Viewing your models - Amazon Lookout for Vision

End of support notice: On October 31, 2025, AWS will discontinue support for Amazon Lookout for Vision. After October 31, 2025, you will no longer be able to access the Lookout for Vision console or Lookout for Vision resources. For more information, visit this blog post.

Viewing your models

A project can have multiple versions of a model. You can use the console to view the models in a project. You can also use the ListModels operation.

Note

The list of models is eventually consistent. If you create a model, you might have to wait a short while before the models list is up to date.

Viewing your models (console)

Perform the steps in the following procedure to view your project's models in the console.

To view your models (console)
  1. Open the Amazon Lookout for Vision console at https://console.aws.amazon.com/lookoutvision/.

  2. Choose Get started.

  3. In the left navigation pane, choose Projects.

  4. On the Projects page, select the project that contains the models that you want to view.

  5. In the left navigation pane, choose Models and then view the model details.

Viewing your models (SDK)

To get view the versions of a model you use the ListModels operation. To get information about a specific model version, use the DescribeModel operation. The following example lists all the model versions in a project and then displays performance and output configuration information for individual model versions.

To view your models (SDK)
  1. If you haven't already done so, install and configure the AWS CLI and the AWS SDKs. For more information, see Step 4: Set up the AWS CLI and AWS SDKs.

  2. Use the following example code to list your models and get information about a model.

    CLI

    Use the list-models command to list the models in a project.

    Change the following value:

    • project-name to the name of the project that contains the model that you want to view.

    aws lookoutvision list-models --project-name project name \ --profile lookoutvision-access

    Use the describe-model command to get information about a model. Change the following values:

    • project-name to the name of the project that contains the model that you want to view.

    • model-version to the version of the model that you want to describe.

    aws lookoutvision describe-model --project-name project name\ --model-version model version \ --profile lookoutvision-access
    Python

    This code is taken from the AWS Documentation SDK examples GitHub repository. See the full example here.

    @staticmethod def describe_models(lookoutvision_client, project_name): """ Gets information about all models in a Lookout for Vision project. :param lookoutvision_client: A Boto3 Lookout for Vision client. :param project_name: The name of the project that you want to use. """ try: response = lookoutvision_client.list_models(ProjectName=project_name) print("Project: " + project_name) for model in response["Models"]: Models.describe_model( lookoutvision_client, project_name, model["ModelVersion"] ) print() print("Done...") except ClientError: logger.exception("Couldn't list models.") raise
    Java V2

    This code is taken from the AWS Documentation SDK examples GitHub repository. See the full example here.

    /** * Lists the models in an Amazon Lookout for Vision project. * * @param lfvClient An Amazon Lookout for Vision client. * @param projectName The name of the project that contains the models that * you want to list. * @return List <Metadata> A list of models in the project. */ public static List<ModelMetadata> listModels(LookoutVisionClient lfvClient, String projectName) throws LookoutVisionException { ListModelsRequest listModelsRequest = ListModelsRequest.builder() .projectName(projectName) .build(); // Get a list of models in the supplied project. ListModelsResponse response = lfvClient.listModels(listModelsRequest); for (ModelMetadata model : response.models()) { logger.log(Level.INFO, "Model ARN: {0}\nVersion: {1}\nStatus: {2}\nMessage: {3}", new Object[] { model.modelArn(), model.modelVersion(), model.statusMessage(), model.statusAsString() }); } return response.models(); }