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Example 16 with GcsDestination

use of com.google.cloud.datalabeling.v1beta1.GcsDestination in project java-aiplatform by googleapis.

the class CreateBatchPredictionJobVideoObjectTrackingSample method batchPredictionJobVideoObjectTracking.

static void batchPredictionJobVideoObjectTracking(String batchPredictionDisplayName, String modelId, String gcsSourceUri, String gcsDestinationOutputUriPrefix, String project) throws IOException {
    JobServiceSettings jobServiceSettings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient jobServiceClient = JobServiceClient.create(jobServiceSettings)) {
        String location = "us-central1";
        LocationName locationName = LocationName.of(project, location);
        ModelName modelName = ModelName.of(project, location, modelId);
        VideoObjectTrackingPredictionParams modelParamsObj = VideoObjectTrackingPredictionParams.newBuilder().setConfidenceThreshold(((float) 0.5)).build();
        Value modelParameters = ValueConverter.toValue(modelParamsObj);
        GcsSource.Builder gcsSource = GcsSource.newBuilder();
        gcsSource.addUris(gcsSourceUri);
        InputConfig inputConfig = InputConfig.newBuilder().setInstancesFormat("jsonl").setGcsSource(gcsSource).build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setPredictionsFormat("jsonl").setGcsDestination(gcsDestination).build();
        BatchPredictionJob batchPredictionJob = BatchPredictionJob.newBuilder().setDisplayName(batchPredictionDisplayName).setModel(modelName.toString()).setModelParameters(modelParameters).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
        BatchPredictionJob batchPredictionJobResponse = jobServiceClient.createBatchPredictionJob(locationName, batchPredictionJob);
        System.out.println("Create Batch Prediction Job Video Object Tracking Response");
        System.out.format("\tName: %s\n", batchPredictionJobResponse.getName());
        System.out.format("\tDisplay Name: %s\n", batchPredictionJobResponse.getDisplayName());
        System.out.format("\tModel %s\n", batchPredictionJobResponse.getModel());
        System.out.format("\tModel Parameters: %s\n", batchPredictionJobResponse.getModelParameters());
        System.out.format("\tState: %s\n", batchPredictionJobResponse.getState());
        System.out.format("\tCreate Time: %s\n", batchPredictionJobResponse.getCreateTime());
        System.out.format("\tStart Time: %s\n", batchPredictionJobResponse.getStartTime());
        System.out.format("\tEnd Time: %s\n", batchPredictionJobResponse.getEndTime());
        System.out.format("\tUpdate Time: %s\n", batchPredictionJobResponse.getUpdateTime());
        System.out.format("\tLabels: %s\n", batchPredictionJobResponse.getLabelsMap());
        InputConfig inputConfigResponse = batchPredictionJobResponse.getInputConfig();
        System.out.println("\tInput Config");
        System.out.format("\t\tInstances Format: %s\n", inputConfigResponse.getInstancesFormat());
        GcsSource gcsSourceResponse = inputConfigResponse.getGcsSource();
        System.out.println("\t\tGcs Source");
        System.out.format("\t\t\tUris %s\n", gcsSourceResponse.getUrisList());
        BigQuerySource bigQuerySource = inputConfigResponse.getBigquerySource();
        System.out.println("\t\tBigquery Source");
        System.out.format("\t\t\tInput_uri: %s\n", bigQuerySource.getInputUri());
        OutputConfig outputConfigResponse = batchPredictionJobResponse.getOutputConfig();
        System.out.println("\tOutput Config");
        System.out.format("\t\tPredictions Format: %s\n", outputConfigResponse.getPredictionsFormat());
        GcsDestination gcsDestinationResponse = outputConfigResponse.getGcsDestination();
        System.out.println("\t\tGcs Destination");
        System.out.format("\t\t\tOutput Uri Prefix: %s\n", gcsDestinationResponse.getOutputUriPrefix());
        BigQueryDestination bigQueryDestination = outputConfigResponse.getBigqueryDestination();
        System.out.println("\t\tBig Query Destination");
        System.out.format("\t\t\tOutput Uri: %s\n", bigQueryDestination.getOutputUri());
        BatchDedicatedResources batchDedicatedResources = batchPredictionJobResponse.getDedicatedResources();
        System.out.println("\tBatch Dedicated Resources");
        System.out.format("\t\tStarting Replica Count: %s\n", batchDedicatedResources.getStartingReplicaCount());
        System.out.format("\t\tMax Replica Count: %s\n", batchDedicatedResources.getMaxReplicaCount());
        MachineSpec machineSpec = batchDedicatedResources.getMachineSpec();
        System.out.println("\t\tMachine Spec");
        System.out.format("\t\t\tMachine Type: %s\n", machineSpec.getMachineType());
        System.out.format("\t\t\tAccelerator Type: %s\n", machineSpec.getAcceleratorType());
        System.out.format("\t\t\tAccelerator Count: %s\n", machineSpec.getAcceleratorCount());
        ManualBatchTuningParameters manualBatchTuningParameters = batchPredictionJobResponse.getManualBatchTuningParameters();
        System.out.println("\tManual Batch Tuning Parameters");
        System.out.format("\t\tBatch Size: %s\n", manualBatchTuningParameters.getBatchSize());
        OutputInfo outputInfo = batchPredictionJobResponse.getOutputInfo();
        System.out.println("\tOutput Info");
        System.out.format("\t\tGcs Output Directory: %s\n", outputInfo.getGcsOutputDirectory());
        System.out.format("\t\tBigquery Output Dataset: %s\n", outputInfo.getBigqueryOutputDataset());
        Status status = batchPredictionJobResponse.getError();
        System.out.println("\tError");
        System.out.format("\t\tCode: %s\n", status.getCode());
        System.out.format("\t\tMessage: %s\n", status.getMessage());
        List<Any> details = status.getDetailsList();
        for (Status partialFailure : batchPredictionJobResponse.getPartialFailuresList()) {
            System.out.println("\tPartial Failure");
            System.out.format("\t\tCode: %s\n", partialFailure.getCode());
            System.out.format("\t\tMessage: %s\n", partialFailure.getMessage());
            List<Any> partialFailureDetailsList = partialFailure.getDetailsList();
        }
        ResourcesConsumed resourcesConsumed = batchPredictionJobResponse.getResourcesConsumed();
        System.out.println("\tResources Consumed");
        System.out.format("\t\tReplica Hours: %s\n", resourcesConsumed.getReplicaHours());
        CompletionStats completionStats = batchPredictionJobResponse.getCompletionStats();
        System.out.println("\tCompletion Stats");
        System.out.format("\t\tSuccessful Count: %s\n", completionStats.getSuccessfulCount());
        System.out.format("\t\tFailed Count: %s\n", completionStats.getFailedCount());
        System.out.format("\t\tIncomplete Count: %s\n", completionStats.getIncompleteCount());
    }
}
Also used : Status(com.google.rpc.Status) JobServiceSettings(com.google.cloud.aiplatform.v1.JobServiceSettings) VideoObjectTrackingPredictionParams(com.google.cloud.aiplatform.v1.schema.predict.params.VideoObjectTrackingPredictionParams) ModelName(com.google.cloud.aiplatform.v1.ModelName) GcsSource(com.google.cloud.aiplatform.v1.GcsSource) BatchPredictionJob(com.google.cloud.aiplatform.v1.BatchPredictionJob) ManualBatchTuningParameters(com.google.cloud.aiplatform.v1.ManualBatchTuningParameters) JobServiceClient(com.google.cloud.aiplatform.v1.JobServiceClient) MachineSpec(com.google.cloud.aiplatform.v1.MachineSpec) BigQueryDestination(com.google.cloud.aiplatform.v1.BigQueryDestination) Any(com.google.protobuf.Any) LocationName(com.google.cloud.aiplatform.v1.LocationName) OutputInfo(com.google.cloud.aiplatform.v1.BatchPredictionJob.OutputInfo) BatchDedicatedResources(com.google.cloud.aiplatform.v1.BatchDedicatedResources) OutputConfig(com.google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig) ResourcesConsumed(com.google.cloud.aiplatform.v1.ResourcesConsumed) Value(com.google.protobuf.Value) InputConfig(com.google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig) GcsDestination(com.google.cloud.aiplatform.v1.GcsDestination) BigQuerySource(com.google.cloud.aiplatform.v1.BigQuerySource) CompletionStats(com.google.cloud.aiplatform.v1.CompletionStats)

Example 17 with GcsDestination

use of com.google.cloud.datalabeling.v1beta1.GcsDestination 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();
            }
        }
    }
}
Also used : BatchProcessDocumentsResponse(com.google.cloud.documentai.v1beta2.BatchProcessDocumentsResponse) DocumentUnderstandingServiceClient(com.google.cloud.documentai.v1beta2.DocumentUnderstandingServiceClient) GcsSource(com.google.cloud.documentai.v1beta2.GcsSource) Page(com.google.api.gax.paging.Page) Document(com.google.cloud.documentai.v1beta2.Document) TableExtractionParams(com.google.cloud.documentai.v1beta2.TableExtractionParams) InputConfig(com.google.cloud.documentai.v1beta2.InputConfig) FileReader(java.io.FileReader) BatchProcessDocumentsRequest(com.google.cloud.documentai.v1beta2.BatchProcessDocumentsRequest) OperationMetadata(com.google.cloud.documentai.v1beta2.OperationMetadata) ProcessDocumentRequest(com.google.cloud.documentai.v1beta2.ProcessDocumentRequest) Blob(com.google.cloud.storage.Blob) TableBoundHint(com.google.cloud.documentai.v1beta2.TableBoundHint) TableBoundHint(com.google.cloud.documentai.v1beta2.TableBoundHint) OutputConfig(com.google.cloud.documentai.v1beta2.OutputConfig) Storage(com.google.cloud.storage.Storage) Bucket(com.google.cloud.storage.Bucket) GcsDestination(com.google.cloud.documentai.v1beta2.GcsDestination) File(java.io.File)

Example 18 with GcsDestination

use of com.google.cloud.datalabeling.v1beta1.GcsDestination 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");
        }
    }
}
Also used : GcsSource(com.google.cloud.vision.v1.GcsSource) Matcher(java.util.regex.Matcher) AsyncAnnotateFileResponse(com.google.cloud.vision.v1.AsyncAnnotateFileResponse) ImageAnnotatorClient(com.google.cloud.vision.v1.ImageAnnotatorClient) Builder(com.google.cloud.vision.v1.AnnotateFileResponse.Builder) ArrayList(java.util.ArrayList) ByteString(com.google.protobuf.ByteString) Feature(com.google.cloud.vision.v1.Feature) AsyncBatchAnnotateFilesResponse(com.google.cloud.vision.v1.AsyncBatchAnnotateFilesResponse) AnnotateFileResponse(com.google.cloud.vision.v1.AnnotateFileResponse) AsyncAnnotateFileResponse(com.google.cloud.vision.v1.AsyncAnnotateFileResponse) InputConfig(com.google.cloud.vision.v1.InputConfig) OperationMetadata(com.google.cloud.vision.v1.OperationMetadata) Pattern(java.util.regex.Pattern) Blob(com.google.cloud.storage.Blob) OutputConfig(com.google.cloud.vision.v1.OutputConfig) Storage(com.google.cloud.storage.Storage) Bucket(com.google.cloud.storage.Bucket) AnnotateImageResponse(com.google.cloud.vision.v1.AnnotateImageResponse) AsyncAnnotateFileRequest(com.google.cloud.vision.v1.AsyncAnnotateFileRequest) GcsDestination(com.google.cloud.vision.v1.GcsDestination)

Example 19 with GcsDestination

use of com.google.cloud.datalabeling.v1beta1.GcsDestination 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());
    }
}
Also used : Pattern(java.util.regex.Pattern) Blob(com.google.cloud.storage.Blob) AsyncBatchAnnotateImagesRequest(com.google.cloud.vision.v1p4beta1.AsyncBatchAnnotateImagesRequest) Matcher(java.util.regex.Matcher) ImageAnnotatorClient(com.google.cloud.vision.v1p4beta1.ImageAnnotatorClient) Builder(com.google.cloud.vision.v1p4beta1.BatchAnnotateImagesResponse.Builder) ArrayList(java.util.ArrayList) Image(com.google.cloud.vision.v1p4beta1.Image) Feature(com.google.cloud.vision.v1p4beta1.Feature) AnnotateImageRequest(com.google.cloud.vision.v1p4beta1.AnnotateImageRequest) OutputConfig(com.google.cloud.vision.v1p4beta1.OutputConfig) Storage(com.google.cloud.storage.Storage) Bucket(com.google.cloud.storage.Bucket) AsyncBatchAnnotateImagesResponse(com.google.cloud.vision.v1p4beta1.AsyncBatchAnnotateImagesResponse) ImageSource(com.google.cloud.vision.v1p4beta1.ImageSource) GcsDestination(com.google.cloud.vision.v1p4beta1.GcsDestination) OperationMetadata(com.google.cloud.vision.v1p4beta1.OperationMetadata) AsyncBatchAnnotateImagesResponse(com.google.cloud.vision.v1p4beta1.AsyncBatchAnnotateImagesResponse) BatchAnnotateImagesResponse(com.google.cloud.vision.v1p4beta1.BatchAnnotateImagesResponse)

Example 20 with GcsDestination

use of com.google.cloud.datalabeling.v1beta1.GcsDestination in project java-vision by googleapis.

the class AsyncBatchAnnotateImages method asyncBatchAnnotateImages.

public static void asyncBatchAnnotateImages(String inputImageUri, String outputUri) throws IOException, ExecutionException, InterruptedException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (ImageAnnotatorClient imageAnnotatorClient = ImageAnnotatorClient.create()) {
        // You can send multiple images to be annotated, this sample demonstrates how to do this with
        // one image. If you want to use multiple images, you have to create a `AnnotateImageRequest`
        // object for each image that you want annotated.
        // First specify where the vision api can find the image
        ImageSource source = ImageSource.newBuilder().setImageUri(inputImageUri).build();
        Image image = Image.newBuilder().setSource(source).build();
        // Set the type of annotation you want to perform on the image
        // https://cloud.google.com/vision/docs/reference/rpc/google.cloud.vision.v1#google.cloud.vision.v1.Feature.Type
        Feature feature = Feature.newBuilder().setType(Feature.Type.LABEL_DETECTION).build();
        // Build the request object for that one image. Note: for additional images you have to create
        // additional `AnnotateImageRequest` objects and store them in a list to be used below.
        AnnotateImageRequest imageRequest = AnnotateImageRequest.newBuilder().setImage(image).addFeatures(feature).build();
        // Set where to store the results for the images that will be annotated.
        GcsDestination gcsDestination = GcsDestination.newBuilder().setUri(outputUri).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).setBatchSize(// The max number of responses to output in each JSON file
        2).build();
        // Add each `AnnotateImageRequest` object to the batch request and add the output config.
        AsyncBatchAnnotateImagesRequest request = AsyncBatchAnnotateImagesRequest.newBuilder().addRequests(imageRequest).setOutputConfig(outputConfig).build();
        // Make the asynchronous batch request.
        AsyncBatchAnnotateImagesResponse response = imageAnnotatorClient.asyncBatchAnnotateImagesAsync(request).get();
        // The output is written to GCS with the provided output_uri as prefix
        String gcsOutputUri = response.getOutputConfig().getGcsDestination().getUri();
        System.out.format("Output written to GCS with prefix: %s%n", gcsOutputUri);
    }
}
Also used : AnnotateImageRequest(com.google.cloud.vision.v1.AnnotateImageRequest) OutputConfig(com.google.cloud.vision.v1.OutputConfig) AsyncBatchAnnotateImagesRequest(com.google.cloud.vision.v1.AsyncBatchAnnotateImagesRequest) ImageAnnotatorClient(com.google.cloud.vision.v1.ImageAnnotatorClient) AsyncBatchAnnotateImagesResponse(com.google.cloud.vision.v1.AsyncBatchAnnotateImagesResponse) ImageSource(com.google.cloud.vision.v1.ImageSource) Image(com.google.cloud.vision.v1.Image) GcsDestination(com.google.cloud.vision.v1.GcsDestination) Feature(com.google.cloud.vision.v1.Feature)

Aggregations

GcsDestination (com.google.cloud.aiplatform.v1.GcsDestination)12 BatchPredictionJob (com.google.cloud.aiplatform.v1.BatchPredictionJob)8 GcsSource (com.google.cloud.aiplatform.v1.GcsSource)8 JobServiceClient (com.google.cloud.aiplatform.v1.JobServiceClient)8 JobServiceSettings (com.google.cloud.aiplatform.v1.JobServiceSettings)8 LocationName (com.google.cloud.aiplatform.v1.LocationName)8 ModelName (com.google.cloud.aiplatform.v1.ModelName)5 Value (com.google.protobuf.Value)5 BatchTranslateMetadata (com.google.cloud.translate.v3.BatchTranslateMetadata)4 BatchTranslateResponse (com.google.cloud.translate.v3.BatchTranslateResponse)4 BatchTranslateTextRequest (com.google.cloud.translate.v3.BatchTranslateTextRequest)4 GcsDestination (com.google.cloud.translate.v3.GcsDestination)4 GcsSource (com.google.cloud.translate.v3.GcsSource)4 InputConfig (com.google.cloud.translate.v3.InputConfig)4 LocationName (com.google.cloud.translate.v3.LocationName)4 OutputConfig (com.google.cloud.translate.v3.OutputConfig)4 TranslationServiceClient (com.google.cloud.translate.v3.TranslationServiceClient)4 GcsDestination (com.google.cloud.vision.v1.GcsDestination)4 ApiException (com.google.api.gax.rpc.ApiException)3 BatchDedicatedResources (com.google.cloud.aiplatform.v1.BatchDedicatedResources)3