title: opencv_traincascade fail to find positive samples
body: <p>I know this has been asked to death, but I have followed every link and solution to no avail. Im training a cascade with 10 original postive images and creating 200 samples from each one. I have 544 negatives. According to this: <a href="https://stackoverflow.com/questions/16058080/how-to-train-cascade-properly">How to train cascade properly</a>, it should work, but mine fails before starting first stage. I've tried increasing/reducing original samples and how many new samples are made but it doesnt make a difference.</p>
  
  <pre><code>PARAMETERS:
  cascadeDirName: classifier
  vecFileName: samples.vec
  bgFileName: negatives.txt
  numPos: 1800
  numNeg: 544
  numStages: 13
  precalcValBufSize[Mb] : 2048
  precalcIdxBufSize[Mb] : 2048
  stageType: BOOST
  featureType: HAAR
  sampleWidth: 24
  sampleHeight: 34
  boostType: GAB
  minHitRate: 0.999
  maxFalseAlarmRate: 0.5
  weightTrimRate: 0.95
  maxDepth: 1
  maxWeakCount: 100
  mode: ALL
  
  ===== TRAINING 0-stage =====
  &lt;BEGIN
  POS OpenCV Error: Bad argument (Can not get new positive sample. The most possible reason is insufficient count of samples in given vec-file. 
  </code></pre>
  
  <p>My confusion is compounded by the huge amount of conflict about this topic, for example this post <a href="http://abhishek4273.com/2014/03/16/traincascade-and-car-detection-using-opencv/" rel="nofollow noreferrer">http://abhishek4273.com/2014/03/16/traincascade-and-car-detection-using-opencv/</a> states that there should be more negative than positive, whereas the first link says the opposite.</p>