from grid.model.perception.detection.gdino import GroundingDINO
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 = GroundingDINO(use_local = False)
box, scores, labels = model.run(rgbimage=img, prompt=<prompt>)
print(box, scores, labels)
## if you want to use the model locally, set use_local=True
model = GroundingDINO(use_local = True)
box, scores, labels = model.run(rgbimage=img, prompt=<prompt>)
print(box, labels)
