title: How do I prepare data (images) for py-faster-rcnn classification training?
body: <p>I am trying to train my own image classificator with <code>py-faster-rcnn</code> <a href="https://github.com/deboc/py-faster-rcnn" rel="nofollow">link</a> using my own images.</p>
  
  <p>It looks rather simple in the <a href="https://github.com/deboc/py-faster-rcnn/blob/master/help/Readme.md" rel="nofollow">example here</a>, but they are using some ready dataset (INRIA Person). Datasets are structured and cropped to sub-images (actually data sets there are both original images and cropped people images from them) and text notation of each image with coordinates of crops. Pretty straightforward.</p>
  
  <p>Still I have no idea how this is done - do they use any sort of tool for this (I can hardly imagine some test lots of data are cropped and notated manually)?</p>
  
  <p>Could anyone please suggest a solution for this one? Thanks. </p>