Module vision_models (1.39.0)

Classes for working with vision models.

Classes

GeneratedImage

GeneratedImage(
    image_bytes: bytes, generation_parameters: typing.Dict[str, typing.Any]
)

Generated image.

Image

Image(image_bytes: bytes)

Image.

ImageCaptioningModel

ImageCaptioningModel(model_id: str, endpoint_name: typing.Optional[str] = None)

Generates captions from image.

Examples::

model = ImageCaptioningModel.from_pretrained("imagetext@001")
image = Image.load_from_file("image.png")
captions = model.get_captions(
    image=image,
    # Optional:
    number_of_results=1,
    language="en",
)

ImageGenerationModel

ImageGenerationModel(model_id: str, endpoint_name: typing.Optional[str] = None)

Generates images from text prompt.

Examples::

model = ImageGenerationModel.from_pretrained("imagegeneration@002")
response = model.generate_images(
    prompt="Astronaut riding a horse",
    # Optional:
    number_of_images=1,
    seed=0,
)
response[0].show()
response[0].save("image1.png")

ImageGenerationResponse

ImageGenerationResponse(images: typing.List[GeneratedImage])

Image generation response.

ImageQnAModel

ImageQnAModel(model_id: str, endpoint_name: typing.Optional[str] = None)

Answers questions about an image.

Examples::

model = ImageQnAModel.from_pretrained("imagetext@001")
image = Image.load_from_file("image.png")
answers = model.ask_question(
    image=image,
    question="What color is the car in this image?",
    # Optional:
    number_of_results=1,
)

MultiModalEmbeddingModel

MultiModalEmbeddingModel(model_id: str, endpoint_name: typing.Optional[str] = None)

Generates embedding vectors from images.

Examples::

model = MultiModalEmbeddingModel.from_pretrained("multimodalembedding@001")
image = Image.load_from_file("image.png")

embeddings = model.get_embeddings(
    image=image,
    contextual_text="Hello world",
)
image_embedding = embeddings.image_embedding
text_embedding = embeddings.text_embedding

MultiModalEmbeddingResponse

MultiModalEmbeddingResponse(
    _prediction_response: typing.Any,
    image_embedding: typing.Optional[typing.List[float]] = None,
    text_embedding: typing.Optional[typing.List[float]] = None,
)

The image embedding response.