On your OpenMV camera

Impulses can be deployed as an optimized OpenMV library. This packages all your signal processing blocks, configuration and learning blocks up into a single package. You can include this package in your own application to run the impulse locally. In this tutorial you'll export an impulse, and run the application on the OpenMV H7 Camera to classify images.

Prerequisites

Make sure you followed the Image classification tutorial, have a trained impulse, and can load code on your OpenMV Camera.

Deploying your impulse

Head over to your Edge Impulse project, and go to Deployment. From here you can create the full library which contains the impulse and all external required libraries. Select OpenMV library and click Build to create the library. Then download and extract the .zip file.

To add the model to your OpenMV camera copy the trained.tflite and labels.txt files to the 'OpenMV Cam' volume (like a USB drive).

Uploading the trained model to your OpenMV cameraUploading the trained model to your OpenMV camera

Uploading the trained model to your OpenMV camera

Next, open the ei_image_classification.py file in the OpenMV IDE, and press the 'Play' icon to run the script.

Running your impulse on your OpenMV camera.Running your impulse on your OpenMV camera.

Running your impulse on your OpenMV camera.

You now have your impulse running on your OpenMV camera!


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