Deploy View

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Deploy View

Overview
PerceptiLabs Deploy View allows you to export and deploy your model to different targets.
The view displays the following options to select the model(s) to export/deploy:
    1. Model Selection Checkbox: enable this to select the model(s) for export/deployment.
    2. Search bar: allows you to filter the list of models by name.
To the right of the model selection screen are the export/deployment targets that you can click:
 
The following subsections describe these targets:
Export Options
The current export options include:
TensorFlow: exports to TensorFlow's exported model format or to TensorFlow Lite.
FastAPI Server: generates a TensorFlow model along with a Python server app with a simple API that you can use for inference on your model.
PL Package: exports a zipped package containing your PerceptiLabs model that you easily can share and load.
Selecting either of these displays a popup with some or all of the following options:
Save to: allows you to specify the location to which the exported model files are to be placed. 
Optimize (available for TensorFlow model exports): provides options to compress and/or quantize your exported model(s) during export. Selecting either of these options will export to TensorFlow Lite format.
Deployment Options
Select Gradio to export and deploy your model as a Gradio app. 
Using the Exported/Deployed Model
After you complete the export/deployment the model can be used for inference.
See Exporting and Deploying Models for information on how to use your exported/deployed model.
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Using the Exported/Deployed Model

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Overview

Export Options

Deployment Options

Using the Exported/Deployed Model

Overview

Export Options

Deployment Options

Using the Exported/Deployed Model

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