import com.google.api.gax.rpc.ApiException;
import com.google.cloud.aiplatform.v1.EndpointName;
import com.google.cloud.aiplatform.v1.PredictResponse;
import com.google.cloud.aiplatform.v1.PredictionServiceClient;
import com.google.cloud.aiplatform.v1.PredictionServiceSettings;
import com.google.gson.Gson;
import com.google.protobuf.InvalidProtocolBufferException;
import com.google.protobuf.Value;
import com.google.protobuf.util.JsonFormat;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.Base64;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
public class EditImageOutpaintingMaskSample {
public static void main(String[] args) throws IOException {
// TODO(developer): Replace these variables before running the sample.
String projectId = "my-project-id";
String location = "us-central1";
String inputPath = "/path/to/my-input.png";
String maskPath = "/path/to/my-mask.png";
String prompt = ""; // The optional text prompt describing what you want to see inserted.
editImageOutpaintingMask(projectId, location, inputPath, maskPath, prompt);
}
// Edit an image using a mask file. Outpainting lets you expand the content of a base image to fit
// a larger or differently sized mask canvas.
public static PredictResponse editImageOutpaintingMask(
String projectId, String location, String inputPath, String maskPath, String prompt)
throws ApiException, IOException {
final String endpoint = String.format("%s-aiplatform.googleapis.com:443", location);
PredictionServiceSettings predictionServiceSettings =
PredictionServiceSettings.newBuilder().setEndpoint(endpoint).build();
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests.
try (PredictionServiceClient predictionServiceClient =
PredictionServiceClient.create(predictionServiceSettings)) {
final EndpointName endpointName =
EndpointName.ofProjectLocationPublisherModelName(
projectId, location, "google", "imagegeneration@006");
// Encode image and mask to Base64
String imageBase64 =
Base64.getEncoder().encodeToString(Files.readAllBytes(Paths.get(inputPath)));
String maskBase64 =
Base64.getEncoder().encodeToString(Files.readAllBytes(Paths.get(maskPath)));
// Create the image and image mask maps
Map<String, String> imageMap = new HashMap<>();
imageMap.put("bytesBase64Encoded", imageBase64);
Map<String, String> maskMap = new HashMap<>();
maskMap.put("bytesBase64Encoded", maskBase64);
Map<String, Map> imageMaskMap = new HashMap<>();
imageMaskMap.put("image", maskMap);
Map<String, Object> instancesMap = new HashMap<>();
instancesMap.put("prompt", prompt); // [ "prompt", "<my-prompt>" ]
instancesMap.put(
"image", imageMap); // [ "image", [ "bytesBase64Encoded", "iVBORw0KGgo...==" ] ]
instancesMap.put(
"mask",
imageMaskMap); // [ "mask", [ "image", [ "bytesBase64Encoded", "iJKDF0KGpl...==" ] ] ]
instancesMap.put("editMode", "outpainting"); // [ "editMode", "outpainting" ]
Value instances = mapToValue(instancesMap);
// Optional parameters
Map<String, Object> paramsMap = new HashMap<>();
paramsMap.put("sampleCount", 1);
Value parameters = mapToValue(paramsMap);
PredictResponse predictResponse =
predictionServiceClient.predict(
endpointName, Collections.singletonList(instances), parameters);
for (Value prediction : predictResponse.getPredictionsList()) {
Map<String, Value> fieldsMap = prediction.getStructValue().getFieldsMap();
if (fieldsMap.containsKey("bytesBase64Encoded")) {
String bytesBase64Encoded = fieldsMap.get("bytesBase64Encoded").getStringValue();
Path tmpPath = Files.createTempFile("imagen-", ".png");
Files.write(tmpPath, Base64.getDecoder().decode(bytesBase64Encoded));
System.out.format("Image file written to: %s\n", tmpPath.toUri());
}
}
return predictResponse;
}
}
private static Value mapToValue(Map<String, Object> map) throws InvalidProtocolBufferException {
Gson gson = new Gson();
String json = gson.toJson(map);
Value.Builder builder = Value.newBuilder();
JsonFormat.parser().merge(json, builder);
return builder.build();
}
}
