Meaning of stages in traincascade

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Stages are a collection of weak classifiers. By default OpenCV uses stumps as weak classifiers, basically a binary decision tree based on a given feature. However a single feature will never work, so multiple features/stumps/classifiers are combined until the stage does better than random guessing on the negatives, while maintaining a high hit ratio on the positives.

But the parameters allow you to change this all.

More info on this can be found in the OpenCV Blueprints book chapter 5!

Good luck!