Image recognition from tensorflow

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1

Hi. I’m stuck, not really sure where to go next.
With Tensorflow I’m doing this

new_model = load_model(os.path.join('imageclassifier.keras'))
img = cv2.imread('Adailer.C.png')
resize = tf.image.resize(img, (256,256))
plt.imshow(img)
plt.show
yhat = new_model.predict(np.expand_dims(resize/255, 0))
yhat
print(
    "This image most likely belongs to {} with a {:.2f} percent confidence."
    .format(class_names[np.argmax(yhat)], 100 * np.max(yhat))
)

I now want to do the same with Hailo8l on the same raspberry pi but with Hailo.

I’ve set up the docker hailo on a Ubuntu Server and created a HAR file.
But after this, I have no idea what I’m meant to be doing.
What are the next steps please?

Much appreciated

2

Hey @phil.e.steadman,

  1. Convert HAR to HEF: You can convert your HAR file to a HEF using the hailo compile and hailo optimize commands. For detailed guidance, refer to the DFC guideline at Hailo Developer Zone. For a simplified explanation, you can check this post: Creating Custom HEF Using DFC Model Zoo.

  2. Run Inference: You can run inference using one of the following methods:

    • HailoRT CLI: Use the command: hailortcli run --hef your_model.hef --input your_input_image --output your_output_dir
    • HailoRT Python API: This allows you to configure the device and run inference programmatically.
    • For more information on using this in an application, check out these examples:

Feel free to reach out if you need more detailed guidance on any specific topic.

Best regards,
Omri