Score Image Model
This article describes a component in Azure Machine Learning designer.
Use this component to generate predictions using a trained image model on input image data.
How to configure Score Image Model
Add the Score Image Model component to your pipeline.
Attach a trained image model and a dataset containing input image data.
The data should be of type ImageDirectory. Refer to Convert to Image Directory component for more information about how to get a image directory. The schema of the input dataset should also generally match the schema of the data used to train the model.
Submit the pipeline.
After you have generated a set of scores using Score Image Model, to generate a set of metrics used for evaluating the model's accuracy (performance), you can connect this component and the scored dataset to Evaluate Model,
Publish scores as a web service
A common use of scoring is to return the output as part of a predictive web service. For more information, see this tutorial on how to deploy a real-time endpoint based on a pipeline in Azure Machine Learning designer.
See the set of components available to Azure Machine Learning.
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