Detect logos

Logo Detection detects popular product logos within an image.

Note: The Vision API now supports offline asynchronous batch image annotation for all features. This asynchronous request supports up to 2000 image files and returns response JSON files that are stored in your Google Cloud Storage bucket. For more information about this feature, refer to Offline batch image annotation.

Image credit: Robert Scoble (CC BY 2.0, annotation added).

Logo detection requests

Set up your GCP project and authentication

If you have not created a Google Cloud Platform (GCP) project and service account credentials, do so now. Expand this section for instructions.

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
2. Set up a Cloud Console project.

   Set up a project

   Click to:

   • Create or select a project.
   • Enable the Vision API for that project.
   • Create a service account.
   • Download a private key as JSON.

   You can view and manage these resources at any time in the Cloud Console.

3. Set the environment variable GOOGLE_APPLICATION_CREDENTIALS to the path of the JSON file that contains your service account key. This variable only applies to your current shell session, so if you open a new session, set the variable again.

   Example: Linux or macOS

   export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   Replace KEY_PATH with the path of the JSON file that contains your service account key.

   For example:

   export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"

   Example: Windows

   For PowerShell:

   $env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   Replace KEY_PATH with the path of the JSON file that contains your service account key.

   For example:

   $env:GOOGLE_APPLICATION_CREDENTIALS="C:\Users\username\Downloads\service-account-file.json"

   For command prompt:

   set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

   Replace KEY_PATH with the path of the JSON file that contains your service account key.

4. Install and initialize the Cloud SDK.

Detect logos in a local image

The Vision API can perform feature detection on a local image file by sending the contents of the image file as a base64 encoded string in the body of your request.

REST & CMD LINE

Before using any of the request data, make the following replacements:

• base64-encoded-image: The base64 representation (ASCII string) of your binary image data. This string should look similar to the following string:
  • /9j/4QAYRXhpZgAA...9tAVx/zDQDlGxn//2Q==
  Visit the base64 encode topic for more information.

HTTP method and URL:

POST https://vision.googleapis.com/v1/images:annotate

Request JSON body:

{
  "requests": [
    {
      "image": {
        "content": "base64-encoded-image"
      },
      "features": [
        {
          "type": "LOGO_DETECTION"
        },
      ]
    }
  ]
}

To send your request, choose one of these options:

curl

Note: Ensure you have set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path for your service account private key file.

Save the request body in a file called request.json, and execute the following command:

curl -X POST \
-H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://vision.googleapis.com/v1/images:annotate"

PowerShell

Note: Ensure you have set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path for your service account private key file.

Save the request body in a file called request.json, and execute the following command:

$cred = gcloud auth application-default print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
  -Method POST `
  -Headers $headers `
  -ContentType: "application/json; charset=utf-8" `
  -InFile request.json `
  -Uri "https://vision.googleapis.com/v1/images:annotate" | Select-Object -Expand Content

If the request is successful, the server returns a 200 OK HTTP status code and the response in JSON format.

Response:

Note: Zero coordinate values omitted. When the API detects a coordinate ("x" or "y") value of 0, that coordinate is omitted in the JSON response. Thus, a response with a bounding poly around the entire image would be
[{},{"x": 100},{"x": 100,"y": 100},{"y": 100}] for an image that is 100px by 100px. For more information, see the API Reference documentation.

{
  "responses": [
    {
      "logoAnnotations": [
        {
          "mid": "/m/045c7b",
          "description": "google",
          "score": 0.980325,
          "boundingPoly": {
            "vertices": [
              {
                "x": 12,
                "y": 42
              },
              {
                "x": 439,
                "y": 42
              },
              {
                "x": 439,
                "y": 285
              },
              {
                "x": 12,
                "y": 285
              }
            ]
          }
        }
      ]
    }
  ]
}

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.

View on GitHub Feedback

// detectLogos gets logos from the Vision API for an image at the given file path.
func detectLogos(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.DetectLogos(ctx, image, nil, 10)
	if err != nil {
		return err
	}

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

	return nil
}

Java

Before trying this sample, follow the Java setup instructions in the Vision API Quickstart Using Client Libraries. For more information, see the Vision API Java API reference documentation.

Note: For Java Spring framework users, Spring Cloud GCP offers a way to automatically configure authentication settings and client objects to use Vision API.

View on GitHub Feedback

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.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

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

  // Detects logos in the specified local image.

  public static void detectLogos(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.LOGO_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.getLogoAnnotationsList()) {
          System.out.println(annotation.getDescription());
        }
      }
    }
  }
}

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.

View on GitHub Feedback

const vision = require('@google-cloud/vision');

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

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

// Performs logo detection on the local file
const [result] = await client.logoDetection(fileName);
const logos = result.logoAnnotations;
console.log('Logos:');
logos.forEach(logo => console.log(logo));

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.

View on GitHub Feedback

def detect_logos(path):
    """Detects logos in the file."""
    from google.cloud import vision
    import io
    client = vision.ImageAnnotatorClient()

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

    image = vision.Image(content=content)

    response = client.logo_detection(image=image)
    logos = response.logo_annotations
    print('Logos:')

    for logo in logos:
        print(logo.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))

Additional languages

C#: Please follow the C# setup instructions on the client libraries page and then visit the Vision reference documentation for .NET.

PHP: Please follow the PHP setup instructions on the client libraries page and then visit the Vision reference documentation for PHP.

Ruby: Please follow the Ruby setup instructions on the client libraries page and then visit the Vision reference documentation for Ruby.

Detect Logos in a remote image

For your convenience, the Vision API can perform feature detection directly on an image file located in Google Cloud Storage or on the Web without the need to send the contents of the image file in the body of your request.

Caution: When fetching images from HTTP/HTTPS URLs, Google cannot guarantee that the request will be completed. Your request may fail if the specified host denies the request (for example, due to request throttling or DOS prevention), or if Google throttles requests to the site for abuse prevention. You should not depend on externally-hosted images for production applications.

REST & CMD LINE

Before using any of the request data, make the following replacements:

• cloud-storage-image-uri: the path to a valid image file in a Cloud Storage bucket. You must at least have read privileges to the file. Example:

  • gs://cloud-samples-data/vision/logo/google_logo.jpg

HTTP method and URL:

POST https://vision.googleapis.com/v1/images:annotate

Request JSON body:

{
  "requests": [
    {
      "image": {
        "source": {
          "gcsImageUri": "cloud-storage-image-uri"
        }
      },
      "features": [
        {
          "type": "LOGO_DETECTION"
        },
      ]
    }
  ]
}

To send your request, choose one of these options:

curl

Note: Ensure you have set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path for your service account private key file.

Save the request body in a file called request.json, and execute the following command:

curl -X POST \
-H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://vision.googleapis.com/v1/images:annotate"

PowerShell

Note: Ensure you have set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path for your service account private key file.

Save the request body in a file called request.json, and execute the following command:

$cred = gcloud auth application-default print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
  -Method POST `
  -Headers $headers `
  -ContentType: "application/json; charset=utf-8" `
  -InFile request.json `
  -Uri "https://vision.googleapis.com/v1/images:annotate" | Select-Object -Expand Content

If the request is successful, the server returns a 200 OK HTTP status code and the response in JSON format.

Response:

Note: Zero coordinate values omitted. When the API detects a coordinate ("x" or "y") value of 0, that coordinate is omitted in the JSON response. Thus, a response with a bounding poly around the entire image would be
[{},{"x": 100},{"x": 100,"y": 100},{"y": 100}] for an image that is 100px by 100px. For more information, see the API Reference documentation.

{
  "responses": [
    {
      "logoAnnotations": [
        {
          "mid": "/m/045c7b",
          "description": "google",
          "score": 0.980325,
          "boundingPoly": {
            "vertices": [
              {
                "x": 12,
                "y": 42
              },
              {
                "x": 439,
                "y": 42
              },
              {
                "x": 439,
                "y": 285
              },
              {
                "x": 12,
                "y": 285
              }
            ]
          }
        }
      ]
    }
  ]
}

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.

View on GitHub Feedback

// detectLogos gets logos from the Vision API for an image at the given file path.
func detectLogosURI(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.DetectLogos(ctx, image, nil, 10)
	if err != nil {
		return err
	}

	if len(annotations) == 0 {
		fmt.Fprintln(w, "No logos found.")
	} else {
		fmt.Fprintln(w, "Logos:")
		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.

View on GitHub Feedback

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 java.io.IOException;
import java.util.ArrayList;
import java.util.List;

public class DetectLogosGcs {

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

  // Detects logos in the specified remote image on Google Cloud Storage.
  public static void detectLogosGcs(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.LOGO_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.getLogoAnnotationsList()) {
          System.out.println(annotation.getDescription());
        }
      }
    }
  }
}

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.

View on GitHub Feedback

// 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 logo detection on the gcs file
const [result] = await client.logoDetection(`gs://${bucketName}/${fileName}`);
const logos = result.logoAnnotations;
console.log('Logos:');
logos.forEach(logo => console.log(logo));

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.

View on GitHub Feedback

def detect_logos_uri(uri):
    """Detects logos 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.logo_detection(image=image)
    logos = response.logo_annotations
    print('Logos:')

    for logo in logos:
        print(logo.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))

gcloud

To perform image property detection, use the gcloud ml vision detect-logos command as shown in the following example:

gcloud ml vision detect-logos gs://cloud-samples-data/vision/logo/google_logo.jpg

Additional languages

C#: Please follow the C# setup instructions on the client libraries page and then visit the Vision reference documentation for .NET.

PHP: Please follow the PHP setup instructions on the client libraries page and then visit the Vision reference documentation for PHP.

Ruby: Please follow the Ruby setup instructions on the client libraries page and then visit the Vision reference documentation for Ruby.

Try it

Try logo detection below. You can use the image specified already (gs://cloud-samples-data/vision/logo/google_logo.jpg) or specify your own image in its place. Send the request by selecting Execute.

Image credit: Robert Scoble (CC BY 2.0, annotation added).

Request body:

{
  "requests": [
    {
      "features": [
        {
          "type": "LOGO_DETECTION"
        }
      ],
      "image": {
        "source": {
          "imageUri": "gs://cloud-samples-data/vision/logo/google_logo.jpg"
        }
      }
    }
  ]
}