Úselo DetectFaces con un o AWS SDK CLI - AWS SDKEjemplos de código

Hay más AWS SDK ejemplos disponibles en el GitHub repositorio de AWS Doc SDK Examples.

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Úselo DetectFaces con un o AWS SDK CLI

En los siguientes ejemplos de código se muestra cómo se utiliza DetectFaces.

Para obtener información, consulte Detección de rostros en una imagen.

.NET
AWS SDK for .NET
nota

Hay más en marcha GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS.

using System; using System.Collections.Generic; using System.Threading.Tasks; using Amazon.Rekognition; using Amazon.Rekognition.Model; /// <summary> /// Uses the Amazon Rekognition Service to detect faces within an image /// stored in an Amazon Simple Storage Service (Amazon S3) bucket. /// </summary> public class DetectFaces { public static async Task Main() { string photo = "input.jpg"; string bucket = "amzn-s3-demo-bucket"; var rekognitionClient = new AmazonRekognitionClient(); var detectFacesRequest = new DetectFacesRequest() { Image = new Image() { S3Object = new S3Object() { Name = photo, Bucket = bucket, }, }, // Attributes can be "ALL" or "DEFAULT". // "DEFAULT": BoundingBox, Confidence, Landmarks, Pose, and Quality. // "ALL": See https://docs.aws.amazon.com/sdkfornet/v3/apidocs/items/Rekognition/TFaceDetail.html Attributes = new List<string>() { "ALL" }, }; try { DetectFacesResponse detectFacesResponse = await rekognitionClient.DetectFacesAsync(detectFacesRequest); bool hasAll = detectFacesRequest.Attributes.Contains("ALL"); foreach (FaceDetail face in detectFacesResponse.FaceDetails) { Console.WriteLine($"BoundingBox: top={face.BoundingBox.Left} left={face.BoundingBox.Top} width={face.BoundingBox.Width} height={face.BoundingBox.Height}"); Console.WriteLine($"Confidence: {face.Confidence}"); Console.WriteLine($"Landmarks: {face.Landmarks.Count}"); Console.WriteLine($"Pose: pitch={face.Pose.Pitch} roll={face.Pose.Roll} yaw={face.Pose.Yaw}"); Console.WriteLine($"Brightness: {face.Quality.Brightness}\tSharpness: {face.Quality.Sharpness}"); if (hasAll) { Console.WriteLine($"Estimated age is between {face.AgeRange.Low} and {face.AgeRange.High} years old."); } } } catch (Exception ex) { Console.WriteLine(ex.Message); } } }

Visualizar información del cuadro delimitador de todos los rostros en una imagen.

using System; using System.Collections.Generic; using System.Drawing; using System.IO; using System.Threading.Tasks; using Amazon.Rekognition; using Amazon.Rekognition.Model; /// <summary> /// Uses the Amazon Rekognition Service to display the details of the /// bounding boxes around the faces detected in an image. /// </summary> public class ImageOrientationBoundingBox { public static async Task Main() { string photo = @"D:\Development\AWS-Examples\Rekognition\target.jpg"; // "photo.jpg"; var rekognitionClient = new AmazonRekognitionClient(); var image = new Amazon.Rekognition.Model.Image(); try { using var fs = new FileStream(photo, FileMode.Open, FileAccess.Read); byte[] data = null; data = new byte[fs.Length]; fs.Read(data, 0, (int)fs.Length); image.Bytes = new MemoryStream(data); } catch (Exception) { Console.WriteLine("Failed to load file " + photo); return; } int height; int width; // Used to extract original photo width/height using (var imageBitmap = new Bitmap(photo)) { height = imageBitmap.Height; width = imageBitmap.Width; } Console.WriteLine("Image Information:"); Console.WriteLine(photo); Console.WriteLine("Image Height: " + height); Console.WriteLine("Image Width: " + width); try { var detectFacesRequest = new DetectFacesRequest() { Image = image, Attributes = new List<string>() { "ALL" }, }; DetectFacesResponse detectFacesResponse = await rekognitionClient.DetectFacesAsync(detectFacesRequest); detectFacesResponse.FaceDetails.ForEach(face => { Console.WriteLine("Face:"); ShowBoundingBoxPositions( height, width, face.BoundingBox, detectFacesResponse.OrientationCorrection); Console.WriteLine($"BoundingBox: top={face.BoundingBox.Left} left={face.BoundingBox.Top} width={face.BoundingBox.Width} height={face.BoundingBox.Height}"); Console.WriteLine($"The detected face is estimated to be between {face.AgeRange.Low} and {face.AgeRange.High} years old.\n"); }); } catch (Exception ex) { Console.WriteLine(ex.Message); } } /// <summary> /// Display the bounding box information for an image. /// </summary> /// <param name="imageHeight">The height of the image.</param> /// <param name="imageWidth">The width of the image.</param> /// <param name="box">The bounding box for a face found within the image.</param> /// <param name="rotation">The rotation of the face's bounding box.</param> public static void ShowBoundingBoxPositions(int imageHeight, int imageWidth, BoundingBox box, string rotation) { float left; float top; if (rotation == null) { Console.WriteLine("No estimated orientation. Check Exif data."); return; } // Calculate face position based on image orientation. switch (rotation) { case "ROTATE_0": left = imageWidth * box.Left; top = imageHeight * box.Top; break; case "ROTATE_90": left = imageHeight * (1 - (box.Top + box.Height)); top = imageWidth * box.Left; break; case "ROTATE_180": left = imageWidth - (imageWidth * (box.Left + box.Width)); top = imageHeight * (1 - (box.Top + box.Height)); break; case "ROTATE_270": left = imageHeight * box.Top; top = imageWidth * (1 - box.Left - box.Width); break; default: Console.WriteLine("No estimated orientation information. Check Exif data."); return; } // Display face location information. Console.WriteLine($"Left: {left}"); Console.WriteLine($"Top: {top}"); Console.WriteLine($"Face Width: {imageWidth * box.Width}"); Console.WriteLine($"Face Height: {imageHeight * box.Height}"); } }
  • Para API obtener más información, consulte DetectFacesla AWS SDK for .NET APIReferencia.

CLI
AWS CLI

Detección de rostros en una imagen

El siguiente comando detect-faces detecta rostros en la imagen especificada almacenada en un bucket de Amazon S3.

aws rekognition detect-faces \ --image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"MyFriend.jpg"}}' \ --attributes "ALL"

Salida:

{ "FaceDetails": [ { "Confidence": 100.0, "Eyeglasses": { "Confidence": 98.91107940673828, "Value": false }, "Sunglasses": { "Confidence": 99.7966537475586, "Value": false }, "Gender": { "Confidence": 99.56611633300781, "Value": "Male" }, "Landmarks": [ { "Y": 0.26721030473709106, "X": 0.6204193830490112, "Type": "eyeLeft" }, { "Y": 0.26831310987472534, "X": 0.6776827573776245, "Type": "eyeRight" }, { "Y": 0.3514654338359833, "X": 0.6241428852081299, "Type": "mouthLeft" }, { "Y": 0.35258132219314575, "X": 0.6713621020317078, "Type": "mouthRight" }, { "Y": 0.3140771687030792, "X": 0.6428444981575012, "Type": "nose" }, { "Y": 0.24662546813488007, "X": 0.6001564860343933, "Type": "leftEyeBrowLeft" }, { "Y": 0.24326619505882263, "X": 0.6303644776344299, "Type": "leftEyeBrowRight" }, { "Y": 0.23818562924861908, "X": 0.6146903038024902, "Type": "leftEyeBrowUp" }, { "Y": 0.24373626708984375, "X": 0.6640064716339111, "Type": "rightEyeBrowLeft" }, { "Y": 0.24877218902111053, "X": 0.7025929093360901, "Type": "rightEyeBrowRight" }, { "Y": 0.23938551545143127, "X": 0.6823262572288513, "Type": "rightEyeBrowUp" }, { "Y": 0.265746533870697, "X": 0.6112898588180542, "Type": "leftEyeLeft" }, { "Y": 0.2676128149032593, "X": 0.6317071914672852, "Type": "leftEyeRight" }, { "Y": 0.262735515832901, "X": 0.6201658248901367, "Type": "leftEyeUp" }, { "Y": 0.27025148272514343, "X": 0.6206279993057251, "Type": "leftEyeDown" }, { "Y": 0.268223375082016, "X": 0.6658390760421753, "Type": "rightEyeLeft" }, { "Y": 0.2672517001628876, "X": 0.687832236289978, "Type": "rightEyeRight" }, { "Y": 0.26383838057518005, "X": 0.6769183874130249, "Type": "rightEyeUp" }, { "Y": 0.27138751745224, "X": 0.676596462726593, "Type": "rightEyeDown" }, { "Y": 0.32283174991607666, "X": 0.6350004076957703, "Type": "noseLeft" }, { "Y": 0.3219289481639862, "X": 0.6567046642303467, "Type": "noseRight" }, { "Y": 0.3420318365097046, "X": 0.6450609564781189, "Type": "mouthUp" }, { "Y": 0.3664324879646301, "X": 0.6455618143081665, "Type": "mouthDown" }, { "Y": 0.26721030473709106, "X": 0.6204193830490112, "Type": "leftPupil" }, { "Y": 0.26831310987472534, "X": 0.6776827573776245, "Type": "rightPupil" }, { "Y": 0.26343393325805664, "X": 0.5946047306060791, "Type": "upperJawlineLeft" }, { "Y": 0.3543180525302887, "X": 0.6044883728027344, "Type": "midJawlineLeft" }, { "Y": 0.4084877669811249, "X": 0.6477024555206299, "Type": "chinBottom" }, { "Y": 0.3562754988670349, "X": 0.707981526851654, "Type": "midJawlineRight" }, { "Y": 0.26580461859703064, "X": 0.7234612107276917, "Type": "upperJawlineRight" } ], "Pose": { "Yaw": -3.7351467609405518, "Roll": -0.10309021919965744, "Pitch": 0.8637830018997192 }, "Emotions": [ { "Confidence": 8.74203109741211, "Type": "SURPRISED" }, { "Confidence": 2.501944065093994, "Type": "ANGRY" }, { "Confidence": 0.7378743290901184, "Type": "DISGUSTED" }, { "Confidence": 3.5296201705932617, "Type": "HAPPY" }, { "Confidence": 1.7162904739379883, "Type": "SAD" }, { "Confidence": 9.518536567687988, "Type": "CONFUSED" }, { "Confidence": 0.45474427938461304, "Type": "FEAR" }, { "Confidence": 72.79895782470703, "Type": "CALM" } ], "AgeRange": { "High": 48, "Low": 32 }, "EyesOpen": { "Confidence": 98.93987274169922, "Value": true }, "BoundingBox": { "Width": 0.12368916720151901, "Top": 0.16007372736930847, "Left": 0.5901257991790771, "Height": 0.25140416622161865 }, "Smile": { "Confidence": 93.4493179321289, "Value": false }, "MouthOpen": { "Confidence": 90.53053283691406, "Value": false }, "Quality": { "Sharpness": 95.51618957519531, "Brightness": 65.29893493652344 }, "Mustache": { "Confidence": 89.85221099853516, "Value": false }, "Beard": { "Confidence": 86.1991195678711, "Value": true } } ] }

Para obtener más información, consulte Detección de rostros en una imagen en la Guía para desarrolladores de Amazon Rekognition.

  • Para API obtener más información, consulte DetectFacesla Referencia de AWS CLI comandos.

Java
SDKpara Java 2.x
nota

Hay más información. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS.

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.DetectFacesRequest; import software.amazon.awssdk.services.rekognition.model.DetectFacesResponse; import software.amazon.awssdk.services.rekognition.model.Image; import software.amazon.awssdk.services.rekognition.model.Attribute; import software.amazon.awssdk.services.rekognition.model.FaceDetail; import software.amazon.awssdk.services.rekognition.model.AgeRange; import software.amazon.awssdk.core.SdkBytes; 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 DetectFaces { 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(); detectFacesinImage(rekClient, sourceImage); rekClient.close(); } public static void detectFacesinImage(RekognitionClient rekClient, String sourceImage) { try { InputStream sourceStream = new FileInputStream(sourceImage); SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream); // Create an Image object for the source image. Image souImage = Image.builder() .bytes(sourceBytes) .build(); DetectFacesRequest facesRequest = DetectFacesRequest.builder() .attributes(Attribute.ALL) .image(souImage) .build(); DetectFacesResponse facesResponse = rekClient.detectFaces(facesRequest); List<FaceDetail> faceDetails = facesResponse.faceDetails(); for (FaceDetail face : faceDetails) { AgeRange ageRange = face.ageRange(); System.out.println("The detected face is estimated to be between " + ageRange.low().toString() + " and " + ageRange.high().toString() + " years old."); System.out.println("There is a smile : " + face.smile().value().toString()); } } catch (RekognitionException | FileNotFoundException e) { System.out.println(e.getMessage()); System.exit(1); } } }
  • Para API obtener más información, consulte DetectFacesla AWS SDK for Java 2.x APIReferencia.

Kotlin
SDKpara Kotlin
nota

Hay más información. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS.

suspend fun detectFacesinImage(sourceImage: String?) { val souImage = Image { bytes = (File(sourceImage).readBytes()) } val request = DetectFacesRequest { attributes = listOf(Attribute.All) image = souImage } RekognitionClient { region = "us-east-1" }.use { rekClient -> val response = rekClient.detectFaces(request) response.faceDetails?.forEach { face -> val ageRange = face.ageRange println("The detected face is estimated to be between ${ageRange?.low} and ${ageRange?.high} years old.") println("There is a smile ${face.smile?.value}") } } }
  • Para API obtener más información, consulta DetectFacesla AWS SDKAPIreferencia sobre Kotlin.

Python
SDKpara Python (Boto3)
nota

Hay más información. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS.

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_faces(self): """ Detects faces in the image. :return: The list of faces found in the image. """ try: response = self.rekognition_client.detect_faces( Image=self.image, Attributes=["ALL"] ) faces = [RekognitionFace(face) for face in response["FaceDetails"]] logger.info("Detected %s faces.", len(faces)) except ClientError: logger.exception("Couldn't detect faces in %s.", self.image_name) raise else: return faces
  • Para API obtener más información, consulte DetectFacesla AWS SDKreferencia de Python (Boto3). API