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

  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.


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.