Imagen ব্যবহার করে ইমেজে বস্তু সন্নিবেশ করান

// Using this SDK to access Imagen models is a Preview release and requires opt-in
@OptIn(PublicPreviewAPI::class)
suspend fun customizeImage() {
    // Initialize the Vertex AI Gemini API backend service
    // Optionally specify the location to access the model (for example, `us-central1`)
    val ai = Firebase.ai(backend = GenerativeBackend.vertexAI(location = "us-central1"))

    // Create an `ImagenModel` instance with an Imagen "capability" model
    val model = ai.imagenModel("imagen-3.0-capability-001")

    // This example assumes 'originalImage' is a pre-loaded Bitmap.
    // In a real app, this might come from the user's device or a URL.
    val originalImage: Bitmap = TODO("Load your original image Bitmap here")

    // Provide the prompt describing the content to be inserted.
    val prompt = "a vase of flowers on the table"

    // Use the editImage API to insert the new content.
    // Pass the original image, the prompt, and an editing configuration.
    val editedImage = model.editImage(
        referenceImages = listOf(
            ImagenRawImage(originalImage.toImagenInlineImage()),
            ImagenBackgroundMask(), // Use ImagenBackgroundMask() to auto-generate the mask.
        ),
        prompt = prompt,
        // Define the editing configuration for inpainting and insertion.
        config = ImagenEditingConfig(ImagenEditMode.INPAINT_INSERTION)
    )

    // Process the resulting 'editedImage' Bitmap, for example, by displaying it in an ImageView.
}

// Initialize the Vertex AI Gemini API backend service
// Optionally specify the location to access the model (for example, `us-central1`)
// Create an `ImagenModel` instance with an Imagen "capability" model
ImagenModel imagenModel = FirebaseAI.getInstance(GenerativeBackend.vertexAI("us-central1"))
        .imagenModel(
                /* modelName */ "imagen-3.0-capability-001");

ImagenModelFutures model = ImagenModelFutures.from(imagenModel);

// This example assumes 'originalImage' is a pre-loaded Bitmap.
// In a real app, this might come from the user's device or a URL.
Bitmap originalImage = null; // TODO("Load your image Bitmap here");

// Provide the prompt describing the content to be inserted.
String prompt = "a vase of flowers on the table";

// Define the list of sources for the editImage call.
// This includes the original image and the auto-generated mask.
ImagenRawImage rawOriginalImage =
    new ImagenRawImage(ImagenInlineImageKt.toImagenInlineImage(originalImage));
// Use ImagenBackgroundMask() to auto-generate the mask.
ImagenBackgroundMask rawMaskedImage = new ImagenBackgroundMask();

ImagenEditingConfig config = new ImagenEditingConfig();

// Use the editImage API to insert the new content.
// Pass the original image, the auto-generated masked image, the prompt, and an editing configuration.
Futures.addCallback(model.editImage(Arrays.asList(rawOriginalImage, rawMaskedImage), prompt, config),
    new FutureCallback<ImagenGenerationResponse>() {
        @Override
        public void onSuccess(ImagenGenerationResponse result) {
            if (result.getImages().isEmpty()) {
                Log.d("ImageEditor", "No images generated");
            }
            Bitmap editedImage = ((ImagenInlineImage) result.getImages().get(0)).asBitmap();
            // Process and use the bitmap to display the image in your UI
        }

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

import 'dart:typed_data';
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 Vertex AI Gemini API backend service
// Optionally specify a location to access the model (for example, `us-central1`)
final ai = FirebaseAI.vertexAI(location: 'us-central1');

// Create an `ImagenModel` instance with an Imagen "capability" model
final model = ai.imagenModel(model: 'imagen-3.0-capability-001');

// This example assumes 'originalImage' is a pre-loaded Uint8List.
// In a real app, this might come from the user's device or a URL.
final Uint8List originalImage = Uint8List(0); // TODO: Load your original image data here.

// Provide the prompt describing the content to be inserted.
final prompt = 'a vase of flowers on the table';

try {
  // Use the editImage API to insert the new content.
  // Pass the original image, the prompt, and an editing configuration.
  final response = await model.editImage(
    sources: [
      ImagenRawImage(originalImage),
      ImagenBackgroundMask(), // Use ImagenBackgroundMask() to auto-generate the mask.
    ],
    prompt: prompt,
    // Define the editing configuration for inpainting and insertion.
    config: const ImagenEditingConfig(
      editMode: ImagenEditMode.inpaintInsertion,
    ),
  );

  // Process the result.
  if (response.images.isNotEmpty) {
    final editedImage = response.images.first.bytes;
    // Use the editedImage (a Uint8List) to display the image, save it, etc.
    print('Image successfully generated!');
  } else {
    // Handle the case where no images were generated.
    print('Error: No images were generated.');
  }
} catch (e) {
  // Handle any potential errors during the API call.
  print('An error occurred: $e');
}

// Using this SDK to access Imagen models is a Preview release and requires opt-in
@OptIn(PublicPreviewAPI::class)
suspend fun customizeImage() {
    // Initialize the Vertex AI Gemini API backend service
    // Optionally specify the location to access the model (for example, `us-central1`)
    val ai = Firebase.ai(backend = GenerativeBackend.vertexAI(location = "us-central1"))

    // Create an `ImagenModel` instance with an Imagen "capability" model
    val model = ai.imagenModel("imagen-3.0-capability-001")

    // This example assumes 'originalImage' is a pre-loaded Bitmap.
    // In a real app, this might come from the user's device or a URL.
    val originalImage: Bitmap = TODO("Load your original image Bitmap here")

    // This example assumes 'maskImage' is a pre-loaded Bitmap that contains the masked area.
    // In a real app, this might come from the user's device or a URL.
    val maskImage: Bitmap = TODO("Load your masked image Bitmap here")

    // Provide the prompt describing the content to be inserted.
    val prompt = "a vase of flowers on the table"

    // Use the editImage API to insert the new content.
    // Pass the original image, the masked image, the prompt, and an editing configuration.
    val editedImage = model.editImage(
        referenceImages = listOf(
            ImagenRawImage(originalImage.toImagenInlineImage()),
            ImagenRawMask(maskImage.toImagenInlineImage()), // Use ImagenRawMask() to provide your own masked image.
        ),
        prompt = prompt,
        // Define the editing configuration for inpainting and insertion.
        config = ImagenEditingConfig(ImagenEditMode.INPAINT_INSERTION)
    )

    // Process the resulting 'editedImage' Bitmap, for example, by displaying it in an ImageView.
}

// Initialize the Vertex AI Gemini API backend service
// Optionally specify the location to access the model (for example, `us-central1`)
// Create an `ImagenModel` instance with an Imagen "capability" model
ImagenModel imagenModel = FirebaseAI.getInstance(GenerativeBackend.vertexAI("us-central1"))
        .imagenModel(
                /* modelName */ "imagen-3.0-capability-001");

ImagenModelFutures model = ImagenModelFutures.from(imagenModel);

// This example assumes 'originalImage' is a pre-loaded Bitmap.
// In a real app, this might come from the user's device or a URL.
Bitmap originalImage = null; // TODO("Load your original image Bitmap here");

// This example assumes 'maskImage' is a pre-loaded Bitmap that contains the masked area.
// In a real app, this might come from the user's device or a URL.
Bitmap maskImage = null; // TODO("Load your masked image Bitmap here");

// Provide the prompt describing the content to be inserted.
String prompt = "a vase of flowers on the table";

// Define the list of source images for the editImage call.
ImagenRawImage rawOriginalImage =
    new ImagenRawImage(ImagenInlineImageKt.toImagenInlineImage(originalImage));
// Use ImagenRawMask() to provide your own masked image.
ImagenBackgroundMask rawMaskedImage =
    new ImagenRawMask(ImagenInlineImageKt.toImagenInlineImage(maskImage));

ImagenEditingConfig config = new ImagenEditingConfig();

// Use the editImage API to insert the new content.
// Pass the original image, the masked image, the prompt, and an editing configuration.
Futures.addCallback(model.editImage(Arrays.asList(rawOriginalImage, rawMaskedImage), prompt, config), new FutureCallback<ImagenGenerationResponse>() {
    @Override
    public void onSuccess(ImagenGenerationResponse result) {
        if (result.getImages().isEmpty()) {
            Log.d("ImageEditor", "No images generated");
        }
        Bitmap editedImage = ((ImagenInlineImage) result.getImages().get(0)).asBitmap();
        // Process and use the bitmap to display the image in your UI
    }

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

import 'dart:typed_data';
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 Vertex AI Gemini API backend service
// Optionally specify a location to access the model (for example, `us-central1`)
final ai = FirebaseAI.vertexAI(location: 'us-central1');

// Create an `ImagenModel` instance with an Imagen "capability" model
final model = ai.imagenModel(model: 'imagen-3.0-capability-001');

// This example assumes 'originalImage' is a pre-loaded Uint8List.
// In a real app, this might come from the user's device or a URL.
final Uint8List originalImage = Uint8List(0); // TODO: Load your original image data here.

// This example assumes 'maskImage' is a pre-loaded Uint8List that contains the masked area.
// In a real app, this might come from the user's device or a URL.
final Uint8List maskImage = Uint8List(0); // TODO: Load your masked image data here.

// Provide the prompt describing the content to be inserted.
final prompt = 'a vase of flowers on the table';

try {
  // Use the editImage API to insert the new content.
  // Pass the original image, the prompt, and an editing configuration.
  final response = await model.editImage(
    sources: [
      ImagenRawImage(originalImage),
      ImagenRawMask(maskImage), // Use ImagenRawMask() to provide your own masked image.
    ],
    prompt: prompt,
    // Define the editing configuration for inpainting and insertion.
    config: const ImagenEditingConfig(
      editMode: ImagenEditMode.inpaintInsertion,
    ),
  );

  // Process the result.
  if (response.images.isNotEmpty) {
    final editedImage = response.images.first.bytes;
    // Use the editedImage (a Uint8List) to display the image, save it, etc.
    print('Image successfully generated!');
  } else {
    // Handle the case where no images were generated.
    print('Error: No images were generated.');
  }
} catch (e) {
  // Handle any potential errors during the API call.
  print('An error occurred: $e');
}