train it to categorize images of flowers. 


These labs sections will be updated frequently in order to keep all codes and tutorials up-to-date.

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