Class ImageTextModel (1.60.0)

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

Generates text from images.

Examples::

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

Methods

ImageTextModel

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

Creates a _ModelGardenModel.

This constructor should not be called directly. Use {model_class}.from_pretrained(model_name=...) instead.

Parameters
Name	Description
`model_id`	`str` Identifier of a Model Garden Model. Example: "text-bison@001"
`endpoint_name`	`typing.Optional[str]` Vertex Endpoint resource name for the model

ask_question

ask_question(
 image: vertexai.vision_models.Image, question: str, *, number_of_results: int = 1
) -> typing.List[str]

Answers questions about an image.

Parameters
Name	Description
`image`	`Image` The image to get captions for. Size limit: 10 MB.
`question`	`str` Question to ask about the image.

from_pretrained

from_pretrained(model_name: str) -> vertexai._model_garden._model_garden_models.T

Loads a _ModelGardenModel.

Parameter
Name	Description
`model_name`	`str` Name of the model.

Exceptions
Type	Description
`ValueError`	If model_name is unknown.
`ValueError`	If model does not support this class.

get_captions

get_captions(
 image: vertexai.vision_models.Image,
 *,
 number_of_results: int = 1,
 language: str = "en",
 output_gcs_uri: typing.Optional[str] = None
) -> typing.List[str]

Generates captions for a given image.

Parameter
Name	Description
`image`	`Image` The image to get captions for. Size limit: 10 MB.

Class ImageTextModel (1.60.0) Stay organized with collections Save and categorize content based on your preferences.