Detect landmarks in a Cloud Storage file

Perform landmark detection on a file stored in Cloud Storage.

Explore further

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

• Detect landmarks

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.

To authenticate to Vision, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

// detectLandmarks gets landmarks from the Vision API for an image at the given file path.
func detectLandmarksURI(w io.Writer, file string) error {
	ctx := context.Background()

	client, err := vision.NewImageAnnotatorClient(ctx)
	if err != nil {
		return err
	}

	image := vision.NewImageFromURI(file)
	annotations, err := client.DetectLandmarks(ctx, image, nil, 10)
	if err != nil {
		return err
	}

	if len(annotations) == 0 {
		fmt.Fprintln(w, "No landmarks found.")
	} else {
		fmt.Fprintln(w, "Landmarks:")
		for _, annotation := range annotations {
			fmt.Fprintln(w, annotation.Description)
		}
	}

	return nil
}

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.

To authenticate to Vision, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

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.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.cloud.vision.v1.ImageSource;
import com.google.cloud.vision.v1.LocationInfo;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

public class DetectLandmarksGcs {

  public static void detectLandmarksGcs() throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String filePath = "gs://your-gcs-bucket/path/to/image/file.jpg";
    detectLandmarksGcs(filePath);
  }

  // Detects landmarks in the specified remote image on Google Cloud Storage.
  public static void detectLandmarksGcs(String gcsPath) throws IOException {
    List<AnnotateImageRequest> requests = new ArrayList<>();

    ImageSource imgSource = ImageSource.newBuilder().setGcsImageUri(gcsPath).build();
    Image img = Image.newBuilder().setSource(imgSource).build();
    Feature feat = Feature.newBuilder().setType(Feature.Type.LANDMARK_DETECTION).build();
    AnnotateImageRequest request =
        AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
    requests.add(request);

    // 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 client = ImageAnnotatorClient.create()) {
      BatchAnnotateImagesResponse response = client.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 full list of available annotations, see http://g.co/cloud/vision/docs
        for (EntityAnnotation annotation : res.getLandmarkAnnotationsList()) {
          LocationInfo info = annotation.getLocationsList().listIterator().next();
          System.out.format("Landmark: %s%n %s%n", annotation.getDescription(), info.getLatLng());
        }
      }
    }
  }
}

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.

To authenticate to Vision, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

// Imports the Google Cloud client libraries
const vision = require('@google-cloud/vision');

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

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const bucketName = 'Bucket where the file resides, e.g. my-bucket';
// const fileName = 'Path to file within bucket, e.g. path/to/image.png';

// Performs landmark detection on the gcs file
const [result] = await client.landmarkDetection(
  `gs://${bucketName}/${fileName}`
);
const landmarks = result.landmarkAnnotations;
console.log('Landmarks:');
landmarks.forEach(landmark => console.log(landmark));

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.

To authenticate to Vision, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

namespace Google\Cloud\Samples\Vision;

use Google\Cloud\Vision\V1\ImageAnnotatorClient;

/**
 * @param string $path GCS path to the image, e.g. "gs://path/to/your/image.jpg"
 */
function detect_landmark_gcs(string $path)
{
    $imageAnnotator = new ImageAnnotatorClient();

    # annotate the image
    $response = $imageAnnotator->landmarkDetection($path);
    $landmarks = $response->getLandmarkAnnotations();

    printf('%d landmark found:' . PHP_EOL, count($landmarks));
    foreach ($landmarks as $landmark) {
        print($landmark->getDescription() . PHP_EOL);
    }

    $imageAnnotator->close();
}

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.

To authenticate to Vision, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

def detect_landmarks_uri(uri):
    """Detects landmarks in the file located in Google Cloud Storage or on the
    Web."""
    from google.cloud import vision

    client = vision.ImageAnnotatorClient()
    image = vision.Image()
    image.source.image_uri = uri

    response = client.landmark_detection(image=image)
    landmarks = response.landmark_annotations
    print("Landmarks:")

    for landmark in landmarks:
        print(landmark.description)

    if response.error.message:
        raise Exception(
            "{}\nFor more info on error messages, check: "
            "https://cloud.google.com/apis/design/errors".format(response.error.message)
        )

What's next

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