A prototype that uses image processing and neural networks algorithms to predict the sex of a chick from the egg shape
The prototype takes a sample set of egg photos labelled male and female to use as a training set.
These photos are then processed into gray-scale images from which 2 dimensional matrices are generated. This makes processing easier and more efficient as what is relevant is the shape of the egg.
The matrices and corresponding labels are applied to a neural network architecture from which a set of weights is generated that will be used to predict the expected sex from the image of an egg.