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

• Ubuntu 18.04 / 20.04
• Python 3.6+
• OpenVINO™ - for exporting and running models
• CUDA Toolkit 10.2 - for training on GPU

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.

• Action Recognition
  • Custom Action Recognition
  • Gesture Recognition
• Instance Segmentation
  • COCO instance segmentation
  • Custom instance segmentation
• Image classification
  • Custom image classification
• Object Detection
  • Custom Object Detection
  • Face Detection
  • Horizontal Text Detection
  • Person Detection
  • Person Vehicle Bike Detection
  • Vehicle Detection
• Text Spotting
  • Alphanumeric Text Spotting

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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* Other names and brands may be claimed as the property of others.