How does the OpenCV-Transcascade collecting negative samples?

e.g. -numPos 2000 -numNeg 1000 -numStages 10 -w 20 -h 20 -minHitRate 0.995 -maxFalseAlarmRate 0.2

I have some questions about collecting negative samples.

1.According to the answer of the article(opencv_traincascade Negative samples training method), is 800 negative samples will be recognize as NEG and 200 negative samples be recognize as POS by 0th stage? If Yes, will those 200 samples be picked up to the next stage?

2.The source code in the imagestorge.cpp ->NegReader::nextImg

What is meaning of "round"? if the current negative image is 1000x1000 pixels, will the image be cropped to many 20x20 images and randomly resized to predict function? The main question is how does the procedure of collecting negative samples?

3.Why does the process of "NEG current samples" always count slowly by the high-stages?

Thanks in advance!