Models

Machine learning models for AIY kits

Machine learning is the process of making predictions based on patterns and relationships that have been discovered in data. Experiment with these models to see machine learning in action.

Did you build your own model? We’re accepting contributions for future projects. Please share with us.

Face Detector

The Face Detector model locates and identifies faces from an image. It also provides a “joy score” for each face.

Supported device: Vision Kit
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Dog / Cat / Human Detector

The Dog / Cat / Human model can identify whether there’s a dog, cat, or person in an image and draw a box around the identified objects. It’s based on the MobileNet model, a general-purpose object detection model.

Supported device: Vision Kit
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Dish Classifier

The Dish Classifier model is designed to identify food in an image. It’s based on the MobileNet model, a general-purpose object detection model.

Supported device: Vision Kit
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Google Image Classifier

The Google Image Classifier is a general-purpose model designed to recognize and identify objects in an image. It’s based on the MobileNet ImageNet classifier model.

Supported device: Vision Kit
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Image Classifier

The Image Classifier model is designed to identify objects in an image. It’s based on the SqueezeNet model.

Supported device: Vision Kit
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Nature Explorer

Nature explorer has 3 machine learning models based on MobileNet, trained on photos contributed by the iNaturalist community. These models are built to recognize 4,080 different species (~960 birds, ~1020 insects, ~2100 plants)

In collaboration with iNaturalist
Supported device: Vision Kit
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