# 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](https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html).
Use tags to:
+ Track billing for a model by using cost allocation tags. For more information, see [Using Cost Allocation Tags](https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html).
+ Control access to a model by using Identity and Access Management (IAM). For more information, see [Controlling access to AWS resources using resource tags](https://docs.aws.amazon.com/IAM/latest/UserGuide/access_tags.html).
+ 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](running-model.md).
You can tag models by using the Amazon Rekognition console or by using the AWS SDKs.
**Topics**
+ [Tagging models (console)](#tm-tagging-model-console)
+ [Viewing model tags](#tm-tagging-model-viewing-console)
+ [Tagging models (SDK)](#tm-tagging-model-sdk)
## 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](training-model.md).
**To add tags to, or remove tags from, an existing model using the console**
1. Open the Amazon Rekognition console at [ https://console.aws.amazon.com/rekognition/]( https://console.aws.amazon.com/rekognition/).
1. Choose **Get started**.
1. In the navigation pane, choose **Projects**.
1. On the **Projects** resources page, choose the project that contains the model that you want to tag.
1. In the navigation pane, under the project you previously chose, choose **Models**.
1. In the **Models** section, choose the model that you want to add a tag to.
1. On the model's details page, choose the **Tags** tab.
1. In the **Tags** section, choose **Manage tags**.
1. On the **Manage tags** page, choose **Add new tag**.
1. Enter a key and a value.
1. For **Key**, enter a name for the key.
1. For **Value**, enter a value.
1. To add more tags, repeat steps 9 and 10.
1. (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.
1. 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](#listing-model-tags-sdk).
**To view the tags attached to a model**
1. Open the Amazon Rekognition console at [ https://console.aws.amazon.com/rekognition/]( https://console.aws.amazon.com/rekognition/).
1. Choose **Get started**.
1. In the navigation pane, choose **Projects**.
1. On the **Projects** resources page, choose the project that contains the model whose tag you want to view.
1. In the navigation pane, under the project you previously chose, choose **Models**.
1. In the **Models** section, choose the model whose tag you want to view.
1. 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](su-awscli-sdk.md).
### Adding tags to a new model
You can add tags to a model when you create it using the [CreateProjectVersion](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_CreateProjectVersion.html) 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)](training-model.md#tm-sdk).
### Adding tags to an existing model
To add one or more tags to an existing model, use the [TagResource](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_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](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_CreateProjectVersion).
### Listing model tags
To list the tags attached to a model, use the [ListTagsForResource](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_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**
1. 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()
```
1. 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](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_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
```