与 AWS SDK或DetectModerationLabels一起使用 CLI - AWS SDK 代码示例

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与 AWS SDK或DetectModerationLabels一起使用 CLI

以下代码示例演示如何使用 DetectModerationLabels

有关更多信息,请参阅检测不适宜的图像

.NET
AWS SDK for .NET
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

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 = "amzn-s3-demo-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

检测图像中不安全的内容

以下 detect-moderation-labels 命令将检测存储在 Amazon S3 存储桶中的指定图像中不安全的内容。

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

输出:

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

有关更多信息,请参阅《Amazon Rekognition 开发人员指南》中的检测不安全的图像

Java
SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

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对于 Kotlin 来说
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

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适用于 Python (Boto3)
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

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