use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class VisionClassificationPredict method predict.
static void predict(String projectId, String modelId, String filePath) throws IOException {
// the "close" method on the client to safely clean up any remaining background resources.
try (PredictionServiceClient client = PredictionServiceClient.create()) {
// Get the full path of the model.
ModelName name = ModelName.of(projectId, "us-central1", modelId);
ByteString content = ByteString.copyFrom(Files.readAllBytes(Paths.get(filePath)));
Image image = Image.newBuilder().setImageBytes(content).build();
ExamplePayload payload = ExamplePayload.newBuilder().setImage(image).build();
PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).putParams("score_threshold", // [0.0-1.0] Only produce results higher than this value
"0.8").build();
PredictResponse response = client.predict(predictRequest);
for (AnnotationPayload annotationPayload : response.getPayloadList()) {
System.out.format("Predicted class name: %s\n", annotationPayload.getDisplayName());
System.out.format("Predicted class score: %.2f\n", annotationPayload.getClassification().getScore());
}
}
}
use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class VisionObjectDetectionDeployModelNodeCount method visionObjectDetectionDeployModelNodeCount.
// Deploy a model for prediction with a specified node count (can be used to redeploy a model)
static void visionObjectDetectionDeployModelNodeCount(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
ImageObjectDetectionModelDeploymentMetadata metadata = ImageObjectDetectionModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).setImageObjectDetectionModelDeploymentMetadata(metadata).build();
OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
future.get();
System.out.println("Model deployment finished");
}
}
use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class VisionObjectDetectionPredict method predict.
static void predict(String projectId, String modelId, String filePath) throws IOException {
// the "close" method on the client to safely clean up any remaining background resources.
try (PredictionServiceClient client = PredictionServiceClient.create()) {
// Get the full path of the model.
ModelName name = ModelName.of(projectId, "us-central1", modelId);
ByteString content = ByteString.copyFrom(Files.readAllBytes(Paths.get(filePath)));
Image image = Image.newBuilder().setImageBytes(content).build();
ExamplePayload payload = ExamplePayload.newBuilder().setImage(image).build();
PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).putParams("score_threshold", // [0.0-1.0] Only produce results higher than this value
"0.5").build();
PredictResponse response = client.predict(predictRequest);
for (AnnotationPayload annotationPayload : response.getPayloadList()) {
System.out.format("Predicted class name: %s\n", annotationPayload.getDisplayName());
System.out.format("Predicted class score: %.2f\n", annotationPayload.getImageObjectDetection().getScore());
BoundingPoly boundingPoly = annotationPayload.getImageObjectDetection().getBoundingBox();
System.out.println("Normalized Vertices:");
for (NormalizedVertex vertex : boundingPoly.getNormalizedVerticesList()) {
System.out.format("\tX: %.2f, Y: %.2f\n", vertex.getX(), vertex.getY());
}
}
}
}
use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class ClassificationUndeployModel method classificationUndeployModel.
// Deploy a model
static void classificationUndeployModel(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
// Build deploy model request.
UndeployModelRequest undeployModelRequest = UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
// Deploy a model with the deploy model request.
OperationFuture<Empty, OperationMetadata> future = client.undeployModelAsync(undeployModelRequest);
future.get();
// Display the deployment details of model.
System.out.println("Model undeploy finished");
}
}
use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class ClassificationDeployModel method classificationDeployModel.
// Deploy a model
static void classificationDeployModel(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
// Build deploy model request.
DeployModelRequest deployModelRequest = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
// Deploy a model with the deploy model request.
OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(deployModelRequest);
future.get();
// Display the deployment details of model.
System.out.println("Model deployment finished");
}
}
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