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OpenVINO™ Training Extensions

OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.

Quick Start Guide

Prerequisites

Setup OpenVINO™ Training Extensions

  1. Clone repository in the working directory by running the following:

    git clone https://github.com/openvinotoolkit/training_extensions.git
    export OTE_DIR=`pwd`/training_extensions
    
  2. Clone Open Model Zoo repository to run demos:

    git clone https://github.com/openvinotoolkit/open_model_zoo --branch develop
    export OMZ_DIR=`pwd`/open_model_zoo
    
  3. Install prerequisites by running the following:

    sudo apt-get install python3-pip virtualenv
    
  4. Create and activate virtual environment:

    cd training_extensions
    virtualenv venv
    source venv/bin/activate
    
  5. Install ote package:

    pip3 install -e ote/
    

Models

After installation, you are ready to train your own models, evaluate and use them for prediction.

Optimization

The image classification and object detection models can be compressed by NNCF framework.

See details in the corresponding readme files of the models.

Misc

Models that were previously developed can be found here.

Contributing

Please read the contribution guidelines before starting work on a pull request.

Known Limitations

Currently, training, exporting, evaluation scripts for TensorFlow*-based models and the most of PyTorch*-based models from Misc section are exploratory and are not validated.


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