使用 Imagen 生成图片

 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-4.0-generate-001") // 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) 

 suspend fun generateImage() {  // 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-4.0-generate-001")  // 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 // Create an `ImagenModel` instance with an Imagen model that supports your use case ImagenModel imagenModel = FirebaseAI.getInstance(GenerativeBackend.googleAI())  .imagenModel(  /* modelName */ "imagen-4.0-generate-001"); 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<ImagenInlineImage>>() {  @Override  public void onSuccess(ImagenGenerationResponse<ImagenInlineImage> 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()); 

 import { initializeApp } from "firebase/app"; import { getAI, getGenerativeModel, GoogleAIBackend } from "firebase/ai"; // TODO(developer) Replace the following with your app's Firebase configuration // See: https://firebase.google.com/docs/web/learn-more#config-object 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-4.0-generate-001" }); // 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 '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 model = FirebaseAI.googleAI(); // Create an `ImagenModel` instance with an Imagen model that supports your use case final model = ai.imagenModel(model: 'imagen-4.0-generate-001'); // 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.'); } 

 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-4.0-generate-001"); // 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(); 

 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-4.0-generate-001",  // Configure the model to generate multiple images for each request  // See: https://firebase.google.com/docs/ai-logic/model-parameters  generationConfig: ImagenGenerationConfig(numberOfImages: 4) ) // Provide an image generation prompt let prompt = "An astronaut riding a horse" // To generate images, call `generateImages` with the text prompt let response = try await model.generateImages(prompt: prompt) // If fewer images were generated than were requested, // then `filteredReason` will describe the reason they were filtered out if let filteredReason = response.filteredReason {  print(filteredReason) } // Handle the generated images let uiImages = response.images.compactMap { UIImage(data: $0.data) } 

 suspend fun generateImage() {  // 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(  modelName = "imagen-4.0-generate-001",  // Configure the model to generate multiple images for each request  // See: https://firebase.google.com/docs/ai-logic/model-parameters  generationConfig = ImagenGenerationConfig(numberOfImages = 4)  )  // Provide an image generation prompt  val prompt = "An astronaut riding a horse"  // To generate images, call `generateImages` with the text prompt  val imageResponse = model.generateImages(prompt)  // If fewer images were generated than were requested,  // then `filteredReason` will describe the reason they were filtered out  if (imageResponse.filteredReason != null) {  Log.d(TAG, "FilteredReason: ${imageResponse.filteredReason}")  }  for (image in imageResponse.images) {  val bitmap = image.asBitmap()  // Use the bitmap to display the image in your UI  } } 

 // Configure the model to generate multiple images for each request // See: https://firebase.google.com/docs/ai-logic/model-parameters ImagenGenerationConfig imagenGenerationConfig = new ImagenGenerationConfig.Builder()  .setNumberOfImages(4)  .build(); // 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-4.0-generate-001",  /* imageGenerationConfig */ imagenGenerationConfig); ImagenModelFutures model = ImagenModelFutures.from(imagenModel); // Provide an image generation prompt String prompt = "An astronaut riding a horse"; // To generate images, call `generateImages` with the text prompt Futures.addCallback(model.generateImages(prompt), new FutureCallback<ImagenGenerationResponse<ImagenInlineImage>>() {  @Override  public void onSuccess(ImagenGenerationResponse<ImagenInlineImage> result) {  // If fewer images were generated than were requested,  // then `filteredReason` will describe the reason they were filtered out  if (result.getFilteredReason() != null){  Log.d("TAG", "FilteredReason: " + result.getFilteredReason());  }  // Handle the generated images  List<ImagenInlineImage> images = result.getImages();  for (ImagenInlineImage image : images) {  Bitmap bitmap = image.asBitmap();  // Use the bitmap to display the image in your UI  }  }  @Override  public void onFailure(Throwable t) {  // ...  } }, Executors.newSingleThreadExecutor()); 

 import { initializeApp } from "firebase/app"; import { getAI, getGenerativeModel, GoogleAIBackend } from "firebase/ai"; // TODO(developer) Replace the following with your app's Firebase configuration // See: https://firebase.google.com/docs/web/learn-more#config-object 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-4.0-generate-001",  // Configure the model to generate multiple images for each request  // See: https://firebase.google.com/docs/ai-logic/model-parameters  generationConfig: {  numberOfImages: 4  }  } ); // Provide an image generation prompt const prompt = "An astronaut riding a horse."; // To generate images, 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 images = response.images[0]; 

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-4.0-generate-001',  // Configure the model to generate multiple images for each request  // See: https://firebase.google.com/docs/ai-logic/model-parameters  generationConfig: ImagenGenerationConfig(numberOfImages: 4), ); // Provide an image generation prompt const prompt = 'An astronaut riding a horse.'; // To generate images, call `generateImages` with the text prompt final 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 != null) {  print(response.filteredReason); } if (response.images.isNotEmpty) {  final images = response.images;  for(var image in images) {  // 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-4.0-generate-001",  // Configure the model to generate multiple images for each request  // See: https://firebase.google.com/docs/ai-logic/model-parameters  generationConfig: new ImagenGenerationConfig(numberOfImages: 4) ); // 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); // If fewer images were generated than were requested, // then `filteredReason` will describe the reason they were filtered out if (!string.IsNullOrEmpty(response.FilteredReason)) {  UnityEngine.Debug.Log("Filtered reason: " + response.FilteredReason); } // Handle the generated images var images = response.Images.Select(image => image.AsTexture2D());