Import multiple product images

Import images of multiple products in a product set.

Documentation pages that include this code sample

To view the code sample used in context, see the following documentation:

Code sample

Go



import (
	"context"
	"fmt"
	"io"

	vision "cloud.google.com/go/vision/apiv1"
	visionpb "google.golang.org/genproto/googleapis/cloud/vision/v1"
)


// importProductSets creates a product set using information in a csv file on GCS.
func importProductSets(w io.Writer, projectID string, location string, gcsURI string) error {
	ctx := context.Background()
	c, err := vision.NewProductSearchClient(ctx)
	if err != nil {
		return fmt.Errorf("NewProductSearchClient: %v", err)
	}
	defer c.Close()

	req := &visionpb.ImportProductSetsRequest{
		Parent: fmt.Sprintf("projects/%s/locations/%s", projectID, location),
		InputConfig: &visionpb.ImportProductSetsInputConfig{
			Source: &visionpb.ImportProductSetsInputConfig_GcsSource{
				GcsSource: &visionpb.ImportProductSetsGcsSource{
					CsvFileUri: gcsURI,
				},
			},
		},
	}

	op, err := c.ImportProductSets(ctx, req)
	if err != nil {
		return fmt.Errorf("ImportProductSets: %v", err)
	}

	fmt.Fprintf(w, "Processing operation name: %s\n", op.Name())

	resp, err := op.Wait(ctx)
	if err != nil {
		return fmt.Errorf("Wait: %v", err)
	}

	fmt.Fprintf(w, "processing done.\n")

	for i, status := range resp.Statuses {
		// `0` is the coee for OK in google.rpc.code
		fmt.Fprintf(w, "Status of processing line %d of the csv: %d\n", i, status.Code)

		if status.Code == 0 {
			fmt.Fprintf(w, "Reference image name: %s\n", resp.ReferenceImages[i].Name)
		} else {
			fmt.Fprintf(w, "Status code not OK: %s\n", status.Message)
		}
	}

	return nil
}

Java

/**
 * Import images of different products in the product set.
 *
 * @param projectId - Id of the project.
 * @param computeRegion - Region name.
 * @param gcsUri - Google Cloud Storage URI.Target files must be in Product Search CSV format.
 * @throws Exception - on client errors.
 */
public static void importProductSets(String projectId, String computeRegion, String gcsUri)
    throws Exception {
  try (ProductSearchClient client = ProductSearchClient.create()) {

    // A resource that represents Google Cloud Platform location.
    String formattedParent = ProductSearchClient.formatLocationName(projectId, computeRegion);
    Builder gcsSource = ImportProductSetsGcsSource.newBuilder().setCsvFileUri(gcsUri);

    // Set the input configuration along with Google Cloud Storage URI
    ImportProductSetsInputConfig inputConfig =
        ImportProductSetsInputConfig.newBuilder().setGcsSource(gcsSource).build();

    // Import the product sets from the input URI.
    OperationFuture<ImportProductSetsResponse, BatchOperationMetadata> response =
        client.importProductSetsAsync(formattedParent, inputConfig);

    System.out.println(String.format("Processing operation name: %s", response.getName()));
    ImportProductSetsResponse results = response.get();
    System.out.println("Processing done.");
    System.out.println("Results of the processing:");

    for (int i = 0; i < results.getStatusesCount(); i++) {
      System.out.println(
          String.format(
              "Status of processing line %s of the csv: %s", i, results.getStatuses(i)));
      // Check the status of reference image.
      if (results.getStatuses(i).getCode() == 0) {
        ReferenceImage referenceImage = results.getReferenceImages(i);
        System.out.println(referenceImage);
      } else {
        System.out.println("No reference image.");
      }
    }
  }
}

Node.js

// Imports the Google Cloud client library
const vision = require('@google-cloud/vision');
// Creates a client
const client = new vision.ProductSearchClient();

async function importProductSets() {
  /**
   * TODO(developer): Uncomment the following line before running the sample.
   */
  // const projectId = 'Your Google Cloud project Id';
  // const location = 'A compute region name';
  // const gcsUri = 'Google Cloud Storage path of the input image'';

  // A resource that represents Google Cloud Platform location.
  const projectLocation = client.locationPath(projectId, location);

  // Set the input configuration along with Google Cloud Storage URI
  const inputConfig = {
    gcsSource: {
      csvFileUri: gcsUri,
    },
  };

  // Import the product sets from the input URI.
  const [response, operation] = await client.importProductSets({
    parent: projectLocation,
    inputConfig: inputConfig,
  });

  console.log('Processing operation name: ', operation.name);

  // synchronous check of operation status
  const [result] = await response.promise();
  console.log('Processing done.');
  console.log('Results of the processing:');

  for (const i in result.statuses) {
    console.log(
      'Status of processing ',
      i,
      'of the csv:',
      result.statuses[i]
    );

    // Check the status of reference image
    if (result.statuses[i].code === 0) {
      console.log(result.referenceImages[i]);
    } else {
      console.log('No reference image.');
    }
  }
}
importProductSets();

Python

def import_product_sets(project_id, location, gcs_uri):
    """Import images of different products in the product set.
    Args:
        project_id: Id of the project.
        location: A compute region name.
        gcs_uri: Google Cloud Storage URI.
            Target files must be in Product Search CSV format.
    """
    client = vision.ProductSearchClient()

    # A resource that represents Google Cloud Platform location.
    location_path = f"projects/{project_id}/locations/{location}"

    # Set the input configuration along with Google Cloud Storage URI
    gcs_source = vision.ImportProductSetsGcsSource(
        csv_file_uri=gcs_uri)
    input_config = vision.ImportProductSetsInputConfig(
        gcs_source=gcs_source)

    # Import the product sets from the input URI.
    response = client.import_product_sets(
        parent=location_path, input_config=input_config)

    print('Processing operation name: {}'.format(response.operation.name))
    # synchronous check of operation status
    result = response.result()
    print('Processing done.')

    for i, status in enumerate(result.statuses):
        print('Status of processing line {} of the csv: {}'.format(
            i, status))
        # Check the status of reference image
        # `0` is the code for OK in google.rpc.Code.
        if status.code == 0:
            reference_image = result.reference_images[i]
            print(reference_image)
        else:
            print('Status code not OK: {}'.format(status.message))

What's next

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