June 2019 | By Al Bencomo

A machine that dispenses candy when the user displays the requested image in front of the trained image model.

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NeuralCandy combines image classifier and sugar highs in one delicious Android Things project. The application asks for a random image to be placed in front of the camera module and if it matches the request; then the motor of the candy dispenser is activated to release the reward.

NeuralCandy uses the TensorFlow Lite inference library for Android to locally classify the captured image against the pre-trained ImageNet model. This model is good at recognizing categories that it was trained with. You can use a smartphone to search on Google for the requested target image and put it in front of the Pi camera. The Raspberry Pi 3 model B will handle the image processing and the motor for the candy release.