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panel](http://localhost:8080/admin). There you ![](static/documentation/images/image007.jpg) -### Model manager - -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. +### Models + +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.