Use DetectModerationLabels with an AWS SDK or command line tool - AWS SDK Code Examples

There are more AWS SDK examples available in the AWS Doc SDK Examples GitHub repo.

Use DetectModerationLabels with an AWS SDK or command line tool

The following code examples show how to use DetectModerationLabels.

For more information, see Detecting inappropriate images.

.NET
AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

using System; using System.Threading.Tasks; using Amazon.Rekognition; using Amazon.Rekognition.Model; /// <summary> /// Uses the Amazon Rekognition Service to detect unsafe content in a /// JPEG or PNG format image. /// </summary> public class DetectModerationLabels { public static async Task Main(string[] args) { string photo = "input.jpg"; string bucket = "bucket"; var rekognitionClient = new AmazonRekognitionClient(); var detectModerationLabelsRequest = new DetectModerationLabelsRequest() { Image = new Image() { S3Object = new S3Object() { Name = photo, Bucket = bucket, }, }, MinConfidence = 60F, }; try { var detectModerationLabelsResponse = await rekognitionClient.DetectModerationLabelsAsync(detectModerationLabelsRequest); Console.WriteLine("Detected labels for " + photo); foreach (ModerationLabel label in detectModerationLabelsResponse.ModerationLabels) { Console.WriteLine($"Label: {label.Name}"); Console.WriteLine($"Confidence: {label.Confidence}"); Console.WriteLine($"Parent: {label.ParentName}"); } } catch (Exception ex) { Console.WriteLine(ex.Message); } } }
CLI
AWS CLI

To detect unsafe content in an image

The following detect-moderation-labels command detects unsafe content in the specified image stored in an Amazon S3 bucket.

aws rekognition detect-moderation-labels \ --image "S3Object={Bucket=MyImageS3Bucket,Name=gun.jpg}"

Output:

{ "ModerationModelVersion": "3.0", "ModerationLabels": [ { "Confidence": 97.29618072509766, "ParentName": "Violence", "Name": "Weapon Violence" }, { "Confidence": 97.29618072509766, "ParentName": "", "Name": "Violence" } ] }

For more information, see Detecting Unsafe Images in the Amazon Rekognition Developer Guide.

Java
SDK for Java 2.x
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

import software.amazon.awssdk.core.SdkBytes; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.rekognition.RekognitionClient; import software.amazon.awssdk.services.rekognition.model.RekognitionException; import software.amazon.awssdk.services.rekognition.model.Image; import software.amazon.awssdk.services.rekognition.model.DetectModerationLabelsRequest; import software.amazon.awssdk.services.rekognition.model.DetectModerationLabelsResponse; import software.amazon.awssdk.services.rekognition.model.ModerationLabel; import java.io.FileInputStream; import java.io.FileNotFoundException; import java.io.InputStream; import java.util.List; /** * Before running this Java V2 code example, set up your development * environment, including your credentials. * * For more information, see the following documentation topic: * * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html */ public class DetectModerationLabels { public static void main(String[] args) { final String usage = """ Usage: <sourceImage> Where: sourceImage - The path to the image (for example, C:\\AWS\\pic1.png).\s """; if (args.length < 1) { System.out.println(usage); System.exit(1); } String sourceImage = args[0]; Region region = Region.US_EAST_1; RekognitionClient rekClient = RekognitionClient.builder() .region(region) .build(); detectModLabels(rekClient, sourceImage); rekClient.close(); } public static void detectModLabels(RekognitionClient rekClient, String sourceImage) { try { InputStream sourceStream = new FileInputStream(sourceImage); SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream); Image souImage = Image.builder() .bytes(sourceBytes) .build(); DetectModerationLabelsRequest moderationLabelsRequest = DetectModerationLabelsRequest.builder() .image(souImage) .minConfidence(60F) .build(); DetectModerationLabelsResponse moderationLabelsResponse = rekClient .detectModerationLabels(moderationLabelsRequest); List<ModerationLabel> labels = moderationLabelsResponse.moderationLabels(); System.out.println("Detected labels for image"); for (ModerationLabel label : labels) { System.out.println("Label: " + label.name() + "\n Confidence: " + label.confidence().toString() + "%" + "\n Parent:" + label.parentName()); } } catch (RekognitionException | FileNotFoundException e) { e.printStackTrace(); System.exit(1); } } }
Kotlin
SDK for Kotlin
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

suspend fun detectModLabels(sourceImage: String) { val myImage = Image { this.bytes = (File(sourceImage).readBytes()) } val request = DetectModerationLabelsRequest { image = myImage minConfidence = 60f } RekognitionClient { region = "us-east-1" }.use { rekClient -> val response = rekClient.detectModerationLabels(request) response.moderationLabels?.forEach { label -> println("Label: ${label.name} - Confidence: ${label.confidence} % Parent: ${label.parentName}") } } }
Python
SDK for Python (Boto3)
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

class RekognitionImage: """ Encapsulates an Amazon Rekognition image. This class is a thin wrapper around parts of the Boto3 Amazon Rekognition API. """ def __init__(self, image, image_name, rekognition_client): """ Initializes the image object. :param image: Data that defines the image, either the image bytes or an Amazon S3 bucket and object key. :param image_name: The name of the image. :param rekognition_client: A Boto3 Rekognition client. """ self.image = image self.image_name = image_name self.rekognition_client = rekognition_client def detect_moderation_labels(self): """ Detects moderation labels in the image. Moderation labels identify content that may be inappropriate for some audiences. :return: The list of moderation labels found in the image. """ try: response = self.rekognition_client.detect_moderation_labels( Image=self.image ) labels = [ RekognitionModerationLabel(label) for label in response["ModerationLabels"] ] logger.info( "Found %s moderation labels in %s.", len(labels), self.image_name ) except ClientError: logger.exception( "Couldn't detect moderation labels in %s.", self.image_name ) raise else: return labels