[DOCS] Add OTX page to Ecosystem (#16118)
* add otx page * change ecosystem page * add ote img * move ote page to rst * fix path * add path * img test * otx page * add docs to ecosystem page
This commit is contained in:
1 parent
cf8dccaedb
commit
3faf4fcb3e
3 files changed
+54
-7
No files matched your search
@@ -6,11 +6,11 @@
|
||||
:maxdepth: 1
|
||||
:hidden:
|
||||
|
||||
ote_documentation
|
||||
ovtf_integration
|
||||
ovsa_get_started
|
||||
openvino_inference_engine_tools_compile_tool_README
|
||||
openvino_docs_tuning_utilities
|
||||
workbench_docs_Workbench_DG_Introduction
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
@@ -25,6 +25,15 @@ More resources:
|
||||
* [GitHub](https://github.com/openvinotoolkit/nncf)
|
||||
* [PyPI](https://pypi.org/project/nncf/)
|
||||
|
||||
### OpenVINO™ Training Extensions
|
||||
A convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.
|
||||
|
||||
More resources:
|
||||
|
||||
* [Overview](@ref ote_documentation)
|
||||
* [GitHub](https://github.com/openvinotoolkit/training_extensions)
|
||||
* [Documentation](https://openvinotoolkit.github.io/training_extensions/stable/guide/get_started/introduction.html)
|
||||
|
||||
### OpenVINO™ Security Add-on
|
||||
A solution for Model Developers and Independent Software Vendors to use secure packaging and secure model execution.
|
||||
|
||||
@@ -48,6 +57,7 @@ More resources:
|
||||
* [documentation on GitHub](https://dlstreamer.github.io/index.html)
|
||||
* [installation Guide on GitHub](https://github.com/openvinotoolkit/dlstreamer_gst/wiki/Install-Guide)
|
||||
|
||||
|
||||
### DL Workbench
|
||||
A web-based tool for deploying deep learning models. Built on the core of OpenVINO and equipped with a graphics user interface, DL Workbench is a great way to explore the possibilities of the OpenVINO workflow, import, analyze, optimize, and build your pre-trained models. You can do all that by visiting [Intel® Developer Cloud](https://software.intel.com/content/www/us/en/develop/tools/devcloud.html) and launching DL Workbench online.
|
||||
|
||||
@@ -56,12 +66,6 @@ More resources:
|
||||
* [Docker Hub](https://hub.docker.com/r/openvino/workbench)
|
||||
* [PyPI](https://pypi.org/project/openvino-workbench/)
|
||||
|
||||
### OpenVINO™ Training Extensions (OTX)
|
||||
A convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.
|
||||
|
||||
More resources:
|
||||
* [GitHub](https://github.com/openvinotoolkit/training_extensions)
|
||||
|
||||
### Computer Vision Annotation Tool (CVAT)
|
||||
An online, interactive video and image annotation tool for computer vision purposes.
|
||||
|
||||
|
||||
@@ -0,0 +1,40 @@
|
||||
# OpenVINO™ Training Extensions {#ote_documentation}
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
OpenVINO™ Training Extensions provide a suite of advanced algorithms to train
|
||||
Deep Learning models and convert them using the `OpenVINO™
|
||||
toolkit <https://software.intel.com/en-us/openvino-toolkit>`__ for optimized
|
||||
inference. It allows you to export and convert the models to the needed format. OpenVINO Training Extensions independently create and train the model. It is open-sourced and available on `GitHub <https://github.com/openvinotoolkit/training_extensions>`__. Read the OpenVINO Training Extensions `documentation <https://openvinotoolkit.github.io/training_extensions/stable/guide/get_started/introduction.html>`__ to learn more.
|
||||
|
||||
Detailed Workflow
|
||||
#################
|
||||
|
||||
.. image:: ./_static/images/training_extensions_framework.png
|
||||
|
||||
1. To start working with OpenVINO Training Extensions, prepare and annotate your dataset. For example, on CVAT.
|
||||
|
||||
2. OpenVINO Training Extensions train the model, using training interface, and evaluate the model quality on your dataset, using evaluation and inference interfaces.
|
||||
|
||||
.. note::
|
||||
Prepare a separate dataset or split the dataset you have for more accurate quality evaluation.
|
||||
|
||||
3. Having successful evaluation results received, you have an opportunity to deploy your model or continue optimizing it, using NNCF and POT. For more information about these frameworks, go to :doc:`Optimization Guide <openvino_docs_model_optimization_guide>`.
|
||||
|
||||
If the results are unsatisfactory, add datasets and perform the same steps, starting with dataset annotation.
|
||||
|
||||
OpenVINO Training Extensions Components
|
||||
#######################################
|
||||
|
||||
- `OpenVINO Training Extensions SDK <https://github.com/openvinotoolkit/training_extensions/tree/master/ote_sdk>`__
|
||||
- `OpenVINO Training Extensions CLI <https://github.com/openvinotoolkit/training_extensions/tree/master/ote_cli>`__
|
||||
- `OpenVINO Training Extensions Algorithms <https://github.com/openvinotoolkit/training_extensions/tree/master/external>`__
|
||||
|
||||
Tutorials
|
||||
#########
|
||||
|
||||
`Object Detection <https://github.com/openvinotoolkit/training_extensions/blob/master/ote_cli/notebooks/train.ipynb>`__
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
|
||||
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:2b3932d0cf0071c629e1013f3e17a9f8abda800eb01c50b3e826a42127e42da7
|
||||
size 48770
|
||||
Reference in new issue
Block a user