33 lines
1.6 KiB
Markdown
33 lines
1.6 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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{{< ilink "/docs/administration/advanced/installation_automatic_annotation"
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"Semi-automatic and Automatic Annotation guide" >}}.
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To learn how to deploy the model, read
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{{< ilink "/docs/manual/advanced/serverless-tutorial" "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
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(available in {{< ilink "/docs/manual/advanced/ai-tools#detectors" "detectors" >}}
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and {{< ilink "/docs/manual/advanced/automatic-annotation" "automatic annotation" >}})
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- `interactor` - used for semi-automatic shape annotation
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(available in {{< ilink "/docs/manual/advanced/ai-tools#interactors" "interactors" >}})
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- `tracker` - used for semi-automatic track annotation
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(available in {{< ilink "/docs/manual/advanced/ai-tools#trackers" "trackers" >}})
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- `reid` - used to combine individual objects into a track
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(available in {{< ilink "/docs/manual/advanced/automatic-annotation" "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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