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Score Image Model

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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

  1. Add the Score Image Model component to your pipeline.

  2. 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.

  3. Submit the pipeline.

Results

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.

Next steps

See the set of components available to Azure Machine Learning.