GRID Docs | General Robotics

Segment an image with SAM-3.1 using exactly one prompt type.

Input images up to 1280 x 720 (width x height). Larger images are rejected with HTTP 413, not downscaled — resize first.

Parameters

ImageInput

required

RGB image as file path, URL, PIL Image, or numpy array.

Optional[str]

Text prompt describing objects to segment (exclusive with points/boxes).

Optional[Iterable[Iterable[float]]]

List of [x, y] point coordinates (exclusive with text/boxes).

Optional[Iterable[Iterable[float]]]

List of [x0, y0, x1, y1] box coordinates (exclusive with text/points).

Optional[Iterable[int]]

Required for points/boxes. 1=foreground, 0=background.

Optional[float]

Optional HTTP timeout in seconds.

Returns

np.ndarray: Binary segmentation mask as numpy array (H, W) with dtype uint8. Foreground pixels are 255, background pixels are 0.

Example

from grid_cortex_client import CortexClient, ModelType
import numpy as np
from PIL import Image
client = CortexClient()
image = np.array(Image.open("cat.jpg"))
# Text prompt
mask = client.run(ModelType.SAM3_1, image_input=image, text="cat")
# Point prompts
mask = client.run(
    ModelType.SAM3_1, image_input=image,
    points=[[320, 240]], labels=[1]
)
# Box prompts
mask = client.run(
    ModelType.SAM3_1, image_input=image,
    boxes=[[100, 120, 520, 480]], labels=[1]
)

⌘I

Overview

Cortex Models

sam3-1

Parameters

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Example

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