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feat: add Imagen watermarking and captions samples and tests (#9549)
* feat: add Imagen watermarking and captions samples and tests * add comment * remove parameter * Update aiplatform/src/main/java/aiplatform/imagen/VerifyImageWatermarkSample.java Co-authored-by: Sita Lakshmi Sangameswaran <[email protected]> * address feedback --------- Co-authored-by: Sita Lakshmi Sangameswaran <[email protected]>
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‎aiplatform/resources/dog_newspaper.png

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‎aiplatform/src/main/java/aiplatform/imagen/GetShortFormImageCaptionsSample.java

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/*
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* Copyright 2024 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package aiplatform.imagen;
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// [START generativeaionvertexai_imagen_get_short_form_image_captions]
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import com.google.api.gax.rpc.ApiException;
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import com.google.cloud.aiplatform.v1.EndpointName;
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import com.google.cloud.aiplatform.v1.PredictResponse;
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import com.google.cloud.aiplatform.v1.PredictionServiceClient;
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import com.google.cloud.aiplatform.v1.PredictionServiceSettings;
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import com.google.gson.Gson;
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import com.google.protobuf.InvalidProtocolBufferException;
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import com.google.protobuf.Value;
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import com.google.protobuf.util.JsonFormat;
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import java.io.IOException;
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import java.nio.file.Files;
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import java.nio.file.Paths;
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import java.util.Base64;
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import java.util.Collections;
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import java.util.HashMap;
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import java.util.Map;
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public class GetShortFormImageCaptionsSample {
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public static void main(String[] args) throws IOException {
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// TODO(developer): Replace these variables before running the sample.
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String projectId = "my-project-id";
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String location = "us-central1";
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String inputPath = "/path/to/my-input.png";
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getShortFormImageCaptions(projectId, location, inputPath);
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}
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// Get the short form captions for an image
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public static PredictResponse getShortFormImageCaptions(
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String projectId, String location, String inputPath) throws ApiException, IOException {
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final String endpoint = String.format("%s-aiplatform.googleapis.com:443", location);
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PredictionServiceSettings predictionServiceSettings =
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PredictionServiceSettings.newBuilder().setEndpoint(endpoint).build();
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// Initialize client that will be used to send requests. This client only needs to be created
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// once, and can be reused for multiple requests.
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try (PredictionServiceClient predictionServiceClient =
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PredictionServiceClient.create(predictionServiceSettings)) {
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final EndpointName endpointName =
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EndpointName.ofProjectLocationPublisherModelName(
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projectId, location, "google", "imagetext@001");
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// Encode image to Base64
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String imageBase64 =
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Base64.getEncoder().encodeToString(Files.readAllBytes(Paths.get(inputPath)));
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// Create the image map
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Map<String, String> imageMap = new HashMap<>();
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imageMap.put("bytesBase64Encoded", imageBase64);
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Map<String, Object> instancesMap = new HashMap<>();
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instancesMap.put("image", imageMap);
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Value instances = mapToValue(instancesMap);
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// Optional parameters
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Map<String, Object> paramsMap = new HashMap<>();
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paramsMap.put("language", "en");
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paramsMap.put("sampleCount", 2);
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Value parameters = mapToValue(paramsMap);
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PredictResponse predictResponse =
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predictionServiceClient.predict(
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endpointName, Collections.singletonList(instances), parameters);
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for (Value prediction : predictResponse.getPredictionsList()) {
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System.out.println(prediction.getStringValue());
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}
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return predictResponse;
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}
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}
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private static Value mapToValue(Map<String, Object> map) throws InvalidProtocolBufferException {
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Gson gson = new Gson();
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String json = gson.toJson(map);
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Value.Builder builder = Value.newBuilder();
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JsonFormat.parser().merge(json, builder);
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return builder.build();
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}
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}
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// [END generativeaionvertexai_imagen_get_short_form_image_captions]

‎aiplatform/src/main/java/aiplatform/imagen/GetShortFormImageResponsesSample.java

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/*
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* Copyright 2024 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package aiplatform.imagen;
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// [START generativeaionvertexai_imagen_get_short_form_image_responses]
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import com.google.api.gax.rpc.ApiException;
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import com.google.cloud.aiplatform.v1.EndpointName;
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import com.google.cloud.aiplatform.v1.PredictResponse;
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import com.google.cloud.aiplatform.v1.PredictionServiceClient;
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import com.google.cloud.aiplatform.v1.PredictionServiceSettings;
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import com.google.gson.Gson;
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import com.google.protobuf.InvalidProtocolBufferException;
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import com.google.protobuf.Value;
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import com.google.protobuf.util.JsonFormat;
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import java.io.IOException;
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import java.nio.file.Files;
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import java.nio.file.Paths;
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import java.util.Base64;
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import java.util.Collections;
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import java.util.HashMap;
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import java.util.Map;
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public class GetShortFormImageResponsesSample {
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public static void main(String[] args) throws IOException {
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// TODO(developer): Replace these variables before running the sample.
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String projectId = "my-project-id";
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String location = "us-central1";
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String inputPath = "/path/to/my-input.png";
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String prompt = ""; // The question about the contents of the image.
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getShortFormImageResponses(projectId, location, inputPath, prompt);
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}
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// Get the short form responses to a question about an image
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public static PredictResponse getShortFormImageResponses(
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String projectId, String location, String inputPath, String prompt)
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throws ApiException, IOException {
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final String endpoint = String.format("%s-aiplatform.googleapis.com:443", location);
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PredictionServiceSettings predictionServiceSettings =
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PredictionServiceSettings.newBuilder().setEndpoint(endpoint).build();
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// Initialize client that will be used to send requests. This client only needs to be created
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// once, and can be reused for multiple requests.
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try (PredictionServiceClient predictionServiceClient =
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PredictionServiceClient.create(predictionServiceSettings)) {
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final EndpointName endpointName =
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EndpointName.ofProjectLocationPublisherModelName(
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projectId, location, "google", "imagetext@001");
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// Encode image to Base64
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String imageBase64 =
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Base64.getEncoder().encodeToString(Files.readAllBytes(Paths.get(inputPath)));
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// Create the image map
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Map<String, String> imageMap = new HashMap<>();
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imageMap.put("bytesBase64Encoded", imageBase64);
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Map<String, Object> instancesMap = new HashMap<>();
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instancesMap.put("prompt", prompt);
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instancesMap.put("image", imageMap);
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Value instances = mapToValue(instancesMap);
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// Optional parameters
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Map<String, Object> paramsMap = new HashMap<>();
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paramsMap.put("sampleCount", 2);
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Value parameters = mapToValue(paramsMap);
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PredictResponse predictResponse =
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predictionServiceClient.predict(
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endpointName, Collections.singletonList(instances), parameters);
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for (Value prediction : predictResponse.getPredictionsList()) {
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System.out.println(prediction.getStringValue());
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}
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return predictResponse;
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}
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}
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private static Value mapToValue(Map<String, Object> map) throws InvalidProtocolBufferException {
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Gson gson = new Gson();
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String json = gson.toJson(map);
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Value.Builder builder = Value.newBuilder();
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JsonFormat.parser().merge(json, builder);
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return builder.build();
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}
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}
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// [END generativeaionvertexai_imagen_get_short_form_image_responses]

‎aiplatform/src/main/java/aiplatform/imagen/VerifyImageWatermarkSample.java

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/*
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* Copyright 2024 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package aiplatform.imagen;
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// [START generativeaionvertexai_imagen_verify_image_watermark]
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import com.google.api.gax.rpc.ApiException;
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import com.google.cloud.aiplatform.v1.EndpointName;
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import com.google.cloud.aiplatform.v1.PredictResponse;
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import com.google.cloud.aiplatform.v1.PredictionServiceClient;
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import com.google.cloud.aiplatform.v1.PredictionServiceSettings;
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import com.google.gson.Gson;
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import com.google.protobuf.InvalidProtocolBufferException;
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import com.google.protobuf.Value;
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import com.google.protobuf.util.JsonFormat;
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import java.io.IOException;
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import java.nio.file.Files;
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import java.nio.file.Paths;
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import java.util.Base64;
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import java.util.Collections;
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import java.util.HashMap;
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import java.util.Map;
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public class VerifyImageWatermarkSample {
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public static void main(String[] args) throws IOException {
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// TODO(developer): Replace these variables before running the sample.
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String projectId = "my-project-id";
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String location = "us-central1";
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String inputPath = "/path/to/my-input.png";
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verifyImageWatermark(projectId, location, inputPath);
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}
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// Verify if an image contains a digital watermark. By default, a non-visible, digital watermark
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// (called a SynthID) is added to images generated by a model version that supports
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// watermark generation.
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public static PredictResponse verifyImageWatermark(
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String projectId, String location, String inputPath) throws ApiException, IOException {
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final String endpoint = String.format("%s-aiplatform.googleapis.com:443", location);
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PredictionServiceSettings predictionServiceSettings =
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PredictionServiceSettings.newBuilder().setEndpoint(endpoint).build();
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// Initialize client that will be used to send requests. This client only needs to be created
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// once, and can be reused for multiple requests.
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try (PredictionServiceClient predictionServiceClient =
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PredictionServiceClient.create(predictionServiceSettings)) {
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final EndpointName endpointName =
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EndpointName.ofProjectLocationPublisherModelName(
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projectId, location, "google", "imageverification@001");
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// Encode image to Base64
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String imageBase64 =
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Base64.getEncoder().encodeToString(Files.readAllBytes(Paths.get(inputPath)));
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// Create the image map
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Map<String, String> imageMap = new HashMap<>();
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imageMap.put("bytesBase64Encoded", imageBase64);
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Map<String, Object> instancesMap = new HashMap<>();
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instancesMap.put("image", imageMap);
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Value instances = mapToValue(instancesMap);
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// Optional parameters
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Map<String, Object> paramsMap = new HashMap<>();
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Value parameters = mapToValue(paramsMap);
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PredictResponse predictResponse =
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predictionServiceClient.predict(
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endpointName, Collections.singletonList(instances), parameters);
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for (Value prediction : predictResponse.getPredictionsList()) {
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Map<String, Value> fieldsMap = prediction.getStructValue().getFieldsMap();
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if (fieldsMap.containsKey("decision")) {
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// "ACCEPT" if the image contains a digital watermark
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// "REJECT" if the image does not contain a digital watermark
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System.out.format(
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"Watermark verification result: %s", fieldsMap.get("decision").getStringValue());
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}
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}
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return predictResponse;
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}
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}
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private static Value mapToValue(Map<String, Object> map) throws InvalidProtocolBufferException {
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Gson gson = new Gson();
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String json = gson.toJson(map);
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Value.Builder builder = Value.newBuilder();
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JsonFormat.parser().merge(json, builder);
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return builder.build();
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}
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}
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// [END generativeaionvertexai_imagen_verify_image_watermark]

‎aiplatform/src/test/java/aiplatform/imagen/GetShortFormImageCaptionsSampleTest.java

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/*
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* Copyright 2024 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package aiplatform.imagen;
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import static com.google.common.truth.Truth.assertThat;
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import static junit.framework.TestCase.assertNotNull;
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import com.google.cloud.aiplatform.v1.PredictResponse;
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import com.google.protobuf.Value;
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import java.io.IOException;
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import org.junit.BeforeClass;
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import org.junit.Test;
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import org.junit.runner.RunWith;
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import org.junit.runners.JUnit4;
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@RunWith(JUnit4.class)
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public class GetShortFormImageCaptionsSampleTest {
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private static final String PROJECT = System.getenv("GOOGLE_CLOUD_PROJECT");
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private static final String INPUT_FILE = "resources/cat.png";
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private static void requireEnvVar(String varName) {
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String errorMessage =
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String.format("Environment variable '%s' is required to perform these tests.", varName);
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assertNotNull(errorMessage, System.getenv(varName));
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}
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@BeforeClass
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public static void checkRequirements() {
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requireEnvVar("GOOGLE_APPLICATION_CREDENTIALS");
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requireEnvVar("GOOGLE_CLOUD_PROJECT");
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}
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@Test
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public void testGetShortFormImageCaptionsSample() throws IOException {
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PredictResponse response =
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GetShortFormImageCaptionsSample.getShortFormImageCaptions(
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PROJECT, "us-central1", INPUT_FILE);
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assertThat(response).isNotNull();
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for (Value prediction : response.getPredictionsList()) {
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assertThat(prediction.getStringValue().contains("cat"));
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}
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}
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}

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