Tagging models (console)Viewing model tags Tagging models (SDK)

Tagging a model

You can identify, organize, search for, and filter your Amazon Rekognition models by using tags. Each tag is a label consisting of a user-defined key and value. For example, to help determine billing for your models, tag your models with a Cost center key and add the appropriate cost center number as a value. For more information, see Tagging AWS resources.

Use tags to:

Track billing for a model by using cost allocation tags. For more information, see Using Cost Allocation Tags.
Control access to a model by using Identity and Access Management (IAM). For more information, see Controlling access to AWS resources using resource tags.
Automate model management. For example, you can run automated start or stop scripts that turn off development models during non-business hours to reduce costs. For more information, see Running a trained Amazon Rekognition Custom Labels model.

You can tag models by using the Amazon Rekognition console or by using the AWS SDKs.

Tagging models (console)

You can use the Rekognition console to add tags to models, view the tags attached to a model, and remove tags.

Adding or removing tags

This procedure explains how to add tags to, or remove tags from, an existing model. You can also add tags to a new model when it is trained. For more information, see Training an Amazon Rekognition Custom Labels model.

To add tags to, or remove tags from, an existing model using the console

Open the Amazon Rekognition console at https://console.aws.amazon.com/rekognition/.
Choose Get started.
In the navigation pane, choose Projects.
On the Projects resources page, choose the project that contains the model that you want to tag.
In the navigation pane, under the project you previously chose, choose Models.
In the Models section, choose the model that you want to add a tag to.
On the model's details page, choose the Tags tab.
In the Tags section, choose Manage tags.
On the Manage tags page, choose Add new tag.
Enter a key and a value.
1. For Key, enter a name for the key.
2. For Value, enter a value.
To add more tags, repeat steps 9 and 10.
(Optional) To remove a tag, choose Remove next to the tag that you want to remove. If you are removing a previously saved tag, it is removed when you save your changes.
Choose Save changes to save your changes.

Viewing model tags

You can use the Amazon Rekognition console to view the tags attached to a model.

To view the tags attached to all models within a project, you must use the AWS SDK. For more information, see Listing model tags.

To view the tags attached to a model

Open the Amazon Rekognition console at https://console.aws.amazon.com/rekognition/.
Choose Get started.
In the navigation pane, choose Projects.
On the Projects resources page, choose the project that contains the model whose tag you want to view.
In the navigation pane, under the project you previously chose, choose Models.
In the Models section, choose the model whose tag you want to view.
On the model's details page, choose the Tags tab. The tags are shown in Tags section.

Tagging models (SDK)

You can use the AWS SDK to:

Add tags to a new model
Add tags to an existing model
List the tags attached to a model
Remove tags from a model

The tags in the following AWS CLI examples are in the following format.


--tags '{"key1":"value1","key2":"value2"}'

Alternatively, you can use this format.


--tags key1=value1,key2=value2

If you haven't installed the AWS CLI, see Step 4: Set up the AWS CLI and AWS SDKs.

Adding tags to a new model

You can add tags to a model when you create it using the CreateProjectVersion operation. Specify one or more tags in the Tags array input parameter.


aws rekognition create-project-version --project-arn project arn \
  --version-name version_name \
  --output-config '{ "S3Location": { "Bucket": "output bucket", "Prefix":  "output folder" } }' \
  --tags '{"key1":"value1","key2":"value2"}' \
  --profile custom-labels-access

For information about creating and training a model, see Training a model (SDK).

Adding tags to an existing model

To add one or more tags to an existing model, use the TagResource operation. Specify the model's Amazon Resource Name (ARN) (ResourceArn) and the tags (Tags) that you want to add. The following example shows how to add two tags.


aws rekognition tag-resource --resource-arn resource-arn \
  --tags '{"key1":"value1","key2":"value2"}' \
  --profile custom-labels-access

You can get the ARN for a model by calling CreateProjectVersion.

Listing model tags

To list the tags attached to a model, use the ListTagsForResource operation and specify the ARN of the model (ResourceArn). The response is a map of tag keys and values that are attached to the specified model.


aws rekognition list-tags-for-resource --resource-arn resource-arn \
  --profile custom-labels-access

The output displays a list of the tags attached to the model.


{
    "Tags": {
        "Dept": "Engineering",
        "Name": "Ana Silva Carolina",
        "Role": "Developer"
    }
}

To see which models in a project have a specific tag, call DescribeProjectVersions to get a list of models. Then call ListTagsForResource for each model in the response from DescribeProjectVersions. Inspect the response from ListTagsForResource to see if the required tag is present.

The following Python 3 example shows you how search all your projects for a specific tag key and value. The output includes the project ARN and the model ARN where a matching key is found.

To search for a tag value

Save the following code to a file named find_tag.py.


# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""
Purpose
Shows how to find a tag value that's associated with models within
your Amazon Rekognition Custom Labels projects.
"""
import logging
import argparse
import boto3

from botocore.exceptions import ClientError


logger = logging.getLogger(__name__)


def find_tag_in_projects(rekognition_client, key, value):
    """
    Finds Amazon Rekognition Custom Label models tagged with the supplied key and key value.
    :param rekognition_client: An Amazon Rekognition boto3 client.
    :param key: The tag key to find.
    :param value: The value of the tag that you want to find.
    return: A list of matching model versions (and model projects) that were found.
    """
    try:

        found_tags = []
        found = False

        projects = rekognition_client.describe_projects()
        # Iterate through each project and models within a project.
        for project in projects["ProjectDescriptions"]:
            logger.info("Searching project: %s ...", project["ProjectArn"])

            models = rekognition_client.describe_project_versions(
                ProjectArn=(project["ProjectArn"])
            )

            for model in models["ProjectVersionDescriptions"]:
                logger.info("Searching model %s", model["ProjectVersionArn"])

                tags = rekognition_client.list_tags_for_resource(
                    ResourceArn=model["ProjectVersionArn"]
                )

                logger.info(
                    "\tSearching model: %s for tag: %s value: %s.",
                    model["ProjectVersionArn"],
                    key,
                    value,
                )
                # Check if tag exists.

                if key in tags["Tags"]:
                    if tags["Tags"][key] == value:
                        found = True
                        logger.info(
                            "\t\tMATCH: Project: %s: model version %s",
                            project["ProjectArn"],
                            model["ProjectVersionArn"],
                        )
                        found_tags.append(
                            {
                                "Project": project["ProjectArn"],
                                "ModelVersion": model["ProjectVersionArn"],
                            }
                        )

        if found is False:
            logger.info("No match for Tag %s with value %s.", key, value)
        return found_tags
    except ClientError as err:
        logger.info("Problem finding tags: %s. ", format(err))
        raise


def main():
    """
    Entry point for example.
    """
    logging.basicConfig(level=logging.INFO,
                        format="%(levelname)s: %(message)s")

    # Set up command line arguments.
    parser = argparse.ArgumentParser(usage=argparse.SUPPRESS)

    parser.add_argument("tag", help="The tag that you want to find.")
    parser.add_argument("value", help="The tag value that you want to find.")

    args = parser.parse_args()
    key = args.tag
    value = args.value

    print(f"Searching your models for tag: {key} with value: {value}.")


    session = boto3.Session(profile_name='custom-labels-access')
    rekognition_client = session.client("rekognition")

    # Get tagged models for all projects.
    tagged_models = find_tag_in_projects(rekognition_client, key, value)

    print("Matched models\n--------------")
    if len(tagged_models) > 0:
        for model in tagged_models:
            print(
                "Project: {project}\nModel version: {version}\n".format(
                    project=model["Project"], version=model["ModelVersion"]
                )
            )

    else:
        print("No matches found.")

    print("Done.")


if __name__ == "__main__":
    main()

At the command prompt, enter the following. Replace key and value with the key name and the key value that you want to find.
```
python find_tag.py key value
```

Deleting tags from a model

To remove one or more tags from a model, use the UntagResource operation. Specify the ARN of the model (ResourceArn) and the tag keys (Tag-Keys) that you want to remove.


aws rekognition untag-resource --resource-arn resource-arn \
  --tag-keys '["key1","key2"]' \
  --profile custom-labels-access

Alternatively, you can specify tag-keys in this format.


--tag-keys key1,key2

Warning Javascript is disabled or is unavailable in your browser.

To use the Amazon Web Services Documentation, Javascript must be enabled. Please refer to your browser's Help pages for instructions.

Document Conventions

Deleting a model

Describing a model (SDK)