# Use Amazon Augmented AI with Amazon Rekognition
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Amazon Rekognition makes it easy to add image analysis to your applications. The Amazon Rekognition `DetectModerationLabels` API operation is directly integrated with Amazon A2I so that you can easily create a human loop to review unsafe images, such as explicit adult or violent content. You can use `DetectModerationLabels` to configure a human loop using a flow definition ARN. This enables Amazon A2I to analyze predictions made by Amazon Rekognition and send results to a human for review to ensure they meet the conditions set in your flow definition.

The following image depicts the Amazon A2I built-in workflow with Amazon Rekognition. On the left, the resources that are required to create an Amazon Rekognition human review workflow are depicted: and Amazon S3 bucket, activation conditions, a worker task template, and a work team. These resources are used to create a human review workflow, or flow definition. An arrow points right to the next step in the workflow: using Amazon Rekognition to configure a human loop with the human review workflow. A second arrow points right from this step to the step in which activation conditions specified in the human review workflow are met. This initiates the creation of a human loop. On the right of the image, the human loop is depicted in three steps: 1) the worker UI and tools are generated and the task is made available to workers, 2) workers review input data, and finally, 3) results are saved in Amazon S3.

![\[Use Amazon Augmented AI with Amazon Rekognition\]](http://docs.amazonaws.cn/en_us/sagemaker/latest/dg/images/a2i/diagrams/product-page-diagram_A2I-Components_Rekognition@2x.png)


You can set the following activation conditions when using the Amazon Rekognition task type:
+ Initiate human review for labels identified by Amazon Rekognition based on the label confidence score.
+ Randomly send a sample of images to humans for review.

You can set these activation conditions using the Amazon SageMaker AI console when you create a human review workflow, or by creating a JSON for human loop activation conditions and specifying this as input in the `HumanLoopActivationConditions` parameter of the `CreateFlowDefinition` API operation. To learn how specify activation conditions in JSON format, see [JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI](a2i-human-fallback-conditions-json-schema.md) and [Use Human Loop Activation Conditions JSON Schema with Amazon Rekognition](a2i-json-humantaskactivationconditions-rekognition-example.md).

**Note**  
When using Augmented AI with Amazon Rekognition, create Augmented AI resources in the same Amazon Region you use to call `DetectModerationLabels`. 

## Get Started: Integrate a Human Review into an Amazon Rekognition Image Moderation Job
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To integrate a human review into an Amazon Rekognition, see the following topics:
+ [Create a Human Review Workflow (Console)](a2i-create-flow-definition.md#a2i-create-human-review-console)
+ [Create a Human Review Workflow (API)](a2i-create-flow-definition.md#a2i-create-human-review-api)

After you've created your flow definition, see [Using Augmented AI with Amazon Rekognition](https://docs.amazonaws.cn/rekognition/latest/dg/a2i-rekognition.html) to learn how to integrate your flow definition into your Amazon Rekognition task. 

## End-to-end Demo Using Amazon Rekognition and Amazon A2I
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For an end-to-end example that demonstrates how to use Amazon Rekognition with Amazon A2I using the console, see [Tutorial: Get Started in the Amazon A2I Console](a2i-get-started-console.md).

To learn how to use the Amazon A2I API to create and start a human review, you can use [Amazon Augmented AI (Amazon A2I) integration with Amazon Rekognition [Example]](https://github.com/aws-samples/amazon-a2i-sample-jupyter-notebooks/blob/master/Amazon%20Augmented%20AI%20(A2I)%20and%20Rekognition%20DetectModerationLabels.ipynb) in a SageMaker notebook instance. To get started, see [Use SageMaker Notebook Instance with Amazon A2I Jupyter Notebook](a2i-task-types-general.md#a2i-task-types-notebook-demo).

## A2I Rekognition Worker Console Preview
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When they're assigned a review task in an Amazon Rekognition workflow, workers might see a user interface similar to the following:

![\[Example image in the A2I Rekognition worker console.\]](http://docs.amazonaws.cn/en_us/sagemaker/latest/dg/images/a2i-rekognition-example.png)


You can customize this interface in the SageMaker AI console when you create your human review definition, or by creating and using a custom template. To learn more, see [Create and Manage Worker Task Templates](a2i-instructions-overview.md).