LLaVA

The LLaVA class provides a wrapper for the LLaVA model, which answers questions about visual media (images) using the LLaVA framework.

boolean

default:"False"

If True, inference call is run on the local VM, else offloaded onto GRID-Cortex. Defaults to False.

np.ndarray

required

The input RGB image of shape

(M,N,3)

str

required

The question to answer about the media.

str

The response to the prompt.

from grid.model.perception.vlm.llava import LLaVA
car = AirGenCar()

# We will be capturing an image from the AirGen simulator 
# and run model inference on it.

img =  car.getImage("front_center", "rgb").data

model = LLaVA(use_local = False)
result = model.run(rgbimage=img, prompt=<prompt>)
print(result)

License
Source

This code is licensed under the Apache 2.0 License.

⌘I

from grid.model.perception.vlm.llava import LLaVA
car = AirGenCar()

# We will be capturing an image from the AirGen simulator 
# and run model inference on it.

img =  car.getImage("front_center", "rgb").data

model = LLaVA(use_local = False)
result = model.run(rgbimage=img, prompt=<prompt>)
print(result)

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