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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,
width=1024,
width=768,
seed=0,
)
response[0].show()
response[0].save("image1.png")
ImageGenerationResponse
ImageGenerationResponse(
images: typing.List[vertexai.vision_models._vision_models.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.