4547818fb1
* Refactored code, updated comments and documentation related to TF OD API models pre-processing. * Improved MO messages related to pre-processor block removal during conversion of the TD OD API models. Remove mean/scale if padding is used and mean/scale is applied before resize * Updated TF OD API transformation and documentation for SSD models * Updated comments and documentation for the ObjectDetectionAPIMaskRCNNSigmoidReplacement transformation * Updated comments and documentation for the ObjectDetectionAPIMaskRCNNROIPoolingSecondReplacement transformation * Updated comments and documentation for the ObjectDetectionAPIPSROIPoolingReplacement transformation * Updated comments and documentation for the ObjectDetectionAPIProposalReplacement transformation * Updated comments and documentation for the ObjectDetectionAPIDetectionOutputReplacement transformation * Minor code style fixes * Fixed unit tests for ObjectDetectionAPIPreprocessor2Replacement transformation * Improved unit test for pipeline.config parser. Fixed very long bug with incorrect test data for the PipelineConfig parser class * Code style fixes * Get rid of "coordinates_swap_method" parameter in the JSON configuration file for TF OD API models * Code style fixes and minor refactoring * Simplied code related to swapping Proposal coordinates * Removed incorrectly removed code * Fixed code review comments about the code comments |
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| tools | ||
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| README.md | ||
| SECURITY.md | ||
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.