Sapiens Segmentation

The SapiensSegmentation class provides a wrapper for the Sapiens body-part segmentation model.

This model is specifically trained for images with humans as the primary subject.

boolean

default:"False"

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

This model is currently not available via Cortex.

np.ndarray

required

The input RGB image of shape

(M, N, 3)

np.ndarray

The predicted segmentation mask of shape

(M, N)

from grid.model.perception.segmentation.sapiens_segmentation import SapiensSegmentation
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 = SapiensSegmentation(use_local = False)
result = model.run(rgbimage=img)
print(result.shape)

License
Source

This code is licensed under the CC-by-NC 4.0 License.

⌘I

from grid.model.perception.segmentation.sapiens_segmentation import SapiensSegmentation
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 = SapiensSegmentation(use_local = False)
result = model.run(rgbimage=img)
print(result.shape)

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