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What characteristics does opencv's k nearest neighbor algorithm use to predict?

I found this basic ocr example in the opencv docs that uses the k nearest neighbor algorithm to predict.

From here, the algorithm predicts by plotting a set of training data in feature space by some characteristics of each data, and then finding the nearest neighbors of the given object plotted in the same feature space.

What features does opencv's k nearest neighbor algorithm use to identify the handwritten digits in the example I found?