ImageAnnotatorClient

ImageAnnotatorClient

Service that performs Google Cloud Vision API detection tasks over client images, such as face, landmark, logo, label, and text detection. The ImageAnnotator service returns detected entities from the images.

Constructor

new ImageAnnotatorClient(optionsopt)

Construct an instance of ImageAnnotatorClient.

Parameters:
Name Type Attributes Description
options object <optional>

The configuration object. See the subsequent parameters for more details.

Properties
Name Type Attributes Description
credentials object <optional>

Credentials object.

Properties
Name Type Attributes Description
client_email string <optional>
private_key string <optional>
email string <optional>

Account email address. Required when using a .pem or .p12 keyFilename.

keyFilename string <optional>

Full path to the a .json, .pem, or .p12 key downloaded from the Google Developers Console. If you provide a path to a JSON file, the projectId option below is not necessary. NOTE: .pem and .p12 require you to specify options.email as well.

port number <optional>

The port on which to connect to the remote host.

projectId string <optional>

The project ID from the Google Developer's Console, e.g. 'grape-spaceship-123'. We will also check the environment variable GCLOUD_PROJECT for your project ID. If your app is running in an environment which supports Application Default Credentials, your project ID will be detected automatically.

promise function <optional>

Custom promise module to use instead of native Promises.

apiEndpoint string <optional>

The domain name of the API remote host.

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Members

(static) apiEndpoint

The DNS address for this API service - same as servicePath(), exists for compatibility reasons.

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(static) port

The port for this API service.

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(static) scopes

The scopes needed to make gRPC calls for every method defined in this service.

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(static) servicePath

The DNS address for this API service.

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Methods

asyncBatchAnnotateFiles(request, optionsopt, callbackopt) → {Promise}

Run asynchronous image detection and annotation for a list of generic files, such as PDF files, which may contain multiple pages and multiple images per page. Progress and results can be retrieved through the google.longrunning.Operations interface. Operation.metadata contains OperationMetadata (metadata). Operation.response contains AsyncBatchAnnotateFilesResponse (results).

Parameters:
Name Type Attributes Description
request Object

The request object that will be sent.

Properties
Name Type Description
requests Array.<Object>

Individual async file annotation requests for this batch.

This object should have the same structure as AsyncAnnotateFileRequest

options Object <optional>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See gax.CallOptions for the details.

callback function <optional>

The function which will be called with the result of the API call.

The second parameter to the callback is a gax.Operation object.

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Example
const vision = require('vision.v1p4beta1');

const client = new vision.v1p4beta1.ImageAnnotatorClient({
  // optional auth parameters.
});

const requests = [];

// Handle the operation using the promise pattern.
client.asyncBatchAnnotateFiles({requests: requests})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const requests = [];

// Handle the operation using the event emitter pattern.
client.asyncBatchAnnotateFiles({requests: requests})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const requests = [];

// Handle the operation using the await pattern.
const [operation] = await client.asyncBatchAnnotateFiles({requests: requests});

const [response] = await operation.promise();

asyncBatchAnnotateImages(request, optionsopt, callbackopt) → {Promise}

Run asynchronous image detection and annotation for a list of images.

Progress and results can be retrieved through the google.longrunning.Operations interface. Operation.metadata contains OperationMetadata (metadata). Operation.response contains AsyncBatchAnnotateImagesResponse (results).

This service will write image annotation outputs to json files in customer GCS bucket, each json file containing BatchAnnotateImagesResponse proto.

Parameters:
Name Type Attributes Description
request Object

The request object that will be sent.

Properties
Name Type Description
requests Array.<Object>

Individual image annotation requests for this batch.

This object should have the same structure as AnnotateImageRequest

outputConfig Object

Required. The desired output location and metadata (e.g. format).

This object should have the same structure as OutputConfig

options Object <optional>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See gax.CallOptions for the details.

callback function <optional>

The function which will be called with the result of the API call.

The second parameter to the callback is a gax.Operation object.

Source:
Example
const vision = require('vision.v1p4beta1');

const client = new vision.v1p4beta1.ImageAnnotatorClient({
  // optional auth parameters.
});

const requests = [];
const outputConfig = {};
const request = {
  requests: requests,
  outputConfig: outputConfig,
};

// Handle the operation using the promise pattern.
client.asyncBatchAnnotateImages(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const requests = [];
const outputConfig = {};
const request = {
  requests: requests,
  outputConfig: outputConfig,
};

// Handle the operation using the event emitter pattern.
client.asyncBatchAnnotateImages(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const requests = [];
const outputConfig = {};
const request = {
  requests: requests,
  outputConfig: outputConfig,
};

// Handle the operation using the await pattern.
const [operation] = await client.asyncBatchAnnotateImages(request);

const [response] = await operation.promise();

batchAnnotateFiles(request, optionsopt, callbackopt) → {Promise}

Service that performs image detection and annotation for a batch of files. Now only "application/pdf", "image/tiff" and "image/gif" are supported.

This service will extract at most 5 (customers can specify which 5 in AnnotateFileRequest.pages) frames (gif) or pages (pdf or tiff) from each file provided and perform detection and annotation for each image extracted.

Parameters:
Name Type Attributes Description
request Object

The request object that will be sent.

Properties
Name Type Description
requests Array.<Object>

The list of file annotation requests. Right now we support only one AnnotateFileRequest in BatchAnnotateFilesRequest.

This object should have the same structure as AnnotateFileRequest

options Object <optional>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See gax.CallOptions for the details.

callback function <optional>

The function which will be called with the result of the API call.

The second parameter to the callback is an object representing BatchAnnotateFilesResponse.

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Example
const vision = require('vision.v1p4beta1');

const client = new vision.v1p4beta1.ImageAnnotatorClient({
  // optional auth parameters.
});

const requests = [];
client.batchAnnotateFiles({requests: requests})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

batchAnnotateImages(request, optionsopt, callbackopt) → {Promise}

Run image detection and annotation for a batch of images.

Parameters:
Name Type Attributes Description
request Object

The request object that will be sent.

Properties
Name Type Description
requests Array.<Object>

Individual image annotation requests for this batch.

This object should have the same structure as AnnotateImageRequest

options Object <optional>

Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See gax.CallOptions for the details.

callback function <optional>

The function which will be called with the result of the API call.

The second parameter to the callback is an object representing BatchAnnotateImagesResponse.

Source:
Example
const vision = require('vision.v1p4beta1');

const client = new vision.v1p4beta1.ImageAnnotatorClient({
  // optional auth parameters.
});

const requests = [];
client.batchAnnotateImages({requests: requests})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

getProjectId(callback)

Return the project ID used by this class.

Parameters:
Name Type Description
callback function

the callback to be called with the current project Id.

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