Try Gemini 1.5 models , the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.
Try Gemini 1.5 models , the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.
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Class ImageCaptioningModel (1.67.1)
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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",
)
Methods
ImageCaptioningModel
ImageCaptioningModel(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.
from_pretrained
from_pretrained(model_name: str) -> vertexai._model_garden._model_garden_models.T
Loads a _ModelGardenModel.
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.
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Last updated 2024-09-19 UTC.
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{"lastModified": "Last updated 2024-09-19 UTC."}