Contoh: Menggambar kotak pembatas di sekitar penutup wajah

Contoh berikut menunjukkan cara menggambar kotak pembatas di sekitar penutup wajah yang terdeteksi pada orang. Untuk contoh yang menggunakan AWS Lambda dan Amazon DynamoDB, lihat AWS repositori contoh SDK Documentation. GitHub

Untuk mendeteksi penutup wajah Anda menggunakan operasi API non-penyimpanan DetectProtectiveEquipment. Citra dimuat dari sistem file lokal. Anda memberikan citra input ke DetectProtectiveEquipment sebagai array bit citra (bit citra yang dikodekan base64). Untuk informasi selengkapnya, lihat Bekerja dengan citra.

Contoh ini menampilkan kotak pembatas di sekitar penutup wajah yang terdeteksi. Kotak pembatas berwarna hijau jika penutup wajah menutupi bagian tubuh sepenuhnya. Jika tidak, kotak pembatas merah ditampilkan. Sebagai peringatan, kotak pembatas kuning ditampilkan dalam kotak pembatas penutup wajah, jika kepercayaan pendeteksian kurang dari nilai kepercayaan yang ditentukan. Jika penutup wajah tidak terdeteksi, maka kotak pembatas merah dicitra di sekitar orang tersebut.

Output citra tersebut mirip dengan hal berikut.

Empat pekerja di sebuah gudang, mengenakan rompi visibilitas tinggi, helm, kacamata keselamatan, dan masker. Topeng dikelilingi oleh kotak pembatas.

Untuk menampilkan kotak pembatas pada penutup wajah yang terdeteksi

Jika belum:
1. Buat atau perbarui pengguna dengan AmazonRekognitionFullAccess izin. Untuk informasi selengkapnya, lihat Langkah 1: Siapkan akun AWS dan buat Pengguna.
2. Instal dan konfigurasikan AWS CLI dan AWS SDKs. Untuk informasi selengkapnya, lihat Langkah 2: Mengatur AWS CLI dan AWS SDKs.

Gunakan contoh berikut untuk memanggil operasi DetectProtectiveEquipment. Untuk informasi tentang menampilkan kotak pembatas di citra, lihat Menampilkan kotak pembatas.

Java

Dalam fungsi main, ubah hal berikut:

Nilai photo ke jalur dan nama file citra lokal (PNG atau JPEG).
Nilai confidence sampai dengan tingkat kepercayaan yang diinginkan (50-100).



//Loads images, detects faces and draws bounding boxes.Determines exif orientation, if necessary.
package com.amazonaws.samples;


import java.awt.*;
import java.awt.image.BufferedImage;
import java.util.List;
import javax.imageio.ImageIO;
import javax.swing.*;

import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.nio.ByteBuffer;
import com.amazonaws.util.IOUtils;

import com.amazonaws.client.builder.AwsClientBuilder;
import com.amazonaws.services.rekognition.AmazonRekognition;
import com.amazonaws.services.rekognition.AmazonRekognitionClientBuilder;
import com.amazonaws.services.rekognition.model.BoundingBox;
import com.amazonaws.services.rekognition.model.DetectProtectiveEquipmentRequest;
import com.amazonaws.services.rekognition.model.DetectProtectiveEquipmentResult;
import com.amazonaws.services.rekognition.model.EquipmentDetection;
import com.amazonaws.services.rekognition.model.Image;
import com.amazonaws.services.rekognition.model.ProtectiveEquipmentBodyPart;
import com.amazonaws.services.rekognition.model.ProtectiveEquipmentPerson;

// Calls DetectFaces and displays a bounding box around each detected image.
public class PPEBoundingBox extends JPanel {

    private static final long serialVersionUID = 1L;

    BufferedImage image;
    static int scale;
    DetectProtectiveEquipmentResult result;
    float confidence=80;

    public PPEBoundingBox(DetectProtectiveEquipmentResult ppeResult, BufferedImage bufImage, float requiredConfidence) throws Exception {
        super();
        scale = 2; // increase to shrink image size.

        result = ppeResult;
        image = bufImage;
        
        confidence=requiredConfidence;
    }
    // Draws the bounding box around the detected faces.
    public void paintComponent(Graphics g) {
        float left = 0;
        float top = 0;
        int height = image.getHeight(this);
        int width = image.getWidth(this);
        int offset=20;

        Graphics2D g2d = (Graphics2D) g; // Create a Java2D version of g.

        // Draw the image.
        g2d.drawImage(image, 0, 0, width / scale, height / scale, this);
        g2d.setColor(new Color(0, 212, 0));

        // Iterate through detected persons and display bounding boxes.
        List<ProtectiveEquipmentPerson> persons = result.getPersons();

        for (ProtectiveEquipmentPerson person: persons) {
            BoundingBox boxPerson = person.getBoundingBox();
            left = width * boxPerson.getLeft();
            top = height * boxPerson.getTop();
            Boolean foundMask=false;

            List<ProtectiveEquipmentBodyPart> bodyParts=person.getBodyParts();
            
            if (bodyParts.isEmpty()==false)
             {
                    //body parts detected

                    for (ProtectiveEquipmentBodyPart bodyPart: bodyParts) {

                        List<EquipmentDetection> equipmentDetections=bodyPart.getEquipmentDetections();

                        for (EquipmentDetection item: equipmentDetections) {

                            if (item.getType().contentEquals("FACE_COVER"))
                            {
                                // Draw green or red bounding box depending on mask coverage.
                                foundMask=true;
                                BoundingBox box =item.getBoundingBox();
                                left = width * box.getLeft();
                                top = height * box.getTop();
                                Color maskColor=new Color( 0, 212, 0);

                                if (item.getCoversBodyPart().getValue()==false) {
                                    // red bounding box
                                    maskColor=new Color( 255, 0, 0);
                                }
                                g2d.setColor(maskColor);
                                g2d.drawRect(Math.round(left / scale), Math.round(top / scale),
                                        Math.round((width * box.getWidth()) / scale), Math.round((height * box.getHeight())) / scale);
                                
                                // Check confidence is > supplied confidence.
                                if (item.getCoversBodyPart().getConfidence()< confidence)
                                {
                                    // Draw a yellow bounding box inside face mask bounding box 
                                    maskColor=new Color( 255, 255, 0);
                                    g2d.setColor(maskColor);
                                    g2d.drawRect(Math.round((left + offset) / scale),
                                             Math.round((top + offset) / scale),
                                             Math.round((width * box.getWidth())- (offset * 2 ))/ scale,
                                             Math.round((height * box.getHeight()) -( offset* 2)) / scale);
                                }

                            }
                        }

                    }

                } 

            // Didn't find a mask, so draw person bounding box red
            if (foundMask==false) {

                left = width * boxPerson.getLeft();
                top = height * boxPerson.getTop();
                g2d.setColor(new Color(255, 0, 0));
                g2d.drawRect(Math.round(left / scale), Math.round(top / scale),
                        Math.round(((width) * boxPerson.getWidth()) / scale), Math.round((height * boxPerson.getHeight())) / scale);
            }
         }  
         
    }


    public static void main(String arg[]) throws Exception {

        String photo = "photo";
        
        float confidence =80;

  
        int height = 0;
        int width = 0;

        BufferedImage image = null;
        ByteBuffer imageBytes;
        
        // Get image bytes for call to DetectProtectiveEquipment
        try (InputStream inputStream = new FileInputStream(new File(photo))) {
            imageBytes = ByteBuffer.wrap(IOUtils.toByteArray(inputStream));
        }
        
        //Get image for display
        InputStream imageBytesStream;
        imageBytesStream = new ByteArrayInputStream(imageBytes.array());

        ByteArrayOutputStream baos = new ByteArrayOutputStream();
        image=ImageIO.read(imageBytesStream);
        ImageIO.write(image, "jpg", baos);
        width = image.getWidth();
        height = image.getHeight();
 
        //Get Rekognition client
        AmazonRekognition rekognitionClient = AmazonRekognitionClientBuilder.defaultClient();
        
       
        // Call DetectProtectiveEquipment
        DetectProtectiveEquipmentRequest request = new DetectProtectiveEquipmentRequest()
                .withImage(new Image()
                        .withBytes(imageBytes));

        DetectProtectiveEquipmentResult result = rekognitionClient.detectProtectiveEquipment(request);


        // Create frame and panel.
        JFrame frame = new JFrame("Detect PPE");
        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        PPEBoundingBox panel = new PPEBoundingBox(result, image, confidence);
        panel.setPreferredSize(new Dimension(image.getWidth() / scale, image.getHeight() / scale));
        frame.setContentPane(panel);
        frame.pack();
        frame.setVisible(true);

    }
}

Java V2

Kode ini diambil dari GitHub repositori contoh SDK AWS Dokumentasi. Lihat contoh lengkapnya di sini.


import java.awt.*;
import java.awt.image.BufferedImage;
import java.io.*;
import java.util.List;
import javax.imageio.ImageIO;
import javax.swing.*;
import software.amazon.awssdk.auth.credentials.ProfileCredentialsProvider;
import software.amazon.awssdk.core.ResponseBytes;
import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.model.BoundingBox;
import software.amazon.awssdk.services.rekognition.model.DetectProtectiveEquipmentRequest;
import software.amazon.awssdk.services.rekognition.model.EquipmentDetection;
import software.amazon.awssdk.services.rekognition.model.ProtectiveEquipmentBodyPart;
import software.amazon.awssdk.services.rekognition.model.ProtectiveEquipmentPerson;
import software.amazon.awssdk.services.rekognition.model.ProtectiveEquipmentSummarizationAttributes;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.s3.S3Client;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.s3.model.GetObjectRequest;
import software.amazon.awssdk.services.s3.model.GetObjectResponse;
import software.amazon.awssdk.services.s3.model.S3Exception;
import software.amazon.awssdk.services.rekognition.model.DetectProtectiveEquipmentResponse;
//snippet-end:[rekognition.java2.display_mask.import]

/**
* 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 PPEBoundingBoxFrame extends JPanel {

 DetectProtectiveEquipmentResponse result;
 static BufferedImage image;
 static int scale;
 float confidence;

 public static void main(String[] args) throws Exception {

     final String usage = "\n" +
         "Usage: " +
         "   <sourceImage> <bucketName>\n\n" +
         "Where:\n" +
         "   sourceImage - The name of the image in an Amazon S3 bucket that shows a person wearing a mask (for example, masks.png). \n\n" +
         "   bucketName - The name of the Amazon S3 bucket (for example, amzn-s3-demo-bucket). \n\n";

     if (args.length != 2) {
         System.out.println(usage);
         System.exit(1);
     }

     String sourceImage = args[0];
     String bucketName = args[1];
     Region region = Region.US_EAST_1;
     S3Client s3 = S3Client.builder()
         .region(region)
         .credentialsProvider(ProfileCredentialsProvider.create("profile-name"))
         .build();

     RekognitionClient rekClient = RekognitionClient.builder()
         .region(region)
         .credentialsProvider(ProfileCredentialsProvider.create("profile-name"))
         .build();

     displayGear(s3, rekClient, sourceImage, bucketName);
     s3.close();
     rekClient.close();
 }

 // snippet-start:[rekognition.java2.display_mask.main]
public static void displayGear(S3Client s3,
                                    RekognitionClient rekClient,
                                    String sourceImage,
                                    String bucketName) {
    float confidence = 80;
    byte[] data = getObjectBytes(s3, bucketName, sourceImage);
    InputStream is = new ByteArrayInputStream(data);

    try {
        ProtectiveEquipmentSummarizationAttributes summarizationAttributes = ProtectiveEquipmentSummarizationAttributes.builder()
            .minConfidence(70F)
            .requiredEquipmentTypesWithStrings("FACE_COVER")
            .build();

        SdkBytes sourceBytes = SdkBytes.fromInputStream(is);
        image = ImageIO.read(sourceBytes.asInputStream());

        // Create an Image object for the source image.
        software.amazon.awssdk.services.rekognition.model.Image souImage = Image.builder()
            .bytes(sourceBytes)
            .build();

        DetectProtectiveEquipmentRequest request = DetectProtectiveEquipmentRequest.builder()
            .image(souImage)
            .summarizationAttributes(summarizationAttributes)
            .build();

        DetectProtectiveEquipmentResponse result = rekClient.detectProtectiveEquipment(request);
        JFrame frame = new JFrame("Detect PPE");
        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        PPEBoundingBoxFrame panel = new PPEBoundingBoxFrame(result, image, confidence);
        panel.setPreferredSize(new Dimension(image.getWidth() / scale, image.getHeight() / scale));
        frame.setContentPane(panel);
        frame.pack();
        frame.setVisible(true);

    } catch (RekognitionException e) {
        e.printStackTrace();
        System.exit(1);
    } catch (Exception e) {
        e.printStackTrace();
    }
}

 public static byte[] getObjectBytes (S3Client s3, String bucketName, String keyName) {

     try {
         GetObjectRequest objectRequest = GetObjectRequest
             .builder()
             .key(keyName)
             .bucket(bucketName)
             .build();

         ResponseBytes<GetObjectResponse> objectBytes = s3.getObjectAsBytes(objectRequest);
         return objectBytes.asByteArray();

     } catch (S3Exception e) {
         System.err.println(e.awsErrorDetails().errorMessage());
         System.exit(1);
     }
     return null;
  }

 public PPEBoundingBoxFrame(DetectProtectiveEquipmentResponse ppeResult, BufferedImage bufImage, float requiredConfidence) {
     super();
     scale = 1; // increase to shrink image size.
     result = ppeResult;
     image = bufImage;
     confidence=requiredConfidence;
 }

 // Draws the bounding box around the detected masks.
 public void paintComponent(Graphics g) {
     float left = 0;
     float top = 0;
     int height = image.getHeight(this);
     int width = image.getWidth(this);
     int offset=20;

     Graphics2D g2d = (Graphics2D) g; // Create a Java2D version of g.

     // Draw the image.
     g2d.drawImage(image, 0, 0, width / scale, height / scale, this);
     g2d.setColor(new Color(0, 212, 0));

     // Iterate through detected persons and display bounding boxes.
     List<ProtectiveEquipmentPerson> persons = result.persons();
     for (ProtectiveEquipmentPerson person: persons) {

         List<ProtectiveEquipmentBodyPart> bodyParts=person.bodyParts();
         if (!bodyParts.isEmpty()){
             for (ProtectiveEquipmentBodyPart bodyPart: bodyParts) {
                 List<EquipmentDetection> equipmentDetections=bodyPart.equipmentDetections();
                 for (EquipmentDetection item: equipmentDetections) {

                     String myType = item.type().toString();
                     if (myType.compareTo("FACE_COVER") ==0) {

                         // Draw green bounding box depending on mask coverage.
                         BoundingBox box =item.boundingBox();
                         left = width * box.left();
                         top = height * box.top();
                         Color maskColor=new Color( 0, 212, 0);

                         if (item.coversBodyPart().equals(false)) {
                             // red bounding box.
                             maskColor=new Color( 255, 0, 0);
                         }
                         g2d.setColor(maskColor);
                         g2d.drawRect(Math.round(left / scale), Math.round(top / scale),
                                 Math.round((width * box.width()) / scale), Math.round((height * box.height())) / scale);

                         // Check confidence is > supplied confidence.
                         if (item.coversBodyPart().confidence() < confidence) {
                             // Draw a yellow bounding box inside face mask bounding box.
                             maskColor=new Color( 255, 255, 0);
                             g2d.setColor(maskColor);
                             g2d.drawRect(Math.round((left + offset) / scale),
                                     Math.round((top + offset) / scale),
                                     Math.round((width * box.width())- (offset * 2 ))/ scale,
                                     Math.round((height * box.height()) -( offset* 2)) / scale);
                         }
                     }
                 }
             }
         }
    }
 }
 // snippet-end:[rekognition.java2.display_mask.main]
}

Python

Dalam fungsi main, ubah hal berikut:

Nilai photo ke jalur dan nama file citra lokal (PNG atau JPEG).
Nilai confidence sampai dengan tingkat kepercayaan yang diinginkan (50-100).
Ganti nilai profile_name di baris yang membuat sesi Rekognition dengan nama profil pengembang Anda.


#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)

import boto3
import io
from PIL import Image, ImageDraw, ExifTags, ImageColor

def detect_ppe(photo, confidence):

    fill_green='#00d400'
    fill_red='#ff0000'
    fill_yellow='#ffff00'
    line_width=3

    #open image and get image data from stream.
    image = Image.open(open(photo,'rb'))
    stream = io.BytesIO()
    image.save(stream, format=image.format)    
    image_binary = stream.getvalue()
    imgWidth, imgHeight = image.size  
    draw = ImageDraw.Draw(image)  

    client=boto3.client('rekognition')

    response = client.detect_protective_equipment(Image={'Bytes': image_binary})

    for person in response['Persons']:
        
        found_mask=False

        for body_part in person['BodyParts']:
            ppe_items = body_part['EquipmentDetections']
                 
            for ppe_item in ppe_items:
                #found a mask 
                if ppe_item['Type'] == 'FACE_COVER':
                    fill_color=fill_green
                    found_mask=True
                    # check if mask covers face
                    if ppe_item['CoversBodyPart']['Value'] == False:
                        fill_color=fill='#ff0000'
                    # draw bounding box around mask
                    box = ppe_item['BoundingBox']
                    left = imgWidth * box['Left']
                    top = imgHeight * box['Top']
                    width = imgWidth * box['Width']
                    height = imgHeight * box['Height']
                    points = (
                            (left,top),
                            (left + width, top),
                            (left + width, top + height),
                            (left , top + height),
                            (left, top)
                        )
                    draw.line(points, fill=fill_color, width=line_width)

                     # Check if confidence is lower than supplied value       
                    if ppe_item['CoversBodyPart']['Confidence'] < confidence:
                        #draw warning yellow bounding box within face mask bounding box
                        offset=line_width+ line_width 
                        points = (
                                    (left+offset,top + offset),
                                    (left + width-offset, top+offset),
                                    ((left) + (width-offset), (top-offset) + (height)),
                                    (left+ offset , (top) + (height -offset)),
                                    (left + offset, top + offset)
                                )
                        draw.line(points, fill=fill_yellow, width=line_width)
                
        if found_mask==False:
            # no face mask found so draw red bounding box around body
            box = person['BoundingBox']
            left = imgWidth * box['Left']
            top = imgHeight * box['Top']
            width = imgWidth * box['Width']
            height = imgHeight * box['Height']
            points = (
                (left,top),
                (left + width, top),
                (left + width, top + height),
                (left , top + height),
                (left, top)
                )
            draw.line(points, fill=fill_red, width=line_width)

    image.show()

def main():
    photo='photo'
    confidence=80
    detect_ppe(photo, confidence)

if __name__ == "__main__":
    main()

CLI

Dalam contoh CLI berikut mengubah nilai argumen yang tercantum di bawah ini:

Nilai photo ke jalur dan nama file citra lokal (PNG atau JPEG).
Nilai confidence sampai dengan tingkat kepercayaan yang diinginkan (50-100).
Ganti nilai profile_name di baris yang membuat sesi Rekognition dengan nama profil pengembang Anda.



                                aws rekognition detect-protective-equipment  --image "{"S3Object":{"Bucket":"amzn-s3-demo-bucket","Name":"image-name"}}" --profile profile-name \ 
                                --summarization-attributes "{"MinConfidence":MinConfidenceNumber,"RequiredEquipmentTypes":["FACE_COVER"]}"

Jika Anda mengakses CLI pada perangkat Windows, gunakan tanda kutip ganda alih-alih tanda kutip tunggal dan hindari tanda kutip ganda bagian dalam dengan garis miring terbalik (yaitu\) untuk mengatasi kesalahan parser yang mungkin Anda temui. Sebagai contoh, lihat berikut ini:



                                aws rekognition detect-protective-equipment  --image "{\"S3Object\":{\"Bucket\":\"amzn-s3-demo-bucket\",\"Name\":\"image-name\"}}" \ 
                                --profile profile-name --summarization-attributes "{\"MinConfidence\":MinConfidenceNumber,\"RequiredEquipmentTypes\":[\"FACE_COVER\"]}"

Awas Javascript dinonaktifkan atau tidak tersedia di browser Anda.

Untuk menggunakan Dokumentasi AWS, Javascript harus diaktifkan. Lihat halaman Bantuan browser Anda untuk petunjuk.

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