sam2

from grid_cortex_client import CortexClient, ModelType
import numpy as np
from PIL import Image
client = CortexClient()
image = np.array(Image.open("cat.jpg"))
mask = client.run(
    ModelType.SAM2,
    image_input=image,
    prompts=[[320, 240]],
    labels=[1],
)
print(mask.shape)  # (480, 640)

from grid_cortex_client import CortexClient
import numpy as np
from PIL import Image

client = CortexClient()
img = Image.open("scene.jpg")  # 640x480 RGB
mask = client.run(
    model_id="sam2",
    image_input=img,
    prompts=[[320, 350]],
    labels=[1],  # 1 = foreground
)

print(mask.shape, mask.dtype)
# (480, 640) uint8

print(np.unique(mask))
# [0, 255]

foreground = np.count_nonzero(mask)
print(f"foreground pixels: {foreground} ({foreground / mask.size * 100:.1f}%)")
# foreground pixels: 138532 (45.1%)