A model consists of a series of mathematical operations that are applied on the input data to predict an output.
In principle, we can train a model to recognize any type of objects in images, as long as we are able to provide a large number of sample images where the object to be detected is clearly identified.
The process of training a model consists of providing a large number of different images and labeling the location where the object is in the image.
Currently there are a large number of models already pre-trained to detect different types of objects, but we can perform customized training to detect specific objects.
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