2022.1.0.dev20220215

OpenVINO™ toolkit pre-release definition:

• It is introduced to get early feedback from the community.
• The scope and functionality of the pre-release version is subject to change in the future.
• Using the pre-release in production is strongly discouraged.

You can find OpenVINO™ toolkit 2022.1.0.dev20220215 pre-release version here:

• Download archives* with OpenVINO™ Runtime for C/C++
• OpenVINO™ Runtime for Python: pip install --pre openvino or pip install openvino==2022.1.0.dev20220215
• OpenVINO™ Development tools: pip install --pre openvino-dev or pip install openvino-dev==2022.1.0.dev20220215

* - sha256 sums for archives

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169efcdc21317177e5d8d747c4cbbd50f92ef7fce93999d7207b8e48918d2b81  openvino_opencv_ubuntu18.tgz

NOTE: This version is pre-release software and has not undergone full release validation or qualification. No support is offered on pre-release software and APIs/behavior are subject to change. It should NOT be incorporated into any production software/solution and instead should be used only for early testing and integration while awaiting a final release version of this software.

2022.1.0.dev20220131

OpenVINO™ toolkit pre-release definition:

• It is introduced to get early feedback from the community.
• The scope and functionality of the pre-release version is subject to change in the future.
• Using the pre-release in production is strongly discouraged.

You can find OpenVINO™ toolkit 2022.1.0.dev20220131 pre-release version here:

• Download archives* with OpenVINO™ Runtime for C/C++
• OpenVINO™ Runtime for Python: pip install --pre openvino or pip install openvino==2022.1.0.dev20220131
• OpenVINO™ Development tools: pip install --pre openvino-dev or pip install openvino-dev==2022.1.0.dev20220131

* - sha256 sums for archives

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fe2cd7aba2046c8eed25150cdc10cffce807f0e4231f7774f97e8488a57c2300  opencv_osx.tgz
3b0eaab3209a1e91085b71d5ce12a51747c07f63ec2a6cf471bb9f8e016eab99  opencv_ubuntu18_rhel8.tgz
1d73d11d7d651c8959c012800fa9ae4a6f9f2b550622030fe41b05892a2327cc  opencv_ubuntu20.tgz
7d04b788d139f1ab198d80e10aac974089bf2a2c734e7cf2c3c70036bded2058  opencv_windows.tgz

NOTE: This version is pre-release software and has not undergone full release validation or qualification. No support is offered on pre-release software and APIs/behavior are subject to change. It should NOT be incorporated into any production software/solution and instead should be used only for early testing and integration while awaiting a final release version of this software.

2021.4.2 LTS

This 2021.4.2 LTS release provides functional bug fixes, and minor capability changes for the previous 2021.4.1 Long-Term Support (LTS) release, enabling developers to deploy applications powered by Intel® Distribution of OpenVINO™ toolkit with confidence. To learn more about long-term support and maintenance, go to the Long Term Support Policy.

You can find OpenVINO™ toolkit 2021.4.2 release here:

• Download archives* with OpenVINO™ Runtime
• OpenVINO™ Runtime for Python: pip install openvino==2021.4.2
• OpenVINO™ Development tools: pip install openvino-dev==2021.4.2

Release Notes: https://software.intel.com/content/www/us/en/develop/articles/openvino-2021-4-lts-relnotes.html

2021.4.1 LTS

This 2021.4.1 LTS release provides functional bug fixes, and minor capability changes for the previous 2021.4 Long-Term Support (LTS) release, enabling developers to deploy applications powered by Intel® Distribution of OpenVINO™ toolkit with confidence. To learn more about long-term support and maintenance, go to the Long Term Support Policy.

You can find OpenVINO™ toolkit 2021.4.1 release here:

• Download archives* with OpenVINO™ Runtime
• OpenVINO™ Runtime for Python: pip install openvino==2021.4.1
• OpenVINO™ Development tools: pip install openvino-dev==2021.4.1

Release Notes: https://software.intel.com/content/www/us/en/develop/articles/openvino-2021-4-lts-relnotes.html

2021.4 LTS

What's New

• This new 2021.4 Long-Term Support (LTS) Release provides bug fixes, longer-term maintenance and support with a focus on stability and compatibility enabling developers to deploy applications powered by Intel® Distribution of OpenVINO™ toolkit with confidence. A new LTS version is released every year and supported for two years. For those developers that prefer the very latest features and leading performance, standard releases will continue to be made available 3-4 times a year. Read more about the long-term support and maintenance, go to the Long Term Support Policy.
• New Jupyter Notebooks, demos and support for additional public models to make development easier:
  • Ready-to-run Jupyter Notebooks with tutorials for converting TensorFlow and PyTorch models, image classification, segmentation, depth estimation, post-training quantization and more.
  • Audio Noise Suppression & Time Series Forecasting demos
  • Public Models: RCAN and IseeBetter (image super-resolution), Attention OCR (image text prediction), Tacotron 2 (text-to-speech) and ModNet (portrait/image matting)
• Time-to-first-inference latency performance enhancements: Initialization has been optimized on CPU and integrated GPU (iGPU), significantly improving performance at inferencing startup. Setting up inferencing always involves additional initialization time as the network is loaded and configured on the device, especially on GPUs due to their architecture. This setup time has been reduced significantly for many networks by doing more initialization work in parallel among other optimizations.
• Preview of OpenVINO ™ integration with TensorFlow: Although not a part of the 2021.4 LTS release, a new open source component called the OpenVINO™ integration with TensorFlow is available as a public preview. This component is designed for TensorFlow developers newly exploring OpenVINO™ toolkit to try it with minimal code changes, maximizing TensorFlow API compatibility. For highest performance, lowest memory footprint and complete hardware control, adopting native OpenVINO APIs continues to be the recommended approach.

You can find OpenVINO™ toolkit 2021.4 release here:

• Download archives* with OpenVINO™ Runtime
• OpenVINO™ Runtime for Python: pip install openvino==2021.4.0
• OpenVINO™ Development tools: pip install openvino-dev==2021.4.0

Release Notes: https://software.intel.com/content/www/us/en/develop/articles/openvino-2021-4-lts-relnotes.html

2020.3.2 LTS

This release provides bug fixes for the previous 2020.3 Long-Term Support (LTS) release, a new release type that provides longer-term maintenance and support with a focus on stability and compatibility. Read more about the support details: Long Term Support Release

You can find OpenVINO™ toolkit 2020.3.2 release here:

• Download archives* with OpenVINO™ Runtime

Release notes: https://software.intel.com/content/www/us/en/develop/articles/openvino-2020-3-lts-relnotes.html

2021.3

What's New

• Upgrade to the latest version for new capabilities and performance improvements.
• Introduces a preview of Conditional Compilation (available in open-source distribution) which enables a significant reduction to the binary footprint of the runtime components (Inference Engine linked into applications) for particular models.
• Introducing support for the 3rd Gen Intel® Xeon® Scalable platform (code-named Ice Lake), which delivers advanced performance, security, efficiency, and built-in AI acceleration to handle unique workloads and more powerful AI.
• New pre-trained models and support for public models to streamline development:
  • Pre-trained Models: machine-translation, person-vehicle-bike-detection, text-recognition and text-to-speech.
  • Public Models: aclnet-int8 (sound_classification), deblurgan-v2 (image_processing), fastseg-small and fastseg-large (semantic segmentation) and more.
• Developer tools now available as Python wheel packages for Windows*, Linux*, and macOS* for easy package installation and upgrades (pip install openvino-dev)

You can find OpenVINO™ toolkit 2021.3 release here:

• Download archives* with OpenVINO™ Runtime for C/C++
• OpenVINO™ Runtime for Python: pip install openvino==2021.3.0
• OpenVINO™ Development tools: pip install openvino-dev==2021.3.0

Release Notes: https://software.intel.com/content/www/us/en/develop/articles/openvino-relnotes.html

2021.2

What's New

• Integrates the Deep Learning Workbench with the Intel® DevCloud for the Edge as a Beta release. Graphically analyze models using the Deep Learning Workbench on the Intel® DevCloud for the Edge (instead of a local machine only) to compare, visualize and fine-tune a solution against multiple remote hardware configurations.
• Introduces support for Red Hat Enterprise Linux (RHEL) 8.2.
• Introduces per-channel quantization support in the Model Optimizer for models quantized with TensorFlow Quantization-Aware Training containing per-channel quantization for weights, which improves performance by model compression and latency reduction.
• Pre-trained models and support for public models to streamline development:
  • Public Models: Yolov4 (for object detection), AISpeech (for speech recognition), and DeepLabv3 (for semantic segmentation)
  • Pre-trained Models: Human Pose Estimation (update), Formula Recognition Polynomial Handwritten (new), Machine Translation (update), Common Sign Language Recognition (New), and Text-to-Speech (new)
• New OpenVINO™ Security Add-on, which controls access to model(s) through secure packaging and execution. Based on KVM Virtual machines and Docker* containers and compatible with the OpenVINO™ Model Server, this new add-on enables packaging for flexible deployment and controlled model access.
• PyPI project moved from openvino-python to openvino, and 2021.1 version to be removed in the default view. The specific version is still available for users depending on this exact version by using openvino-python==2021.1

You can find OpenVINO™ toolkit 2021.2 release here:

• Download archives* with OpenVINO™ Runtime for C/C++
• OpenVINO™ Runtime for Python: pip install openvino==2021.2

Release Notes: https://software.intel.com/content/www/us/en/develop/articles/openvino-relnotes.html

2020.3.1 LTS

What's New

• This release provides bug fixes for the previous 2020.3 Long-Term Support (LTS) release, a new release type that provides longer-term maintenance and support with a focus on stability and compatibility. Read more about the support details: Long Term Support Release
• Based on v.2020.3 LTS, the v.2020.3.1 LTS release includes security and functionality bug fixes, and minor capability changes.
• Includes improved support for 11th Generation Intel® Core™ Processor (formerly codenamed Tiger Lake), which includes Intel® Iris® Xe Graphics and Intel® DL Boost instructions.
• Intel® Distribution of OpenVINO™ toolkit 2020.3.X LTS releases will continue to support Intel® Vision Accelerator Design with an Intel® Arria® 10 FPGA and the Intel® Programmable Acceleration Card with Intel® Arria® 10 GX FPGA. For questions about next-generation programmable deep-learning solutions based on FPGAs, talk to your sales representative or contact us to get the latest FPGA updates.

You can find OpenVINO™ toolkit 2020.3.1 release here:

• Download archives* with OpenVINO™ Runtime

Release notes: https://software.intel.com/content/www/us/en/develop/articles/openvino-2020-3-lts-relnotes.html

2021.1

What's New

• Introducing a major release in October 2020 (v.2021). You are highly encouraged to upgrade to this version because there it introduces new and important capabilities, as well as breaking changes and backward-incompatible changes.
• Support for TensorFlow 2.2.x. Introduces official support for models trained in the TensorFlow 2.2.x framework.
• Support for the Latest Hardware. Introduces official support for 11th Generation Intel® Core™ Processor Family for Internet of Things (IoT) Applications (formerly codenamed Tiger Lake) including new inference performance enhancements with Iris® Xe Graphics and Intel® DL Boost instructions, as well as Intel® Gaussian & Neural Accelerators 2.0 for low-power speech processing acceleration.
• Going Beyond Vision. Enables end-to-end capabilities to leverage the Intel® Distribution of OpenVINO™ toolkit for workloads beyond computer vision, which include audio, speech, language, and recommendation, with new pre-trained models, support for public models, code samples and demos, and support for non-vision workloads in OpenVINO™ toolkit DL Streamer.
• Coming in Q4 2020: (Beta Release) Integration of DL Workbench and the Intel® DevCloud for the Edge. Developers can now graphically analyze models using the DL Workbench on Intel® DevCloud for the Edge (instead of a local machine only) to compare, visualize and fine-tune a solution against multiple remote hardware configurations.
• OpenVINO™ Model Server. An add-on to the Intel® Distribution of OpenVINO™ toolkit and a scalable microservice, which provides a gRPC or HTTP/REST endpoint for inference, makes it easier to deploy models in cloud or edge server environments. It is now implemented in C++ to enable reduced container footprint (for example, less than 500MB) and deliver higher throughput and lower latency.
• Now available through Gitee* and PyPI* distribution methods. You are encouraged to choose from the distribution methods and download.

You can find OpenVINO™ toolkit 2021.1 release here:

• Download archives* with OpenVINO™ Runtime

Release Notes: https://software.intel.com/content/www/us/en/develop/articles/openvino-relnotes.html