Image Generation

final result = await RunAnywhere.images.generate('a red bicycle in the rain');

final image = result.images.first;
print('${image.width}x${image.height}');
// image.bytes is encoded image data

final result = await RunAnywhere.images.generate(
  'a red bicycle',
  options: ImageOptions(
    negativePrompt: 'blurry, low quality',
    width: 512,
    height: 512,
    steps: 20,
    guidanceScale: 7.5,
    seed: 42,
  ),
);

await for (final event in RunAnywhere.images.generateStream(
  'a red bicycle',
  options: ImageOptions(steps: 20, reportPartials: true),
)) {
  switch (event) {
    case ImageStarted():
      setState(() => _status = 'Sampling');
    case ImageProgress(:final step, :final totalSteps, :final partialImage):
      setState(() {
        _fraction = totalSteps > 0 ? step / totalSteps : 0;
        if (partialImage != null) _preview = partialImage;
      });
    case ImageCompleted(:final result):
      setState(() => _image = result.images.first.bytes);
  }
}

final result = await RunAnywhere.images.generate(
  'a golden retriever sitting on the bench',
  options: ImageOptions(
    mode: ImageMode.inpaint(
      ImageInput.rawRgb(baseRgb, 512, 512),
      ImageInput.rawRgb(maskRgb, 512, 512),
    ),
  ),
);

import 'dart:io';

if (Platform.isIOS || Platform.isMacOS) {
  await RunAnywhere.models.register(
    ModelRegistration.url(
      id: 'stable-diffusion-v1-5-coreml',
      name: 'Stable Diffusion 1.5 (CoreML)',
      url: 'https://huggingface.co/apple/coreml-stable-diffusion-v1-5-palettized',
      framework: InferenceFramework.INFERENCE_FRAMEWORK_COREML,
      category: ModelCategory.MODEL_CATEGORY_IMAGE_GENERATION,
      memoryRequirementBytes: 1200000000,
    ),
  );
}