La función de búsqueda de productos está en modo de mantenimiento. Para obtener una mejor escalabilidad y la misma funcionalidad que Product Search, usa Vision Warehouse.

Google uses AI technology to translate content into your preferred language. AI translations can contain errors.

Detectar etiquetas en una imagen

Realiza la detección de etiquetas en una imagen.

Explora más

Para obtener documentación en la que se incluye esta muestra de código, consulta lo siguiente:

Muestra de código

Go

Si quieres obtener información sobre cómo instalar y usar la biblioteca cliente de Product Search de la API de Vision, consulta Bibliotecas cliente de Product Search de la API de Vision. Si quieres obtener más información, consulta la documentación de referencia de la API de Vision para Product Search Go.

Para autenticar Product Search de la API de Vision, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para un entorno de desarrollo local.


// Sample vision-quickstart uses the Google Cloud Vision API to label an image.
package main

import (
	"context"
	"fmt"
	"log"
	"os"

	vision "cloud.google.com/go/vision/apiv1"
)

func main() {
	ctx := context.Background()

	// Creates a client.
	client, err := vision.NewImageAnnotatorClient(ctx)
	if err != nil {
		log.Fatalf("Failed to create client: %v", err)
	}
	defer client.Close()

	// Sets the name of the image file to annotate.
	filename := "../testdata/cat.jpg"

	file, err := os.Open(filename)
	if err != nil {
		log.Fatalf("Failed to read file: %v", err)
	}
	defer file.Close()
	image, err := vision.NewImageFromReader(file)
	if err != nil {
		log.Fatalf("Failed to create image: %v", err)
	}

	labels, err := client.DetectLabels(ctx, image, nil, 10)
	if err != nil {
		log.Fatalf("Failed to detect labels: %v", err)
	}

	fmt.Println("Labels:")
	for _, label := range labels {
		fmt.Println(label.Description)
	}
}

Java

// Imports the Google Cloud client library

import com.google.cloud.vision.v1.AnnotateImageRequest;
import com.google.cloud.vision.v1.AnnotateImageResponse;
import com.google.cloud.vision.v1.BatchAnnotateImagesResponse;
import com.google.cloud.vision.v1.EntityAnnotation;
import com.google.cloud.vision.v1.Feature;
import com.google.cloud.vision.v1.Feature.Type;
import com.google.cloud.vision.v1.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.protobuf.ByteString;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.ArrayList;
import java.util.List;

public class QuickstartSample {
  public static void main(String... args) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (ImageAnnotatorClient vision = ImageAnnotatorClient.create()) {

      // The path to the image file to annotate
      String fileName = "./resources/wakeupcat.jpg";

      // Reads the image file into memory
      Path path = Paths.get(fileName);
      byte[] data = Files.readAllBytes(path);
      ByteString imgBytes = ByteString.copyFrom(data);

      // Builds the image annotation request
      List<AnnotateImageRequest> requests = new ArrayList<>();
      Image img = Image.newBuilder().setContent(imgBytes).build();
      Feature feat = Feature.newBuilder().setType(Type.LABEL_DETECTION).build();
      AnnotateImageRequest request =
          AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
      requests.add(request);

      // Performs label detection on the image file
      BatchAnnotateImagesResponse response = vision.batchAnnotateImages(requests);
      List<AnnotateImageResponse> responses = response.getResponsesList();

      for (AnnotateImageResponse res : responses) {
        if (res.hasError()) {
          System.out.format("Error: %s%n", res.getError().getMessage());
          return;
        }

        for (EntityAnnotation annotation : res.getLabelAnnotationsList()) {
          annotation
              .getAllFields()
              .forEach((k, v) -> System.out.format("%s : %s%n", k, v.toString()));
        }
      }
    }
  }
}

Kotlin

// import com.google.cloud.vision.v1.ImageAnnotatorClient
// import java.io.File
val imgProto = ByteString.copyFrom(File(imageFileName).readBytes())
val vision = ImageAnnotatorClient.create()

// Set up the Cloud Vision API request.
val img = Image.newBuilder().setContent(imgProto).build()
val feat = Feature.newBuilder().setType(Type.LABEL_DETECTION).build()
val request = AnnotateImageRequest.newBuilder()
    .addFeatures(feat)
    .setImage(img)
    .build()

// Call the Cloud Vision API and perform label detection on the image.
val result = vision.batchAnnotateImages(arrayListOf(request))

// Print the label annotations for the first response.
result.responsesList[0].labelAnnotationsList.forEach { label ->
    println("${label.description} (${(label.score * 100).toInt()}%)")
}

Node.js

async function quickstart() {
  // Imports the Google Cloud client library
  const vision = require('@google-cloud/vision');

  // Creates a client
  const client = new vision.ImageAnnotatorClient();

  // Performs label detection on the image file
  const [result] = await client.labelDetection('./resources/wakeupcat.jpg');
  const labels = result.labelAnnotations;
  console.log('Labels:');
  labels.forEach(label => console.log(label.description));
}
quickstart();

PHP

Si quieres obtener información sobre cómo instalar y usar la biblioteca cliente de Product Search de la API de Vision, consulta Bibliotecas cliente de Product Search de la API de Vision.

# includes the autoloader for libraries installed with composer
require __DIR__ . '/vendor/autoload.php';

# imports the Google Cloud client library
use Google\Cloud\Vision\V1\Client\ImageAnnotatorClient;

# instantiates a client
$imageAnnotator = new ImageAnnotatorClient();

# the name of the image file to annotate
$fileName = 'test/data/wakeupcat.jpg';

# prepare the image to be annotated
$image = file_get_contents($fileName);

# performs label detection on the image file
$response = $imageAnnotator->labelDetection($image);
$labels = $response->getLabelAnnotations();

if ($labels) {
    echo('Labels:' . PHP_EOL);
    foreach ($labels as $label) {
        echo($label->getDescription() . PHP_EOL);
    }
} else {
    echo('No label found' . PHP_EOL);
}

Python


# Imports the Google Cloud client library
from google.cloud import vision



def run_quickstart() -> vision.EntityAnnotation:
    """Provides a quick start example for Cloud Vision."""

    # Instantiates a client
    client = vision.ImageAnnotatorClient()

    # The URI of the image file to annotate
    file_uri = "gs://cloud-samples-data/vision/label/wakeupcat.jpg"

    image = vision.Image()
    image.source.image_uri = file_uri

    # Performs label detection on the image file
    response = client.label_detection(image=image)
    labels = response.label_annotations

    print("Labels:")
    for label in labels:
        print(label.description)

    return labels

¿Qué sigue?

Si quieres buscar y filtrar muestras de código para otros productos de Google Cloud , consulta el navegador de muestras deGoogle Cloud .

Detectar etiquetas en una imagen Organiza tus páginas con colecciones Guarda y categoriza el contenido según tus preferencias.