Detect multiple objects in a local file

// localizeObjects gets objects and bounding boxes from the Vision API for an image at the given file path.
func localizeObjects(w io.Writer, file string) error {
	ctx := context.Background()

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

	f, err := os.Open(file)
	if err != nil {
		return err
	}
	defer f.Close()

	image, err := vision.NewImageFromReader(f)
	if err != nil {
		return err
	}
	annotations, err := client.LocalizeObjects(ctx, image, nil)
	if err != nil {
		return err
	}

	if len(annotations) == 0 {
		fmt.Fprintln(w, "No objects found.")
		return nil
	}

	fmt.Fprintln(w, "Objects:")
	for _, annotation := range annotations {
		fmt.Fprintln(w, annotation.Name)
		fmt.Fprintln(w, annotation.Score)

		for _, v := range annotation.BoundingPoly.NormalizedVertices {
			fmt.Fprintf(w, "(%f,%f)\n", v.X, v.Y)
		}
	}

	return nil
}

/**
 * Detects localized objects in the specified local image.
 *
 * @param filePath The path to the file to perform localized object detection on.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
public static void detectLocalizedObjects(String filePath) throws IOException {
  List<AnnotateImageRequest> requests = new ArrayList<>();

  ByteString imgBytes = ByteString.readFrom(new FileInputStream(filePath));

  Image img = Image.newBuilder().setContent(imgBytes).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder()
          .addFeatures(Feature.newBuilder().setType(Type.OBJECT_LOCALIZATION))
          .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()) {
    // Perform the request
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();

    // Display the results
    for (AnnotateImageResponse res : responses) {
      for (LocalizedObjectAnnotation entity : res.getLocalizedObjectAnnotationsList()) {
        System.out.format("Object name: %s%n", entity.getName());
        System.out.format("Confidence: %s%n", entity.getScore());
        System.out.format("Normalized Vertices:%n");
        entity
            .getBoundingPoly()
            .getNormalizedVerticesList()
            .forEach(vertex -> System.out.format("- (%s, %s)%n", vertex.getX(), vertex.getY()));
      }
    }
  }
}

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

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

/**
 * TODO(developer): Uncomment the following line before running the sample.
 */
// const fileName = `/path/to/localImage.png`;
const request = {
  image: {content: fs.readFileSync(fileName)},
};

const [result] = await client.objectLocalization(request);
const objects = result.localizedObjectAnnotations;
objects.forEach(object => {
  console.log(`Name: ${object.name}`);
  console.log(`Confidence: ${object.score}`);
  const vertices = object.boundingPoly.normalizedVertices;
  vertices.forEach(v => console.log(`x: ${v.x}, y:${v.y}`));
});

namespace Google\Cloud\Samples\Vision;

use Google\Cloud\Vision\V1\ImageAnnotatorClient;

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

    # annotate the image
    $image = file_get_contents($path);
    $response = $imageAnnotator->objectLocalization($image);
    $objects = $response->getLocalizedObjectAnnotations();

    foreach ($objects as $object) {
        $name = $object->getName();
        $score = $object->getScore();
        $vertices = $object->getBoundingPoly()->getNormalizedVertices();

        printf('%s (confidence %f)):' . PHP_EOL, $name, $score);
        print('normalized bounding polygon vertices: ');
        foreach ($vertices as $vertex) {
            printf(' (%f, %f)', $vertex->getX(), $vertex->getY());
        }
        print(PHP_EOL);
    }

    $imageAnnotator->close();
}

def localize_objects(path):
    """Localize objects in the local image.

    Args:
    path: The path to the local file.
    """
    from google.cloud import vision

    client = vision.ImageAnnotatorClient()

    with open(path, "rb") as image_file:
        content = image_file.read()
    image = vision.Image(content=content)

    objects = client.object_localization(image=image).localized_object_annotations

    print(f"Number of objects found: {len(objects)}")
    for object_ in objects:
        print(f"\n{object_.name} (confidence: {object_.score})")
        print("Normalized bounding polygon vertices: ")
        for vertex in object_.bounding_poly.normalized_vertices:
            print(f" - ({vertex.x}, {vertex.y})")