Legacy Features and Components¶
Since OpenVINO has grown very rapidly in recent years, some of its features and components have been replaced by other solutions. Some of them are still supported to assure OpenVINO users are given enough time to adjust their projects, before the features are fully discontinued.
This section will give you an overview of these major changes and tell you how you can proceed to get the best experience and results with the current OpenVINO offering.
OpenVINO Development Tools Package
New solution: OpenVINO Runtime includes all supported components
Old solution: discontinuation planned for OpenVINO 2025.0
OpenVINO Development Tools used to be the OpenVINO package with tools for
advanced operations on models, such as Model conversion API, Benchmark Tool,
Accuracy Checker, Annotation Converter, Post-Training Optimization Tool,
and Open Model Zoo tools. Most of these tools have been either removed,
replaced by other solutions, or moved to the OpenVINO Runtime package.
Model Optimizer / Conversion API
New solution: Direct model support and OpenVINO Converter (OVC)
Old solution: Legacy Conversion API discontinuation planned for OpenVINO 2025.0
The role of Model Optimizer and later the Conversion API was largely reduced
when all major model frameworks became supported directly. For converting model
files explicitly, it has been replaced with a more light-weight and efficient
solution, the OpenVINO Converter (launched with OpenVINO 2023.1).
OpenVINO Deployment Manager
New solution: the tool is no longer needed
Old solution: discontinuation planned for OpenVINO 2024.0
It is recommended to explore alternative deployment solutions available in OpenVINO.
Open Model ZOO
New solution: users are encouraged to use public model repositories
Old solution: discontinuation planned for OpenVINO 2025.0
Open Model ZOO provided a collection of models prepared for use with OpenVINO,
and a small set of tools enabling a level of automation for the process.
Since the tools have been mostly replaced by other solutions and several
other model repositories have recently grown in size and popularity,
Open Model ZOO will no longer be maintained. You may still use its resources
until they are fully removed.
Apache MXNet, Caffe, and Kaldi model formats
New solution: conversion to ONNX via external tools
Old solution: model support will be discontinued with OpenVINO 2024.0
Since these three model formats proved to be far less popular among OpenVINO users
than the remaining ones, their support has been discontinued. Converting them to the
ONNX format is a possible way of retaining them in the OpenVINO-based pipeline.
Post-training Optimization Tool (POT)
New solution: NNCF extended in OpenVINO 2023.0
Old solution: POT discontinuation planned for 2024.0
Neural Network Compression Framework (NNCF) now offers the same functionality as POT,
apart from its original feature set. It is currently the default tool for performing
both, post-training and quantization optimizations, while POT is considered deprecated.
Old Inference API 1.0
New solution: API 2.0 launched in OpenVINO 2022.1
Old solution: discontinuation planned for OpenVINO 2024.0
API 1.0 (Inference Engine and nGraph) is now deprecated. It can still be
used but is not recommended. Its discontinuation is planned for 2024.
Compile tool
New solution: the tool is no longer needed
Old solution: deprecated in OpenVINO 2023.0
Compile tool is now deprecated. If you need to compile a model for inference on
a specific device, use the following script:
import openvino as ov core = ov.Core() compiled_model = core.compile_model(model_path, device, properties) output_stream = compiled_model.export_model()ov::Core core; ov::CompiledModel model = core.compile_model("modelPath", "deviceName"); std::fstream stream("compiled_model.blob"); model.export_model(stream);
DL Workbench
New solution: DevCloud version
Old solution: local distribution discontinued in OpenVINO 2022.3
The stand-alone version of DL Workbench, a GUI tool for previewing and benchmarking
deep learning models, has been discontinued. You can use its cloud version:
OpenVINO™ integration with TensorFlow (OVTF)
New solution: Direct model support and OpenVINO Converter (OVC)
Old solution: discontinued in OpenVINO 2023.0
OpenVINO™ Integration with TensorFlow is longer supported, as OpenVINO now features a
native TensorFlow support, significantly enhancing user experience with no need for
explicit model conversion.