使用 Imagen 生成图片


Firebase AI Logic SDK 可让您通过 Imagen API 访问 Imagen 模型，以便根据文本提示生成图片。借助此功能，您可以执行以下操作：

  • 根据用自然语言编写的提示生成图片
  • 生成各种格式和风格的图片
  • 在图片中渲染文本

请注意，Firebase AI Logic 尚不支持适用于 Imagen 模型的所有功能。如需了解详情，请参阅本页下文中的支持的功能和特性。

跳转到仅限文本输入的代码

准备工作

点击您的 Gemini API 提供商，在本页面上查看特定于提供商的内容和代码。

如果您尚未完成入门指南，请先完成该指南。其中介绍了如何设置 Firebase 项目、将应用连接到 Firebase、添加 SDK、为所选 API 提供程序初始化后端服务，以及创建 ImagenModel 实例。

支持此功能的模型

Gemini Developer API 仅支持使用最新的稳定版 Imagen 3 模型生成图片，但不支持其他 Imagen 模型。无论您以何种方式访问 Gemini Developer API，这些 Imagen 模型限制都适用。

  • imagen-3.0-generate-002

请注意，Firebase AI Logic 还支持使用 Gemini 模型生成图片 - 相关文档即将推出！

根据纯文本输入生成图片

您可以通过文本提示来要求 Imagen 模型生成图片。您可以生成一张图片或多张图片。

根据纯文本输入生成一张图片

在试用此示例之前，请完成本指南的准备工作部分，以设置您的项目和应用。
在此部分中，您还需要点击所选 Gemini API 提供方的按钮，以便在此页面上看到特定于该提供方的相关内容。

您可以通过文本提示来要求 Imagen 模型生成单张图片。

请务必创建 ImagenModel 实例并调用 generateImages。

Swift


import FirebaseAI

// 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-3.0-generate-002")

// 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)

Kotlin 


// Using this SDK to access Imagen models is a Preview release and requires opt-in
@OptIn(PublicPreviewAPI::class)
suspend fun generateImage() {
  // Initialize the Gemini Developer API backend service
  // Create an `ImagenModel` instance with an Imagen model that supports your use case
  val imagenModel = Firebase.ai(backend = GenerativeBackend.googleAI()).imagenModel("imagen-3.0-generate-002")

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

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

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

  val bitmapImage = image.asBitmap()
}

Java 


// 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-3.0-generate-002");

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());

Web 


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 3 model that supports your use case
const imagenModel = getImagenModel(ai, { model: "imagen-3.0-generate-002" });

// 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 imagenModel.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];

Dart 

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
// Create an `ImagenModel` instance with an Imagen model that supports your use case
final model =
  FirebaseAI.googleAI().imagenModel(model: 'imagen-3.0-generate-002');

// 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.');
}

Unity

Unity 尚不支持使用 Imagen，但请稍后再回来查看！

了解如何选择适合您的应用场景和应用的模型。

根据纯文本输入生成多张图片

在试用此示例之前，请完成本指南的准备工作部分，以设置您的项目和应用。
在此部分中，您还需要点击所选 Gemini API 提供方的按钮，以便在此页面上看到特定于该提供方的相关内容。

默认情况下，Imagen 模型每个请求只生成一张图片。不过，您可以通过在创建 ImagenModel 实例时提供 ImagenGenerationConfig，让 Imagen 模型为每个请求生成多个图片。

请务必创建 ImagenModel 实例并调用 generateImages。

Swift


import FirebaseAI

// 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-3.0-generate-002",
  // 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) }

Kotlin 


// Using this SDK to access Imagen models is a Preview release and requires opt-in
@OptIn(PublicPreviewAPI::class)
suspend fun generateImage() {
  // Initialize the Gemini Developer API backend service
  // Create an `ImagenModel` instance with an Imagen model that supports your use case
  val imagenModel = Firebase.ai(backend = GenerativeBackend.googleAI()).imagenModel(
      modelName = "imagen-3.0-generate-002",
      // 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 = imagenModel.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
  }
}

Java 


// 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-3.0-generate-002",
        /* 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());

Web 


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 3 model that supports your use case
const imagenModel = getImagenModel(
  ai,
  {
    model: "imagen-3.0-generate-002",
    // 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 imagenModel.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];

Dart 

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
// Create an `ImagenModel` instance with an Imagen model that supports your use case
final model =
  FirebaseAI.googleAI().imagenModel(
    model: 'imagen-3.0-generate-002',
    // 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.');
}

Unity

Unity 尚不支持使用 Imagen，但请稍后再回来查看！

了解如何选择适合您的应用场景和应用的模型。


支持的功能和要求

Imagen 模型提供了许多与图片生成相关的功能。本部分介绍了将模型与 Firebase AI Logic 搭配使用时支持的功能。

支持的 capability 和功能

Firebase AI Logic 支持 Imagen 模型的这些功能。

  • 生成人物和面孔（前提是您的 Firebase 项目已获得 Google Cloud 的批准）

  • 在生成的图片中生成文本

  • 为生成的图片添加水印

  • 配置图片生成参数，例如生成的图片数量、宽高比和水印

  • 配置安全设置

Firebase AI Logic 不支持 Imagen 模型的这些高级功能。

请注意，即使在服务器端使用 Imagen 模型，也需要位于已获批准的用户名单中才能使用其中的大多数功能。

  • 图片编辑或处理功能，包括放大图片

  • 在向模型发送的请求中添加图片（例如，用于少样本学习）

  • 使用 SDK 验证数字水印
    如果您想验证图片是否带有水印，可以使用 Vertex AI Studio 的媒体标签页将图片上传到 Vertex AI Studio。

  • 根据文字生成“实况图片”（MP4 生成）

  • 使用预定义风格生成图片

  • 设置输入文本的语言

  • 启用 includeSafetyAttributes，这意味着无法返回 safetyAttributes.categories 和 safetyAttributes.scores

  • 停用提示增强功能（enhancePrompt 参数），这意味着基于 LLM 的重写提示工具将始终自动在所提供的提示中添加更多详细信息，以提供更高质量的图片，从而更好地反映所提供的提示

  • 将生成的图片直接写入 Google Cloud Storage，作为模型响应（storageUri 参数）的一部分。相反，系统会在响应中始终以 base64 编码的图片字节的形式返回图片。
    如果您想将生成的图片上传到 Cloud Storage，可以使用 Cloud Storage for Firebase。

规范和限制

媒体资源（每个请求） 值
输入 token 数上限 480 个词元
输出图片数量上限 4 张图片
支持的输出图片分辨率（像素）
  • 1024x1024 像素（宽高比为 1:1）
  • 896x1280（宽高比为 3:4）
  • 1280x896（宽高比为 4:3）
  • 768x1408（宽高比为 9:16）
  • 1408x768（宽高比为 16:9）


您还可以执行以下操作

了解如何控制内容生成

详细了解支持的模型

了解适用于各种用例的模型及其配额和价格。


就您使用 Firebase AI Logic 的体验提供反馈