0.75

>>> image = pipe.dual_guided(
...     prompt=text, image=image, text_to_image_strength=text_to_image_strength, generator=generator
... ).images[0]
>>> image.save("./car_variation.png")

image_variation

<
source
>
(
image: typing.Union[torch.FloatTensor, PIL.Image.Image]
height: typing.Optional[int] = None
width: typing.Optional[int] = None
num_inference_steps: int = 50
guidance_scale: float = 7.5
negative_prompt: typing.Union[str, typing