Detect labels on an image

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Perform label detection on an image.

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For detailed documentation that includes this code sample, see the following:

Code sample

Go

Before trying this sample, follow the Go setup instructions in the Vision quickstart using client libraries. For more information, see the Vision Go API reference documentation. 


// 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

Before trying this sample, follow the Java setup instructions in the Vision quickstart using client libraries. For more information, see the Vision Java API reference documentation. 

// 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

Before trying this sample, follow the Node.js setup instructions in the Vision quickstart using client libraries. For more information, see the Vision Node.js API reference documentation. 

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

Before trying this sample, follow the PHP setup instructions in the Vision quickstart using client libraries. For more information, see the Vision PHP API reference documentation. 

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

# imports the Google Cloud client library
use Google\Cloud\Vision\V1\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

Before trying this sample, follow the Python setup instructions in the Vision quickstart using client libraries. For more information, see the Vision Python API reference documentation. 

import io
import os

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

# Instantiates a client
client = vision.ImageAnnotatorClient()

# The name of the image file to annotate
file_name = os.path.abspath('resources/wakeupcat.jpg')

# Loads the image into memory
with io.open(file_name, 'rb') as image_file:
    content = image_file.read()

image = vision.Image(content=content)

# 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)

What's next

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