Examples with OperationMetadata com.google.cloud.automl.v1.OperationMetadata used on opensource projects

Example 21 with OperationMetadata

use of com.google.cloud.automl.v1.OperationMetadata in project java-document-ai by googleapis.

the class BatchParseFormBeta method batchParseFormGcs.

public static void batchParseFormGcs(String projectId, String location, String outputGcsBucketName, String outputGcsPrefix, String inputGcsUri) throws IOException, InterruptedException, ExecutionException, TimeoutException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DocumentUnderstandingServiceClient client = DocumentUnderstandingServiceClient.create()) {
        // Configure the request for processing the PDF
        String parent = String.format("projects/%s/locations/%s", projectId, location);
        // Improve form parsing results by providing key-value pair hints.
        // For each key hint, key is text that is likely to appear in the
        // document as a form field name (i.e. "DOB").
        // Value types are optional, but can be one or more of:
        // ADDRESS, LOCATION, ORGANIZATION, PERSON, PHONE_NUMBER, ID,
        // NUMBER, EMAIL, PRICE, TERMS, DATE, NAME
        KeyValuePairHint keyValuePairHint = KeyValuePairHint.newBuilder().setKey("Phone").addValueTypes("PHONE_NUMBER").build();
        KeyValuePairHint keyValuePairHint2 = KeyValuePairHint.newBuilder().setKey("Contact").addValueTypes("EMAIL").addValueTypes("NAME").build();
        // Setting enabled=True enables form extraction
        FormExtractionParams params = FormExtractionParams.newBuilder().setEnabled(true).addKeyValuePairHints(keyValuePairHint).addKeyValuePairHints(keyValuePairHint2).build();
        GcsSource inputUri = GcsSource.newBuilder().setUri(inputGcsUri).build();
        // mime_type can be application/pdf, image/tiff,
        // and image/gif, or application/json
        InputConfig config = InputConfig.newBuilder().setGcsSource(inputUri).setMimeType("application/pdf").build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setUri(String.format("gs://%s/%s", outputGcsBucketName, outputGcsPrefix)).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).setPagesPerShard(1).build();
        ProcessDocumentRequest request = ProcessDocumentRequest.newBuilder().setFormExtractionParams(params).setInputConfig(config).setOutputConfig(outputConfig).build();
        BatchProcessDocumentsRequest requests = BatchProcessDocumentsRequest.newBuilder().addRequests(request).setParent(parent).build();
        // Batch process document using a long-running operation.
        OperationFuture<BatchProcessDocumentsResponse, OperationMetadata> future = client.batchProcessDocumentsAsync(requests);
        // Wait for operation to complete.
        System.out.println("Waiting for operation to complete...");
        future.get(360, TimeUnit.SECONDS);
        System.out.println("Document processing complete.");
        Storage storage = StorageOptions.newBuilder().setProjectId(projectId).build().getService();
        Bucket bucket = storage.get(outputGcsBucketName);
        // List all of the files in the Storage bucket.
        Page<Blob> blobs = bucket.list(Storage.BlobListOption.currentDirectory(), Storage.BlobListOption.prefix(outputGcsPrefix));
        int idx = 0;
        for (Blob blob : blobs.iterateAll()) {
            if (!blob.isDirectory()) {
                System.out.printf("Fetched file #%d\n", ++idx);
                // Read the results
                // Download and store json data in a temp file.
                File tempFile = File.createTempFile("file", ".json");
                Blob fileInfo = storage.get(BlobId.of(outputGcsBucketName, blob.getName()));
                fileInfo.downloadTo(tempFile.toPath());
                // Parse json file into Document.
                FileReader reader = new FileReader(tempFile);
                Document.Builder builder = Document.newBuilder();
                JsonFormat.parser().merge(reader, builder);
                Document document = builder.build();
                // Get all of the document text as one big string.
                String text = document.getText();
                // Process the output.
                if (document.getPagesCount() > 0) {
                    Document.Page page1 = document.getPages(0);
                    for (Document.Page.FormField field : page1.getFormFieldsList()) {
                        String fieldName = getText(field.getFieldName(), text);
                        String fieldValue = getText(field.getFieldValue(), text);
                        System.out.println("Extracted form fields pair:");
                        System.out.printf("\t(%s, %s))", fieldName, fieldValue);
                    }
                }
                // Clean up temp file.
                tempFile.deleteOnExit();
            }
        }
    }
}

Example 22 with OperationMetadata

use of com.google.cloud.automl.v1.OperationMetadata in project java-document-ai by googleapis.

the class BatchParseTableBeta method batchParseTableGcs.

public static void batchParseTableGcs(String projectId, String location, String outputGcsBucketName, String outputGcsPrefix, String inputGcsUri) throws IOException, InterruptedException, ExecutionException, TimeoutException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DocumentUnderstandingServiceClient client = DocumentUnderstandingServiceClient.create()) {
        // Configure the request for processing the PDF
        String parent = String.format("projects/%s/locations/%s", projectId, location);
        TableBoundHint tableBoundHints = TableBoundHint.newBuilder().setBoundingBox(// Each vertice coordinate must be a number between 0 and 1
        BoundingPoly.newBuilder().addNormalizedVertices(NormalizedVertex.newBuilder().setX(0).setX(0).build()).addNormalizedVertices(NormalizedVertex.newBuilder().setX(1).setX(0).build()).addNormalizedVertices(NormalizedVertex.newBuilder().setX(1).setX(1).build()).addNormalizedVertices(NormalizedVertex.newBuilder().setX(0).setX(1).build()).build()).setPageNumber(1).build();
        TableExtractionParams params = TableExtractionParams.newBuilder().setEnabled(true).addTableBoundHints(tableBoundHints).build();
        GcsSource inputUri = GcsSource.newBuilder().setUri(inputGcsUri).build();
        // mime_type can be application/pdf, image/tiff,
        // and image/gif, or application/json
        InputConfig config = InputConfig.newBuilder().setGcsSource(inputUri).setMimeType("application/pdf").build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setUri(String.format("gs://%s/%s", outputGcsBucketName, outputGcsPrefix)).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).setPagesPerShard(1).build();
        ProcessDocumentRequest request = ProcessDocumentRequest.newBuilder().setTableExtractionParams(params).setInputConfig(config).setOutputConfig(outputConfig).build();
        BatchProcessDocumentsRequest requests = BatchProcessDocumentsRequest.newBuilder().addRequests(request).setParent(parent).build();
        // Batch process document using a long-running operation.
        OperationFuture<BatchProcessDocumentsResponse, OperationMetadata> future = client.batchProcessDocumentsAsync(requests);
        // Wait for operation to complete.
        System.out.println("Waiting for operation to complete...");
        future.get(360, TimeUnit.SECONDS);
        System.out.println("Document processing complete.");
        Storage storage = StorageOptions.newBuilder().setProjectId(projectId).build().getService();
        Bucket bucket = storage.get(outputGcsBucketName);
        // List all of the files in the Storage bucket.
        Page<Blob> blobs = bucket.list(Storage.BlobListOption.currentDirectory(), Storage.BlobListOption.prefix(outputGcsPrefix));
        int idx = 0;
        for (Blob blob : blobs.iterateAll()) {
            if (!blob.isDirectory()) {
                System.out.printf("Fetched file #%d\n", ++idx);
                // Read the results
                // Download and store json data in a temp file.
                File tempFile = File.createTempFile("file", ".json");
                Blob fileInfo = storage.get(BlobId.of(outputGcsBucketName, blob.getName()));
                fileInfo.downloadTo(tempFile.toPath());
                // Parse json file into Document.
                FileReader reader = new FileReader(tempFile);
                Document.Builder builder = Document.newBuilder();
                JsonFormat.parser().merge(reader, builder);
                Document document = builder.build();
                // Get all of the document text as one big string.
                String text = document.getText();
                // Process the output.
                if (document.getPagesCount() > 0) {
                    Document.Page page1 = document.getPages(0);
                    if (page1.getTablesCount() > 0) {
                        Document.Page.Table table = page1.getTables(0);
                        System.out.println("Results from first table processed:");
                        System.out.println("Header row:");
                        if (table.getHeaderRowsCount() > 0) {
                            Document.Page.Table.TableRow headerRow = table.getHeaderRows(0);
                            for (Document.Page.Table.TableCell tableCell : headerRow.getCellsList()) {
                                if (!tableCell.getLayout().getTextAnchor().getTextSegmentsList().isEmpty()) {
                                    // Extract shards from the text field
                                    // First shard in document doesn't have startIndex property
                                    List<Document.TextAnchor.TextSegment> textSegments = tableCell.getLayout().getTextAnchor().getTextSegmentsList();
                                    int startIdx = textSegments.size() > 0 ? (int) textSegments.get(0).getStartIndex() : 0;
                                    int endIdx = (int) textSegments.get(0).getEndIndex();
                                    System.out.printf("\t%s", text.substring(startIdx, endIdx));
                                }
                            }
                        }
                    }
                }
                // Clean up temp file.
                tempFile.deleteOnExit();
            }
        }
    }
}

Example 23 with OperationMetadata

use of com.google.cloud.automl.v1.OperationMetadata in project java-vision by googleapis.

the class Detect method detectDocumentsGcs.

// [END vision_fulltext_detection_gcs]
// [START vision_text_detection_pdf_gcs]
/**
 * Performs document text OCR with PDF/TIFF as source files on Google Cloud Storage.
 *
 * @param gcsSourcePath The path to the remote file on Google Cloud Storage to detect document
 *     text on.
 * @param gcsDestinationPath The path to the remote file on Google Cloud Storage to store the
 *     results on.
 * @throws Exception on errors while closing the client.
 */
public static void detectDocumentsGcs(String gcsSourcePath, String gcsDestinationPath) throws Exception {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
        List<AsyncAnnotateFileRequest> requests = new ArrayList<>();
        // Set the GCS source path for the remote file.
        GcsSource gcsSource = GcsSource.newBuilder().setUri(gcsSourcePath).build();
        // Create the configuration with the specified MIME (Multipurpose Internet Mail Extensions)
        // types
        InputConfig inputConfig = InputConfig.newBuilder().setMimeType(// Supported MimeTypes: "application/pdf", "image/tiff"
        "application/pdf").setGcsSource(gcsSource).build();
        // Set the GCS destination path for where to save the results.
        GcsDestination gcsDestination = GcsDestination.newBuilder().setUri(gcsDestinationPath).build();
        // Create the configuration for the System.output with the batch size.
        // The batch size sets how many pages should be grouped into each json System.output file.
        OutputConfig outputConfig = OutputConfig.newBuilder().setBatchSize(2).setGcsDestination(gcsDestination).build();
        // Select the Feature required by the vision API
        Feature feature = Feature.newBuilder().setType(Feature.Type.DOCUMENT_TEXT_DETECTION).build();
        // Build the OCR request
        AsyncAnnotateFileRequest request = AsyncAnnotateFileRequest.newBuilder().addFeatures(feature).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
        requests.add(request);
        // Perform the OCR request
        OperationFuture<AsyncBatchAnnotateFilesResponse, OperationMetadata> response = client.asyncBatchAnnotateFilesAsync(requests);
        System.out.println("Waiting for the operation to finish.");
        // Wait for the request to finish. (The result is not used, since the API saves the result to
        // the specified location on GCS.)
        List<AsyncAnnotateFileResponse> result = response.get(180, TimeUnit.SECONDS).getResponsesList();
        // Once the request has completed and the System.output has been
        // written to GCS, we can list all the System.output files.
        Storage storage = StorageOptions.getDefaultInstance().getService();
        // Get the destination location from the gcsDestinationPath
        Pattern pattern = Pattern.compile("gs://([^/]+)/(.+)");
        Matcher matcher = pattern.matcher(gcsDestinationPath);
        if (matcher.find()) {
            String bucketName = matcher.group(1);
            String prefix = matcher.group(2);
            // Get the list of objects with the given prefix from the GCS bucket
            Bucket bucket = storage.get(bucketName);
            com.google.api.gax.paging.Page<Blob> pageList = bucket.list(BlobListOption.prefix(prefix));
            Blob firstOutputFile = null;
            // List objects with the given prefix.
            System.out.println("Output files:");
            for (Blob blob : pageList.iterateAll()) {
                System.out.println(blob.getName());
                // the first two pages of the input file.
                if (firstOutputFile == null) {
                    firstOutputFile = blob;
                }
            }
            // Get the contents of the file and convert the JSON contents to an AnnotateFileResponse
            // object. If the Blob is small read all its content in one request
            // (Note: the file is a .json file)
            // Storage guide: https://cloud.google.com/storage/docs/downloading-objects
            String jsonContents = new String(firstOutputFile.getContent());
            Builder builder = AnnotateFileResponse.newBuilder();
            JsonFormat.parser().merge(jsonContents, builder);
            // Build the AnnotateFileResponse object
            AnnotateFileResponse annotateFileResponse = builder.build();
            // Parse through the object to get the actual response for the first page of the input file.
            AnnotateImageResponse annotateImageResponse = annotateFileResponse.getResponses(0);
            // Here we print the full text from the first page.
            // The response contains more information:
            // annotation/pages/blocks/paragraphs/words/symbols
            // including confidence score and bounding boxes
            System.out.format("%nText: %s%n", annotateImageResponse.getFullTextAnnotation().getText());
        } else {
            System.out.println("No MATCH");
        }
    }
}

Example 24 with OperationMetadata

use of com.google.cloud.automl.v1.OperationMetadata in project java-vision by googleapis.

the class AsyncBatchAnnotateImagesGcs method asyncBatchAnnotateImagesGcs.

// Performs asynchronous batch annotation of images on Google Cloud Storage
public static void asyncBatchAnnotateImagesGcs(String gcsSourcePath, String gcsDestinationPath) throws Exception {
    // String gcsDestinationPath = "gs://YOUR_BUCKET_ID/path_to_store_annotation";
    try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
        List<AnnotateImageRequest> requests = new ArrayList<>();
        ImageSource imgSource = ImageSource.newBuilder().setImageUri(gcsSourcePath).build();
        Image image = Image.newBuilder().setSource(imgSource).build();
        // Set the GCS destination path for where to save the results.
        GcsDestination gcsDestination = GcsDestination.newBuilder().setUri(gcsDestinationPath).build();
        // Create the configuration for the output with the batch size.
        // The batch size sets how many pages should be grouped into each json output file.
        OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).setBatchSize(2).build();
        // Select the Features required by the vision API
        Feature features = Feature.newBuilder().setType(Type.LABEL_DETECTION).setType(Type.TEXT_DETECTION).setType(Type.IMAGE_PROPERTIES).build();
        // Build the request
        AnnotateImageRequest annotateImageRequest = AnnotateImageRequest.newBuilder().setImage(image).addFeatures(features).build();
        requests.add(annotateImageRequest);
        AsyncBatchAnnotateImagesRequest request = AsyncBatchAnnotateImagesRequest.newBuilder().addAllRequests(requests).setOutputConfig(outputConfig).build();
        OperationFuture<AsyncBatchAnnotateImagesResponse, OperationMetadata> response = client.asyncBatchAnnotateImagesAsync(request);
        System.out.println("Waiting for the operation to finish.");
        // we're not processing the response, since we'll be reading the output from GCS.
        response.get(180, TimeUnit.SECONDS);
        // Once the request has completed and the output has been
        // written to GCS, we can list all the output files.
        Storage storage = StorageOptions.getDefaultInstance().getService();
        // Get the destination location from the gcsDestinationPath
        Pattern pattern = Pattern.compile("gs://([^/]+)/(.+)");
        Matcher matcher = pattern.matcher(gcsDestinationPath);
        if (matcher.find()) {
            String bucketName = matcher.group(1);
            String prefix = matcher.group(2);
            // Get the list of objects with the given prefix from the GCS bucket
            Bucket bucket = storage.get(bucketName);
            Page<Blob> pageList = bucket.list(BlobListOption.prefix(prefix));
            Blob firstOutputFile = null;
            // List objects with the given prefix.
            System.out.println("Output files:");
            for (Blob blob : pageList.iterateAll()) {
                System.out.println(blob.getName());
                // the first two image requests
                if (firstOutputFile == null) {
                    firstOutputFile = blob;
                }
            }
            // Get the contents of the file and convert the JSON contents to an
            // BatchAnnotateImagesResponse
            // object. If the Blob is small read all its content in one request
            // (Note: the file is a .json file)
            // Storage guide: https://cloud.google.com/storage/docs/downloading-objects
            String jsonContents = new String(firstOutputFile.getContent());
            Builder builder = BatchAnnotateImagesResponse.newBuilder();
            JsonFormat.parser().merge(jsonContents, builder);
            // Build the AnnotateFileResponse object
            BatchAnnotateImagesResponse batchAnnotateImagesResponse = builder.build();
            // Here we print the response for the first image
            // The response contains more information:
            // annotation/pages/blocks/paragraphs/words/symbols/colors
            // including confidence score and bounding boxes
            System.out.format("\nResponse: %s\n", batchAnnotateImagesResponse.getResponses(0));
        } else {
            System.out.println("No MATCH");
        }
    } catch (Exception e) {
        System.out.println("Error during asyncBatchAnnotateImagesGcs: \n" + e.toString());
    }
}

Example 25 with OperationMetadata

use of com.google.cloud.automl.v1.OperationMetadata in project java-automl by googleapis.

the class LanguageTextClassificationCreateDataset method createDataset.

// Create a dataset
static void createDataset(String projectId, String displayName) throws IOException, ExecutionException, InterruptedException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, "us-central1");
        // Specify the classification type
        // Types:
        // MultiLabel: Multiple labels are allowed for one example.
        // MultiClass: At most one label is allowed per example.
        ClassificationType classificationType = ClassificationType.MULTILABEL;
        // Specify the text classification type for the dataset.
        TextClassificationDatasetMetadata metadata = TextClassificationDatasetMetadata.newBuilder().setClassificationType(classificationType).build();
        Dataset dataset = Dataset.newBuilder().setDisplayName(displayName).setTextClassificationDatasetMetadata(metadata).build();
        OperationFuture<Dataset, OperationMetadata> future = client.createDatasetAsync(projectLocation, dataset);
        Dataset createdDataset = future.get();
        // Display the dataset information.
        System.out.format("Dataset name: %s\n", createdDataset.getName());
        // To get the dataset id, you have to parse it out of the `name` field. As dataset Ids are
        // required for other methods.
        // Name Form: `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`
        String[] names = createdDataset.getName().split("/");
        String datasetId = names[names.length - 1];
        System.out.format("Dataset id: %s\n", datasetId);
    }
}