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Gunakan DetectFaces dengan AWS SDK atau CLI

Mode fokus
Gunakan DetectFaces dengan AWS SDK atau CLI - Amazon Rekognition

Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.

Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.

Contoh kode berikut menunjukkan cara menggunakanDetectFaces.

Untuk informasi selengkapnya, lihat Mendeteksi wajah dalam gambar.

.NET
SDK for .NET
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode 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); } } }

Menampilkan informasi kotak pembatas untuk semua wajah dalam gambar.

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}"); } }
  • Untuk detail API, lihat DetectFacesdi Referensi AWS SDK for .NET API.

CLI
AWS CLI

Untuk mendeteksi wajah dalam gambar

detect-facesPerintah berikut mendeteksi wajah dalam gambar tertentu yang disimpan dalam bucket Amazon S3.

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

Output:

{ "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 } } ] }

Untuk informasi selengkapnya, lihat Mendeteksi Wajah dalam Gambar di Panduan Pengembang Rekognition Amazon.

  • Untuk detail API, lihat DetectFacesdi Referensi AWS CLI Perintah.

Java
SDK untuk Java 2.x
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode 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); } } }
  • Untuk detail API, lihat DetectFacesdi Referensi AWS SDK for Java 2.x API.

Kotlin
SDK untuk Kotlin
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode 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}") } } }
  • Untuk detail API, lihat DetectFacesdi AWS SDK untuk referensi API Kotlin.

Python
SDK untuk Python (Boto3)
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode 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
  • Untuk detail API, lihat DetectFacesdi AWS SDK for Python (Boto3) Referensi API.

SDK for .NET
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode 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); } } }

Menampilkan informasi kotak pembatas untuk semua wajah dalam gambar.

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}"); } }
  • Untuk detail API, lihat DetectFacesdi Referensi AWS SDK for .NET API.

Untuk daftar lengkap panduan pengembang AWS SDK dan contoh kode, lihatMenggunakan Rekognition dengan SDK AWS. Topik ini juga mencakup informasi tentang memulai dan detail tentang versi SDK sebelumnya.

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