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
-
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 -
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 -
Install prerequisites by running the following:
sudo apt-get install python3-pip virtualenv -
Create and activate virtual environment:
cd training_extensions virtualenv venv source venv/bin/activate -
Install
otepackage: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.
* Other names and brands may be claimed as the property of others.
