OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Tomasz Dołbniak 6780dfcba7
Update of ONNX submodule to v1.10.2 (#8383)
* Update of ONNX submodule to v1.10.0

* Update of ONNX to 1.10.2

* Adaptation of the ONNX FE to ONNX 1.10

* ConstantOfShape XFAIL removal

* SCEL reference model updated to the new ONNX functions expansion behavior

* UnXFAIL more ONNX tests

* UnXFAIL even more ONNX tests
2021-11-09 12:53:34 +03:00
.ci Azure CI: exclude docs from required pipelines triggers (#8468) 2021-11-09 12:33:22 +03:00
.github [Python API] Move samples and docs to the new directory (#7851) 2021-10-14 14:49:35 +03:00
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docs [GPU] Fix default value of KEY_GPU_MODEL_PRIORITY (#8398) 2021-11-04 12:49:00 +03:00
inference-engine FullyConnectedNode: deserialization fix (#8345) 2021-11-09 12:14:36 +03:00
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model-optimizer Offline transformations exposed to python with pybind11 (#7987) 2021-11-03 20:00:14 +03:00
ngraph Update of ONNX submodule to v1.10.2 (#8383) 2021-11-09 12:53:34 +03:00
openvino Fixed dlerror KW issue (#8184) 2021-10-25 13:46:31 +03:00
runtime Update of ONNX submodule to v1.10.2 (#8383) 2021-11-09 12:53:34 +03:00
samples [IE Samples] Enable a custom build output folder (#8263) 2021-11-08 14:15:30 +03:00
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thirdparty Update of ONNX submodule to v1.10.2 (#8383) 2021-11-09 12:53:34 +03:00
tools [POT] Update for the Results quantization & tests (#8324) 2021-11-08 16:28:54 +03:00
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.gitmodules Moved Post-training Optimization Tool to open-source (#7940) 2021-10-15 16:35:35 +03:00
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OpenVINO™ Toolkit

Stable release Apache License Version 2.0 GitHub branch checks state Azure DevOps builds (branch) PyPI Downloads

This toolkit allows developers to deploy pre-trained deep learning models through a high-level C++ Inference Engine API integrated with application logic.

This open source version includes several components: namely Model Optimizer, nGraph and Inference Engine, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as Caffe*, TensorFlow*, MXNet* and ONNX*.

Repository components:

License

Deep Learning Deployment Toolkit is licensed under Apache License Version 2.0. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.

Resources:

Support

Please report questions, issues and suggestions using:


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