ย้ายข้อมูลจาก Imagen ไปยังโมเดลรูปภาพของ Gemini ("Nano Banana")

import FirebaseAILogic

// Initialize the Gemini Developer API backend service.
let ai = FirebaseAI.firebaseAI(backend: .googleAI())

// Create an `ImagenModel` instance with a model that supports your use case.
let model = ai.imagenModel(modelName: "IMAGEN_MODEL_NAME")

// Provide an image generation prompt.
let prompt = "An astronaut riding a horse"

// To generate an image, call `generateImages` with the text prompt.
let response = try await model.generateImages(prompt: prompt)

// Handle the generated image.
guard let image = response.images.first else {
  fatalError("No image in the response.")
}
let uiImage = UIImage(data: image.data)

import FirebaseAILogic

// Initialize the Gemini Developer API backend service.
let ai = FirebaseAI.firebaseAI(backend: .googleAI())

// Create a `GenerativeModel` instance with a Gemini model that supports image output.
let model = ai.generativeModel(
  modelName: "GEMINI_IMAGE_MODEL_NAME",
  generationConfig: GenerationConfig(
    responseModalities: [.image],
    imageConfig: ImageConfig(aspectRatio: .landscape4x3)
  )
)

// Provide an image generation prompt.
let prompt = "An astronaut riding a horse"

// To generate an image, call `generateContent` with the text prompt.
let response = try await model.generateContent(prompt)

// Handle the case where no images were generated.
guard let inlineDataPart = response.inlineDataParts.first else {
  fatalError("No image in the response.")
}

// Process the image.
guard let uiImage = UIImage(data: inlineDataPart.data) else {
  fatalError("Failed to convert data to UIImage.")
}

// Initialize the Gemini Developer API backend service.
val ai = Firebase.ai(backend = GenerativeBackend.googleAI())

// Create an `ImagenModel` instance with an Imagen model that supports your use case.
val model = ai.imagenModel("IMAGEN_MODEL_NAME")

// Provide an image generation prompt.
val prompt = "An astronaut riding a horse"

// To generate an image, call `generateImages` with the text prompt.
val imageResponse = model.generateImages(prompt)

// Handle the generated image.
val image = imageResponse.images.first()

val bitmapImage = image.asBitmap()

// Initialize the Gemini Developer API backend service.
val ai = Firebase.ai(backend = GenerativeBackend.googleAI())

// Create a `GenerativeModel` instance with a Gemini model that supports image output.
val model = ai.generativeModel(
    modelName = "GEMINI_IMAGE_MODEL_NAME",
    generationConfig = generationConfig {
      responseModalities = listOf(ResponseModality.IMAGE),
      imageConfig = imageConfig {
        aspectRatio = AspectRatio.LANDSCAPE_4x3
      }
    }
)

// Provide an image generation prompt.
val prompt = "An astronaut riding a horse"

// To generate an image, call `generateContent` with the text prompt.
val imageResponse = model.generateContent(prompt)

if (imageResponse.finishReason == FinishReason.NO_IMAGE) {
  // Handle the case where no images were generated.
} else {
  // Handle the generated image.
  val bitmapImage = imageResponse.candidates.first().content.parts.filterIsInstance().firstOrNull()?.image
}

// Initialize the Gemini Developer API backend service.
// Create an `ImagenModel` instance with an Imagen model that supports your use case.
ImagenModel imagenModel = FirebaseAI.getInstance(GenerativeBackend.googleAI())
        .imagenModel(
                /* modelName */ "IMAGEN_MODEL_NAME");

ImagenModelFutures model = ImagenModelFutures.from(imagenModel);

// Provide an image generation prompt.
String prompt = "An astronaut riding a horse";

// To generate an image, call `generateImages` with the text prompt.
Futures.addCallback(model.generateImages(prompt), new FutureCallback<ImagenGenerationResponse>() {
    @Override
    public void onSuccess(ImagenGenerationResponse result) {
        if (result.getImages().isEmpty()) {
            Log.d("TAG", "No images generated");
        }
        Bitmap bitmap = result.getImages().get(0).asBitmap();
        // Use the bitmap to display the image in your UI.
    }

    @Override
    public void onFailure(Throwable t) {
        // ...
    }
}, Executors.newSingleThreadExecutor());

// Initialize the Gemini Developer API backend service.
// Create a `GenerativeModel` instance with a Gemini model that supports image output.
GenerativeModel ai = FirebaseAI.getInstance(GenerativeBackend.googleAI()).generativeModel(
    "GEMINI_IMAGE_MODEL_NAME",
    new GenerationConfig.Builder()
        .setResponseModalities(Arrays.asList(ResponseModality.IMAGE))
        .setImageConfig(new ImageConfig(AspectRatio.LANDSCAPE_4x3, null))
        .build()
);

GenerativeModelFutures model = GenerativeModelFutures.from(ai);

// Provide a text prompt instructing the model to generate an image.
Content prompt = new Content.Builder()
        .addText("An astronaut riding a horse")
        .build();

// To generate an image, call `generateContent` with the text input.
Executor executor = Executors.newSingleThreadExecutor();
ListenableFuture response = model.generateContent(prompt);
Futures.addCallback(response, new FutureCallback() {
    @Override
    public void onSuccess(GenerateContentResponse result) {
        if (result.finishReason == FinishReason.NO_IMAGE) {
            // handle the case where no images were generated
            return;
        }
        // iterate over all the parts in the first candidate in the result object.
        for (Part part : result.getCandidates().get(0).getContent().getParts()) {
            if (part instanceof ImagePart) {
                ImagePart imagePart = (ImagePart) part;
                // The returned image as a bitmap
                Bitmap generatedImageAsBitmap = imagePart.getImage();
                break;
            }
        }
    }

    @Override
    public void onFailure(Throwable t) {
        t.printStackTrace();
    }
}, executor);

import { initializeApp } from "firebase/app";
import { getAI, getGenerativeModel, getImagenModel, GoogleAIBackend } from "firebase/ai";

// TODO(developer): Replace the following with your app's Firebase configuration
const firebaseConfig = {
  // ...
};

// Initialize FirebaseApp
const firebaseApp = initializeApp(firebaseConfig);

// Initialize the Gemini Developer API backend service.
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

// Create an `ImagenModel` instance with an Imagen model that supports your use case.
const model = getImagenModel(ai, { model: "IMAGEN_MODEL_NAME" });

// Provide an image generation prompt.
const prompt = "An astronaut riding a horse.";

// To generate an image, call `generateImages` with the text prompt.
const response = await model.generateImages(prompt)

// If fewer images were generated than were requested,
// then `filteredReason` will describe the reason they were filtered out.
if (response.filteredReason) {
  console.log(response.filteredReason);
}

if (response.images.length == 0) {
  throw new Error("No images in the response.")
}

const image = response.images[0];

import { initializeApp } from "firebase/app";
import {
  getAI,
  getGenerativeModel,
  GoogleAIBackend,
  ResponseModality,
  ImageConfigAspectRatio,
  FinishReason
} from "firebase/ai";

// TODO(developer): Replace the following with your app's Firebase configuration
const firebaseConfig = {
  // ...
};

// Initialize FirebaseApp
const firebaseApp = initializeApp(firebaseConfig);

// Initialize the Gemini Developer API backend service.
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

// Create a `GenerativeModel` instance with a model that supports your use case.
const model = getGenerativeModel(ai, {
  model: "GEMINI_IMAGE_MODEL_NAME",
  generationConfig: {
    responseModalities: [ResponseModality.IMAGE],
    imageConfig: {
      aspectRatio: ImageConfigAspectRatio.LANDSCAPE_4x3
    }
  },
});

// Provide an image generation prompt.
const prompt = "An astronaut riding a horse.";

// To generate an image, call `generateContent` with the text prompt.
const result = await model.generateContent(prompt);

// Handle the generated image.
try {
  const response = result.response;
  if (response.candidates?.[0].finishReason == FinishReason.NO_IMAGE) {
    // Handle the case where no images were generated.
  }
  const inlineDataParts = response.inlineDataParts();
  if (inlineDataParts?.[0]) {
    const image = inlineDataParts[0].inlineData;
    // Use this mimeType and base64 data to display the image using your preferred tooling.
    console.log(image.mimeType, image.data);
  }
} catch (err) {
  console.error('Prompt or candidate was blocked:', err);
}

import 'package:firebase_ai/firebase_ai.dart';
import 'package:firebase_core/firebase_core.dart';
import 'firebase_options.dart';

// Initialize FirebaseApp
await Firebase.initializeApp(
  options: DefaultFirebaseOptions.currentPlatform,
);

// Initialize the Gemini Developer API backend service.
final ai = FirebaseAI.googleAI();

// Create an `ImagenModel` instance with an Imagen model that supports your use case.
final model = ai.imagenModel(model: 'IMAGEN_MODEL_NAME');

// Provide an image generation prompt.
const prompt = 'An astronaut riding a horse.';

// To generate an image, call `generateImages` with the text prompt.
final response = await model.generateImages(prompt);

if (response.images.isNotEmpty) {
  final image = response.images[0];
  // Process the image.
} else {
  // Handle the case where no images were generated.
  print('Error: No images were generated.');
}

import 'package:firebase_ai/firebase_ai.dart';
import 'package:firebase_core/firebase_core.dart';
import 'firebase_options.dart';

// Initialize FirebaseApp
await Firebase.initializeApp(
  options: DefaultFirebaseOptions.currentPlatform,
);

// Initialize the Gemini Developer API backend service.
final ai = FirebaseAI.googleAI();

// Create a `GenerativeModel` instance with a Gemini model that supports image output.
final model = ai.generativeModel(
  model: 'GEMINI_IMAGE_MODEL_NAME',
  generationConfig: GenerationConfig(
    responseModalities: [ResponseModalities.image],
    imageConfig: ImageConfig(aspectRatio: ImageAspectRatio.landscape4x3)
  ),
);

// Provide a text prompt instructing the model to generate an image.
final prompt = [Content.text('An astronaut riding a horse.')];

// To generate an image, call `generateContent` with the text prompt.
final response = await model.generateContent(prompt);
if (response.inlineDataParts.isNotEmpty) {
  final imageBytes = response.inlineDataParts.first.bytes;
  // Process the image.
} else {
  // Handle the case where no images were generated.
  print('Error: No images were generated.');
}

using Firebase.AI;

// Initialize the Gemini Developer API backend service
var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());

// Create an `ImagenModel` instance with a model that supports your use case
var model = ai.GetImagenModel(modelName: "IMAGEN_MODEL_NAME");

// Provide an image generation prompt
var prompt = "An astronaut riding a horse";

// To generate an image, call `generateImages` with the text prompt
var response = await model.GenerateImagesAsync(prompt: prompt);

// Handle the generated image
if (response.Images.Count == 0) {
  throw new Exception("No image in the response.");
}
var image = response.Images[0].AsTexture2D();

using Firebase;
using Firebase.AI;

// Initialize the Gemini Developer API backend service.
var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());

// Create a `GenerativeModel` instance with a Gemini model that supports image output.
var model = ai.GetGenerativeModel(
  modelName: "GEMINI_IMAGE_MODEL_NAME",
  generationConfig: new GenerationConfig(
    responseModalities: new[] { ResponseModality.Image },
    imageConfig: new ImageConfig(aspectRatio: ImageConfig.AspectRatio.Landscape4x3)
  )
);

// Provide an image generation prompt.
var prompt = "An astronaut riding a horse";

// To generate an image, call `GenerateContentAsync` with the text prompt.
var response = await model.GenerateContentAsync(prompt);

if (response.Candidates.First().FinishReason == FinishReason.NoImage) {
  // Handle the case where no images were generated.
}

// Handle the generated image.
var imageParts = response.Candidates.First().Content.Parts
                         .OfType<ModelContent.InlineDataPart>()
                         .Where(part => part.MimeType == "image/png");

foreach (var imagePart in imageParts) {
  // Load the Image into a Unity Texture2D object.
  UnityEngine.Texture2D texture2D = new(2, 2);
  if (texture2D.LoadImage(imagePart.Data.ToArray())) {
    // Do something with the image.
  }
}