Detect faces in a local file

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

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

	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.DetectFaces(ctx, image, nil, 10)
	if err != nil {
		return err
	}
	if len(annotations) == 0 {
		fmt.Fprintln(w, "No faces found.")
	} else {
		fmt.Fprintln(w, "Faces:")
		for i, annotation := range annotations {
			fmt.Fprintln(w, "  Face", i)
			fmt.Fprintln(w, "    Anger:", annotation.AngerLikelihood)
			fmt.Fprintln(w, "    Joy:", annotation.JoyLikelihood)
			fmt.Fprintln(w, "    Surprise:", annotation.SurpriseLikelihood)
		}
	}
	return nil
}

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.FaceAnnotation;
import com.google.cloud.vision.v1.Feature;
import com.google.cloud.vision.v1.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

public class DetectFaces {

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

  // Detects faces in the specified local image.
  public static void detectFaces(String filePath) throws IOException {
    List<AnnotateImageRequest> requests = new ArrayList<>();

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

    Image img = Image.newBuilder().setContent(imgBytes).build();
    Feature feat = Feature.newBuilder().setType(Feature.Type.FACE_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 (FaceAnnotation annotation : res.getFaceAnnotationsList()) {
          System.out.format(
              "anger: %s%njoy: %s%nsurprise: %s%nposition: %s",
              annotation.getAngerLikelihood(),
              annotation.getJoyLikelihood(),
              annotation.getSurpriseLikelihood(),
              annotation.getBoundingPoly());
        }
      }
    }
  }
}

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

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

async function detectFaces() {
  /**
   * TODO(developer): Uncomment the following line before running the sample.
   */
  // const fileName = 'Local image file, e.g. /path/to/image.png';

  const [result] = await client.faceDetection(fileName);
  const faces = result.faceAnnotations;
  console.log('Faces:');
  faces.forEach((face, i) => {
    console.log(`  Face #${i + 1}:`);
    console.log(`    Joy: ${face.joyLikelihood}`);
    console.log(`    Anger: ${face.angerLikelihood}`);
    console.log(`    Sorrow: ${face.sorrowLikelihood}`);
    console.log(`    Surprise: ${face.surpriseLikelihood}`);
  });
}
detectFaces();

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"
 * @param string $outFile Saves a copy of the image supplied in $path with a
 *                        rectangle drawn around the detected faces.
 */
function detect_face(string $path, string $outFile = null)
{
    $imageAnnotator = new ImageAnnotatorClient();

    # annotate the image
    // $path = 'path/to/your/image.jpg'
    $image = file_get_contents($path);
    $response = $imageAnnotator->faceDetection($image);
    $faces = $response->getFaceAnnotations();

    # names of likelihood from google.cloud.vision.enums
    $likelihoodName = ['UNKNOWN', 'VERY_UNLIKELY', 'UNLIKELY',
    'POSSIBLE', 'LIKELY', 'VERY_LIKELY'];

    printf('%d faces found:' . PHP_EOL, count($faces));
    foreach ($faces as $face) {
        $anger = $face->getAngerLikelihood();
        printf('Anger: %s' . PHP_EOL, $likelihoodName[$anger]);

        $joy = $face->getJoyLikelihood();
        printf('Joy: %s' . PHP_EOL, $likelihoodName[$joy]);

        $surprise = $face->getSurpriseLikelihood();
        printf('Surprise: %s' . PHP_EOL, $likelihoodName[$surprise]);

        # get bounds
        $vertices = $face->getBoundingPoly()->getVertices();
        $bounds = [];
        foreach ($vertices as $vertex) {
            $bounds[] = sprintf('(%d,%d)', $vertex->getX(), $vertex->getY());
        }
        print('Bounds: ' . join(', ', $bounds) . PHP_EOL);
        print(PHP_EOL);
    }
}

def detect_faces(path):
    """Detects faces in an image."""
    from google.cloud import vision

    client = vision.ImageAnnotatorClient()

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

    image = vision.Image(content=content)

    response = client.face_detection(image=image)
    faces = response.face_annotations

    # Names of likelihood from google.cloud.vision.enums
    likelihood_name = (
        "UNKNOWN",
        "VERY_UNLIKELY",
        "UNLIKELY",
        "POSSIBLE",
        "LIKELY",
        "VERY_LIKELY",
    )
    print("Faces:")

    for face in faces:
        print(f"anger: {likelihood_name[face.anger_likelihood]}")
        print(f"joy: {likelihood_name[face.joy_likelihood]}")
        print(f"surprise: {likelihood_name[face.surprise_likelihood]}")

        vertices = [
            f"({vertex.x},{vertex.y})" for vertex in face.bounding_poly.vertices
        ]

        print("face bounds: {}".format(",".join(vertices)))

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