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* Preprocessing API - base classes Includes API definition for trivial mean/scale operations (which don't require layout) Mean/scale with 'layout' support will be done under separate task together with Layout Current test code coverage: 100% * Python bindings for base preprocessing API * remove pre_post_process directory from ngraph/core * remove files from ngraph/python dir * move pyngraph pre_post_process files from ngraph/python to runtime * remove pre_post_process test from CMakeList * move include to the header * update include path for pre_post_process * style fix * bind InputTensorInfo::set_layout * cleaned test_preprocess * fix test expected output * remove duplicate test * update description of set_element_type * fix style * move preprocess from pyngraph to pyopenvino/graph * update test_preprocess imports and remove unnecessary test * remove duplicate import * update custom method * update test * update test * create decorator that changes Node into Output<Node> * create function that cast Node to Output<Node> * update test_preprocess to use decorator for custom function * change _cast_to_output -> _from_node * move frontend folder to pyopenvino * rename includes and add compile options * include frontend to pyopenvino * move __init__.py * move tests * remove mock from tests_compatibility * rename import module * Fix code style cpp * refactor a few lines * style fix * update few lines in mo * add tests fro scale and mean with vector input * style fix * add docstring for custom_preprocess_function * bind InputInfo network method * style fix * Add pyopenvino to dependencies * bind OutputInfo * fix description of preprocess submodule * fix style * update copyright year * Fix mock * update docstring * bind OutputTensorInfo * bind OutputNetworkInfo and InputNetworkInfo * bind ColorFormat and ResizeAlgorithm * clean imports * fix typo * add PostProcessSteps to init * bind PreProcessSteps * create additional tests * Fix mo test * remove module local * fix code style * update comment * fix return type * update docs * fix code style * change ngraph.Type to ov.Type * fix typo * move _from_node to node_output.hpp * add read_model from buffer * update imports * add new line * remove bad quotes * update imports * style fix * add new line * rename functin args * remove Type import * update tests * style fix * test clean * remove blank line * update PrePostProcessor init and build methods * create test with model update tests with new PrePostProcessor init and build * # Conflicts: # inference-engine/ie_bridges/python/src/openvino/offline_transformations/offline_transformations_api.pyx # inference-engine/ie_bridges/python/src/openvino/offline_transformations/offline_transformations_api_impl.cpp # inference-engine/ie_bridges/python/src/openvino/offline_transformations/offline_transformations_api_impl.hpp # inference-engine/ie_bridges/python/src/openvino/offline_transformations/offline_transformations_api_impl_defs.pxd # inference-engine/tests/ie_test_utils/common_test_utils/ngraph_test_utils.cpp # inference-engine/tests/ie_test_utils/common_test_utils/ngraph_test_utils.hpp # model-optimizer/mo/moc_frontend/serialize.py # thirdparty/gflags/gflags # thirdparty/gtest/gtest * Stash * move preprocess module from openvino.impl to openvino * fix building * fix code style * try to move MO to use new api * Intermediate commit * try to move MO to use new api * Test pybind11 custom holder for Preprocessing types (InputInfo and PreProcessingSteps) * Initial code for source_target layout handling for preprocessing Initial implementation of reverse input channels * Use input's tensor names instead of friendly names * Skeleton for guessing layouts and clearing it after preprocessing * updated package_BOM.txt * Use reference_wrapper for preprocess bindings * Update tests * Layout::find_permutation - support of dynamic layouts Covered case for 'trivial convert' where no permutation is needed It is needed for Model Optimizer for logic which will guess model's layout, like "?c??" * Stash * add bindings to I420_SINGLE_PLANE and I420_THREE_PLANES * remove init from all classes except PrePostProcessor and add RGBX and BGRX to ColorFormat enum * Guess layout so that existing mean/scale tests passed * update test name * Draft to guess layout for 'reverse_input_channels' * More unit tests (error cases) * pylint & flake8 * pylint - ignore import error * Stash * Moved preprocessing to 'back' folder * More tests * Update package_BOM * Support layout_values with no names Support layout set for 'outputs' Tests * Export more enum names from nrgaph * Basic --layout parsing * removed debug prints * Further updates after rebase * Update imports * Removed part from 8829 * Fix imports in test code * Minor cosmetics * Don't guess 'C' if layout is already set by model Expose 'Layout::empty' method * Style fix * Apply review comments Restricted 'heuristics' C++: Added 'fp16', 'fp64' support to mean/scale * Applied review comments * Added some dynamic test cases * Move call of 'apply_preprocessing' to 'serialize.py' * Unnecessary change * Added more comments to code Co-authored-by: pszmel <piotr.szmelczynski@intel.com> Co-authored-by: Alexey Lebedev <alexey.lebedev@intel.com> Co-authored-by: bszmelcz <bartosz.szmelczynski@intel.com> Co-authored-by: Anastasia Kuporosova <anastasia.kuporosova@intel.com> Co-authored-by: y <ilya.lavrenov@intel.com> Co-authored-by: Vafin, Maxim <maxim.vafin@intel.com>
OpenVINO™ Toolkit
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:
- Docs: https://docs.openvinotoolkit.org/
- Wiki: https://github.com/openvinotoolkit/openvino/wiki
- Issue tracking: https://github.com/openvinotoolkit/openvino/issues
- Storage: https://storage.openvinotoolkit.org/
- Additional OpenVINO™ modules: https://github.com/openvinotoolkit/openvino_contrib
- Intel® Distribution of OpenVINO™ toolkit Product Page
- Intel® Distribution of OpenVINO™ toolkit Release Notes
Support
Please report questions, issues and suggestions using:
- The
openvinotag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.