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Edge Impulse

Edge Impulse is the easiest way to build new edge AI models for Qualcomm Dragonwing devices. It's an end-to-end platform that helps you build datasets, train models, and run models with full hardware acceleration. It supports building AI models using audio, image and other sensor data - or bringing your own model in a variety of formats.

Train an AI model​

To start building with Edge Impulse:
1️⃣ Make sure you've followed the device setup for your development board.
2️⃣ Sign up for a free developer account at studio.edgeimpulse.com.
3️⃣ From the terminal or ssh session on your development board, install Node.js 22 from the Nodesource PPA:

# Remove existing installation (if needed)
rm -f /usr/local/bin/node /usr/local/bin/npm

# Install Node.js v22
curl -fsSL https://deb.nodesource.com/setup_22.x | sudo -E bash -
sudo apt install -y nodejs

# Verify installation (might need to open a new terminal window)
node -v
# ... Should return v22.x.x

4️⃣ Then, install Edge Impulse for Linux, and connect your development board to Edge Impulse:

# Install the CLI
npm install -g edge-impulse-linux

# Connect to your project (to switch projects, add --clean)
edge-impulse-linux

5️⃣ Follow one of the end-to-end tutorials to build your first AI model.

tip

Use the target selector on the top right corner to select your Qualcomm Dragonwing development board, and get accurate performance information.

6️⃣ To run your model, from the terminal or ssh session on your development board:

edge-impulse-linux-runner

This will automatically build and download your model, and run it on the NPU (quantized models only).

Or, to manually download the EIM file, search for "Linux (AARCH64 with Qualcomm QNN)" in the Deployment page in your Edge Impulse project.

Bring Your Own Model​

Edge Impulse also lets you bring your own model (BYOM) in SavedModel, ONNX, TFLite, LiteRT or scikit-learn format. Models deployed through BYOM are fully supported on Dragonwing platforms, NPU acceleration (for quantized models). See Edge Impulse docs > Bring Your Own Model.

Tips​

Seeing NPU performance​

Dragonwing platforms have a powerful NPU (neural processing unit) which can drastically speed up AI inference. To see the effect that an NPU has on performance, you can run your model on the CPU via:

edge-impulse-linux-runner --force-target runner-linux-aarch64

E.g. on an example quantized YOLO-based model with 7M parameters on the RUBIK Pi 3 the CPU takes 47ms. per inference, and just 2ms. (!) on the NPU.