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Ok lets get you some answers

  1. I am unsure, if cascade classifiers is actually what you want, since I am unsure how much variation a kidney object can have. But it seems to be a suitable approach.
  2. That being said. drop haartraining completely. It is old, deprecated, not supported anymore and indeed runs for ages without improving.
  3. Instead, use the newer traincascade interface, which is recent, fully supported and has tons of bugfixes compared to the haartraining tool.
  4. To reduce training time, first build a classifier with LBP features, and once you have decent results, you can let your system train a HAAR model. But LBP is better for parameter tuning for your case, since it trains way faster.