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,
)
Methods
ImageQnAModel
ImageQnAModel
(
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.
