Roman Kazantsev 42892767f5 [MO, nGraph, transforms., ref., python] Support DetectionOutput-8 (#8853)
* Implement MO part for DetectionOutput-8

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Implement nGraph part for DetectionOutput-8

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Implement deduction of a number of classes method

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix build

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Implement nGraph tests to check shape inference for DetectionOutput-8 with deduction of num_classes

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Implement attributes tests for DetectionOutput-8

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Remove DetectionOutput-1 from opset8

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Add python bindings for DetectionOutput-8 and tests

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Implement downgrading and upgrading transformations for DetectionOutput

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Implement tests for downgrading and upgrading transformations for DetectionOutput

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Adopt existing reference for DetectionOutput-8

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix DetectionOutput-8 reference

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Add tests for DetectionOutput-8 reference

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Finish resolving merge conflict

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix python bindings after re-structuring

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix BOM package list

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix multibox_detection_test

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix python bindings for DetectionOutput-8

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Insert blank line between summary and description for python binding

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Apply review comments: identation, for loop

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix formatting in python bindings

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix supported_attrs for DetectionOutput from opset1

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Add missed imports for python if_op

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Apply feedback and fix Win build

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Use the same test suite name for test mixture

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix transformation tests

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Recover BWDCMP_RTTI for legacy use and remove unused variables in tests

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Remove unused variables in type_prop tests

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Recover legacy referenceDetectionOutput constructor

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix python binding for DetectionOutput

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
2021-12-07 01:17:49 +03:00
2021-12-06 17:25:35 +03:00
2021-11-27 11:28:25 +03:00
2021-11-27 11:28:25 +03:00
2021-05-31 15:24:56 +03:00
2018-10-16 13:45:03 +03:00
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*.

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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.

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