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Updating the Model Manager section of the CVAT User Guide #991

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42 changes: 30 additions & 12 deletions cvat/apps/documentation/user_guide.md
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
- [Authorization](#authorization)
- [Administration panel](#administration-panel)
- [Creating an annotation task](#creating-an-annotation-task)
- [Model manager](#model-manager)
- [Models](#models)
- [Search](#search)
- [Interface of the annotation tool](#interface-of-the-annotation-tool)
- [Basic navigation](#basic-navigation)
Expand Down Expand Up @@ -272,24 +272,42 @@ Go to the [Django administration panel](http://localhost:8080/admin). There you

![](static/documentation/images/image007.jpg)

### Model manager
### Models

The application will be enabled automatically if [OpenVINO™ component](/components/openvino/README.md) is installed.
It allows to use custom models for auto annotation. Only models in OpenVINO™ toolkit format are supported.
If you would like to annotate a task with a custom model,
please convert it to the intermediate representation (IR) format via the model optimizer tool.
See [OpenVINO documentation](https://software.intel.com/en-us/articles/OpenVINO-InferEngine) for details.
You can "register" a model and "use" it after that to pre annotate your tasks.
On the ``Models`` page allows you to manage your deep learning (DL) models uploaded for auto annotation.
Using the functionality you can upload, update or delete a specific DL model.
To open the model manager, click the ``Models`` button on the navigation bar.
The ``Models`` page contains information about all the existing models. The list of models is divided into two sections:
- Primary — contains default CVAT models. Each model is a separate element.
It contains the model’s name, a framework on which the model was based on and
``Supported labels`` (a dropdown list of all supported labels).
- Uploaded by a user — Contains models uploaded by a user.
The list of user models has additional columns with the following information:
name of the user who uploaded the model and the upload date.
Here you can delete models in the ``Actions`` menu.

![](static/documentation/images/image099.jpg)

The model manager allows you to manage your deep learning (DL) models uploaded for auto annotation.
Using the functionality you can upload, update or delete a specific DL model.
Use "Auto annotation" button to pre annotate a task using one of your DL models.
[Read more](/cvat/apps/auto_annotation)
In order to add your model, click `` Create new model``.
Enter model name, and select model file using "Select files" button.
To annotate a task with a custom model you need to prepare 4 files:
- ``Model config`` (*.xml) - a text file with network configuration.
- ``Model weights`` (*.bin) - a binary file with trained weights.
- ``Label map`` (*.json) - a simple json file with label_map dictionary like an object with
string values for label numbers.
- ``Interpretation script`` (*.py) - a file used to convert net output layer to a predefined structure
which can be processed by CVAT.

You can learn more about creating model files by pressing [(?)](/cvat/apps/auto_annotation).
Check the box `` Load globally`` if you want everyone to be able to use the model.
Click the ``Submit`` button to submit a model.

![](static/documentation/images/image104.jpg)

After the upload is complete your model can be found in the ``Uploaded by a user`` section.
Use "Auto annotation" button to pre annotate a task using one of your DL models.
[Read more](/cvat/apps/auto_annotation)

### Search

There are several options how to use the search.
Expand Down