Ok lets get you some answers
- 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.
- That being said. drop haartraining completely. It is old, deprecated, not supported anymore and indeed runs for ages without improving.
- Instead, use the newer traincascade interface, which is recent, fully supported and has tons of bugfixes compared to the haartraining tool.
- 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.
