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# Ejemplo: dibujar recuadros delimitadores alrededor de las mascarillas
En los siguientes ejemplos, se muestra cómo dibujar recuadros delimitadores alrededor de las mascarillas detectadas en personas. Para ver un ejemplo que utilice AWS Lambda Amazon DynamoDB, consulte el repositorio de ejemplos [AWS del SDK de documentación](https://github.com/awsdocs/aws-doc-sdk-examples/tree/master/javav2/usecases/creating_lambda_ppe). GitHub
Para detectar mascarillas, utilice la operación API que [DetectProtectiveEquipment](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectProtectiveEquipment.html)no es de almacenamiento. La imagen se carga desde el sistema de archivos local. Puede proporcionar la imagen de entrada a `DetectProtectiveEquipment` como una matriz de bytes de imagen (bytes con codificación en base64). Para obtener más información, consulte [Trabajar con imágenes](images.md).
El ejemplo muestra un recuadro delimitador alrededor de las mascarillas detectadas. El recuadro delimitador es verde si la mascarilla cubre completamente la parte del cuerpo. De lo contrario, aparecerá un cuadro delimitador rojo. Como advertencia, si la confianza de la detección es inferior al valor de confianza especificado, aparecerá un recuadro delimitador amarillo dentro del recuadro delimitador de la mascarilla. Si no se detecta ninguna mascarilla, se dibuja un cuadro delimitador rojo alrededor de la persona.
El resultado de la imagen es similar al siguiente.
**Para mostrar los recuadros delimitadores en las mascarillas detectadas**
1. Si aún no lo ha hecho:
1. Cree o actualice un usuario de `AmazonRekognitionFullAccess` con permisos. Para obtener más información, consulte [Paso 1: Configurar una cuenta de AWS y crear un usuario](setting-up.md#setting-up-iam).
1. Instale y configure el AWS CLI y el AWS SDKs. Para obtener más información, consulte [Paso 2: Configure y AWS CLI AWS SDKs](setup-awscli-sdk.md).
1. Consulte los siguientes ejemplos para llamar a la operación `DetectProtectiveEquipment`. Para obtener información sobre cómo mostrar los cuadros delimitadores en una imagen, consulte [Visualización de cuadros delimitadores](images-displaying-bounding-boxes.md).
------
#### [ Java ]
En la función `main`, cambie lo siguiente:
+ El valor de `photo` a la ruta y el nombre de archivo de un archivo de imagen local (PNG o JPEG).
+ El valor de `confidence` al nivel de confianza deseado (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 persons = result.getPersons();
for (ProtectiveEquipmentPerson person: persons) {
BoundingBox boxPerson = person.getBoundingBox();
left = width * boxPerson.getLeft();
top = height * boxPerson.getTop();
Boolean foundMask=false;
List bodyParts=person.getBodyParts();
if (bodyParts.isEmpty()==false)
{
//body parts detected
for (ProtectiveEquipmentBodyPart bodyPart: bodyParts) {
List 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 ]
Este código se ha tomado del GitHub repositorio de ejemplos del SDK de AWS documentación. Consulte el ejemplo completo [aquí](https://github.com/awsdocs/aws-doc-sdk-examples/blob/master/javav2/example_code/rekognition/src/main/java/com/example/rekognition/PPEBoundingBoxFrame.java).
```
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: " +
" \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 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 persons = result.persons();
for (ProtectiveEquipmentPerson person: persons) {
List bodyParts=person.bodyParts();
if (!bodyParts.isEmpty()){
for (ProtectiveEquipmentBodyPart bodyPart: bodyParts) {
List 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 ]
En la función `main`, cambie lo siguiente:
+ El valor de `photo` a la ruta y el nombre de archivo de un archivo de imagen local (PNG o JPEG).
+ El valor de `confidence` al nivel de confianza deseado (50-100).
+ Sustituya el valor de `profile_name` en la línea que crea la sesión de Rekognition por el nombre de su perfil de desarrollador.
```
#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 ]
En el siguiente ejemplo de la CLI, cambie el valor de los argumentos que se enumeran a continuación:
+ El valor de `photo` a la ruta y el nombre de archivo de un archivo de imagen local (PNG o JPEG).
+ El valor de `confidence` al nivel de confianza deseado (50-100).
+ Sustituya el valor de `profile_name` en la línea que crea la sesión de Rekognition por el nombre de su perfil de desarrollador.
```
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"]}"
```
Si accede a la CLI en un dispositivo Windows, utilice comillas dobles en lugar de comillas simples y evite las comillas dobles internas con una barra invertida (es decir, \\) para corregir cualquier error del analizador que pueda encontrar. Por ver un ejemplo, consulte lo siguiente:
```
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\"]}"
```
------