OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Yegor Kruglov 4d9fe14ec6
[MO] ConvolutionWithGroupResolver update to enable TF DepthwiseConv2dNative with in_channels=1 (#5528)
* changed permutation attribute in conv extractor

* changed conv get_group parameter

* implemented a transformation

* updated BOM

* specified transformation for in_channels 1

* added unittest and comment string

* updated convolution normalizer to convert depthwise convolution with group=1 to group convolution

* renamed function

* updated IR reader

* conversations resolving

* condition change
2021-06-07 20:22:26 +03:00
.ci Python in OpenVINO: improvements (#6027) 2021-06-07 10:52:48 +03:00
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cmake Python in OpenVINO: improvements (#6027) 2021-06-07 10:52:48 +03:00
docs RegionYolo operation specification refactoring. (#5926) 2021-06-07 20:12:57 +03:00
inference-engine [IE CLDNN] 54304 fix reduce ops (#5986) 2021-06-07 18:36:38 +03:00
licensing [Speech sample] Added numpy array support (#5479) 2021-06-03 12:22:06 +03:00
model-optimizer [MO] ConvolutionWithGroupResolver update to enable TF DepthwiseConv2dNative with in_channels=1 (#5528) 2021-06-07 20:22:26 +03:00
ngraph Add get_constant_from_source capability to pyngraph (#6018) 2021-06-07 18:19:52 +03:00
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scripts scripts: remove pot dependencies (#5956) 2021-06-01 18:22:22 +03:00
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thirdparty [Speech sample] Added numpy array support (#5479) 2021-06-03 12:22:06 +03:00
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CMakeLists.txt Python in OpenVINO: improvements (#6027) 2021-06-07 10:52:48 +03:00
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OpenVINO™ Toolkit

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

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.