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@ -3,7 +3,7 @@
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- [Authorization](#authorization)
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- [Administration panel](#administration-panel)
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- [Creating an annotation task](#creating-an-annotation-task)
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- [Model manager](#model-manager)
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- [Models](#models)
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- [Search](#search)
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- [Interface of the annotation tool](#interface-of-the-annotation-tool)
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- [Basic navigation](#basic-navigation)
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@ -272,24 +272,42 @@ Go to the [Django administration panel](http://localhost:8080/admin). There you
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### Model manager
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### Models
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The application will be enabled automatically if [OpenVINO™ component](/components/openvino/README.md) is installed.
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It allows to use custom models for auto annotation. Only models in OpenVINO™ toolkit format are supported.
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If you would like to annotate a task with a custom model,
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please convert it to the intermediate representation (IR) format via the model optimizer tool.
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See [OpenVINO documentation](https://software.intel.com/en-us/articles/OpenVINO-InferEngine) for details.
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You can "register" a model and "use" it after that to pre annotate your tasks.
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On the ``Models`` page allows you to manage your deep learning (DL) models uploaded for auto annotation.
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Using the functionality you can upload, update or delete a specific DL model.
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To open the model manager, click the ``Models`` button on the navigation bar.
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The ``Models`` page contains information about all the existing models. The list of models is divided into two sections:
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- Primary — contains default CVAT models. Each model is a separate element.
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It contains the model’s name, a framework on which the model was based on and
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``Supported labels`` (a dropdown list of all supported labels).
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- Uploaded by a user — Contains models uploaded by a user.
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The list of user models has additional columns with the following information:
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name of the user who uploaded the model and the upload date.
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Here you can delete models in the ``Actions`` menu.
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The model manager allows you to manage your deep learning (DL) models uploaded for auto annotation.
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Using the functionality you can upload, update or delete a specific DL model.
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Use "Auto annotation" button to pre annotate a task using one of your DL models.
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[Read more](/cvat/apps/auto_annotation)
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In order to add your model, click `` Create new model``.
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Enter model name, and select model file using "Select files" button.
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To annotate a task with a custom model you need to prepare 4 files:
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- ``Model config`` (*.xml) - a text file with network configuration.
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- ``Model weights`` (*.bin) - a binary file with trained weights.
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- ``Label map`` (*.json) - a simple json file with label_map dictionary like an object with
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string values for label numbers.
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- ``Interpretation script`` (*.py) - a file used to convert net output layer to a predefined structure
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which can be processed by CVAT.
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You can learn more about creating model files by pressing [(?)](/cvat/apps/auto_annotation).
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Check the box `` Load globally`` if you want everyone to be able to use the model.
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Click the ``Submit`` button to submit a model.
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After the upload is complete your model can be found in the ``Uploaded by a user`` section.
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Use "Auto annotation" button to pre annotate a task using one of your DL models.
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[Read more](/cvat/apps/auto_annotation)
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### Search
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There are several options how to use the search.
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