from grid.model.perception.str.mgp_str import MGPSTR
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 = MGPSTR(use_local = True)
result = model.run(rgbimage=img, prompt=<prompt>)
print(result)

The MGPSTR class implements a wrapper for the MGPSTR (Multi-Granularity Prediction for Scene Text Recognition) model, which recognizes text in images.

​
class MGPSTR()
​
use_local
boolean
default:
true

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

​
def run()
​
rgbimage
np.ndarray
required

The input RGB image of shape (M,N,3)(M,N,3).

​
Returns
string

Recognized text from the image.

from grid.model.perception.str.mgp_str import MGPSTR
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 = MGPSTR(use_local = True)
result = model.run(rgbimage=img, prompt=<prompt>)
print(result)
This model is best suited for recognizing text in images (OCR).

This code is licensed under the Apache 2.0 License.

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