GRID Docs | General Robotics

Compute an L2-normalized embedding for a single RGB image.

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.

float | None

Optional timeout in seconds for the HTTP request.

Returns

np.ndarray: Embedding as numpy array of shape (D,), dtype float32, L2-normalized so dot products give cosine similarity directly.

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"))
emb = client.run(ModelType.C_RADIO, image_input=image)
print(emb.shape, float(np.linalg.norm(emb)))  # (D,) 1.0

⌘I

Overview

Cortex Models

c-radio

Parameters

Returns

Example

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Parameters

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Example