OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Mikhail Nosov c2d09afab9
PreProcess API change: (#8629)
- PrePostProcessor takes 'function' argument in constructor
- PrePostProcessor::build() doesn't take any function anymore
- PrePostProcessor::input() method to get reference to input
- PrePostProcessor::output() method to get reference to output
- InputInfo - add getters of tensor, preprocess, network
- OutputInfo - add getters of tensor, preprocess, network

Samples:
ClassificationSampleAsync - use new getters

Inference engine:
- Use new getters in ie_network_reader.cpp

TODO: Consider removal of builder-like API in PrePostProcessor, InputInfo, OutputInfo
2021-11-17 00:51:19 +03:00
.ci Move unit_tests from test_pkg/tools to test_pkg/tests (#8548) 2021-11-15 14:18:16 +03:00
.github [Python API] Move samples and docs to the new directory (#7851) 2021-10-14 14:49:35 +03:00
cmake Fixed ie_mark_target_as_cc (#8608) 2021-11-16 06:48:02 +03:00
docs PreProcess API change: (#8629) 2021-11-17 00:51:19 +03:00
inference-engine PreProcess API change: (#8629) 2021-11-17 00:51:19 +03:00
licensing Update third party files (#8382) 2021-11-03 15:29:42 +03:00
model-optimizer Fix of ReverseInputChannels for NHWC layout. (#8504) 2021-11-15 15:24:46 +03:00
ngraph PreProcess API change: (#8629) 2021-11-17 00:51:19 +03:00
openvino Enable GPU in static build w/o oneDNN (#8563) 2021-11-15 13:44:11 +03:00
runtime [PYTHON] Expose layout helpers (#8507) 2021-11-17 00:47:18 +03:00
samples samples: Print verbose error messages to stderr (#7795) 2021-11-10 11:42:52 +03:00
scripts [IE Sample Scripts] Use cmake to build samples (#8442) 2021-11-10 17:31:28 +03:00
tests [TF FE] Implement and refactor tensorflow layer tests (#8051) 2021-11-12 11:03:45 +03:00
thirdparty Fixed cnpy coverity issues (#8515) 2021-11-15 17:24:48 +03:00
tools [POT] Add pattern se blocks (#8425) 2021-11-15 12:53:07 +03:00
.gitattributes [POT] Update tests with new data (#8209) 2021-10-27 12:40:19 +03:00
.gitignore [POT] Added missed file to POT (#8118) 2021-10-21 11:28:26 +03:00
.gitmodules Moved Post-training Optimization Tool to open-source (#7940) 2021-10-15 16:35:35 +03:00
CMakeLists.txt Added support of external modules in static build (#8518) 2021-11-12 08:56:57 +03:00
CODEOWNERS CODEOWNERS: Add /tools/pot/ @openvinotoolkit/openvino-pot-maintainers 2021-11-02 13:55:02 +03:00
install_build_dependencies.sh Added reporting of unresolved symbols for plugins (#7810) 2021-10-05 04:26:01 +03:00
Jenkinsfile Beautify Jenkinsfile a little bit 2021-05-31 15:24:56 +03:00
LICENSE Publishing R3 2018-10-16 13:45:03 +03:00
README.md [README.md] change latest release to 2021.4.2 2021-11-16 22:12:20 +03:00
SECURITY.md Added SECURITY.md back (#3177) 2020-11-17 16:44:44 +03:00

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

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