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Explore, Prototype and Accelerate
Edge AI

DeGirum AI Hub lets you explore AI models, test hardware compatibility, and run inference on real-world solutions. Access ready-to-use models, run them in your browser or locally with PySDK, and discover edge AI hardware accelerators.

Simplifying Edge AI Development with DeGirum Solutions

  • Develop, test, and optimize AI across any hardware platform with Python.

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  • Run models instantly and explore AI capabilities in your browser.

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  • Boost performance for edge AI with our efficient accelerator and modules.

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Start Prototyping Today

Choose your workflow—run models effortlessly in your browser or dive into code-based development with PySDK.

// initiate DeGirum SDK package
let dg = new dg_sdk();

// load mobilenet model from deGirum's public model zoo to run in the cloud
const secretToken = prompt("Enter secret token:");
let zoo = await dg.connect("cloud", "https://hub.degirum.com/degirum/public", secretToken);
let model = await zoo.loadModel("mobilenet_v2_ssd_coco--300x300_quant_n2x_orca1_1", { autoScaleDrawing: true, overlayShowProbabilities: true});

// perform AI inference of an image specified by URL
const result = await model.predict("https://raw.githubusercontent.com/DeGirum/PySDKExamples/main/images/TwoCats.jpg");

// print numeric results
console.log("Result:", result);

// show graphical results
let canvas = document.getElementById("outputCanvas");
model.displayResultToCanvas(result, canvas);
# import DeGirum PySDK package
import degirum as dg
# load mobilenet model from deGirum's public model zoo to run in the cloud
model = dg.load_model(
  model_name = "mobilenet_v2_ssd_coco--300x300_quant_n2x_orca1_1",
  inference_host_address = dg.CLOUD,
  zoo_url = "degirum/public",
  token = "your_cloud_access_token",
  image_backend = "pil"
)

# perform AI inference of an image specified by URL
result = model("https://raw.githubusercontent.com/DeGirum/PySDKExamples/main/images/TwoCats.jpg")

# print numeric result
print(result)

# show graphical results
result.image_overlay.show()

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