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27 lines
1.5 KiB
Markdown
27 lines
1.5 KiB
Markdown
---
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title: 'Models'
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linkTitle: 'Models'
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weight: 13
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---
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To deploy the models, you will need to install the necessary components using
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[Semi-automatic and Automatic Annotation guide](/docs/administration/advanced/installation_automatic_annotation/).
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To learn how to deploy the model, read [Serverless tutorial](/docs/manual/advanced/serverless-tutorial/).
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The Models page contains a list of deep learning (DL) models deployed for semi-automatic and automatic annotation.
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To open the Models page, click the Models button on the navigation bar.
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The list of models is presented in the form of a table. The parameters indicated for each model are the following:
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- `Framework` the model is based on
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- model `Name`
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- model `Type`:
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- `detector` - used for automatic annotation (available in [detectors](/docs/manual/advanced/ai-tools/#detectors)
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and [automatic annotation](/docs/manual/advanced/automatic-annotation/))
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- `interactor` - used for semi-automatic shape annotation (available in [interactors](/docs/manual/advanced/ai-tools/#interactors))
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- `tracker` - used for semi-automatic track annotation (available in [trackers](/docs/manual/advanced/ai-tools/#trackers))
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- `reid` - used to combine individual objects into a track (available in [automatic annotation](/docs/manual/advanced/automatic-annotation/))
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- `Description` - brief description of the model
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- `Labels` - list of the supported labels (only for the models of the `detectors` type)
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