title: OpenCV HaarCascade Training for Flowers
body: <p>I have decided to train Haar classifier for 102 flower categories given here:(The dataset)<br>
  <a href="http://www.robots.ox.ac.uk/~vgg/data/flowers/102/categories.html" rel="nofollow noreferrer">http://www.robots.ox.ac.uk/~vgg/data/flowers/102/categories.html</a></p>
  
  <p>In the link you can see several categories. I am posting a few images of an individual flower to explain the question.<br></p>
  
  <p><img src="https://i.stack.imgur.com/BqlRG.jpg" alt="enter image description here">
  <img src="https://i.stack.imgur.com/NHl3Y.jpg" alt="enter image description here">
  <img src="https://i.stack.imgur.com/Iv2iP.jpg" alt="enter image description here">
  This flower belongs to a single class. I have 250 images as positives. There is a considerable variation in this flower's others images(of color, brightness, orientation, etc.). I am hunting for negative images right now. As you might have guessed, I didn't click these pictures so I can't go to the places where these were clicked to collect negative dataset. Instead, I have decided to extract frames from a video. Here is the link:<br>
  <a href="https://www.youtube.com/watch?v=x3zT1mJE0W0" rel="nofollow noreferrer">https://www.youtube.com/watch?v=x3zT1mJE0W0</a></p>
  
  <p>Here are the images from the video:<br>
  <img src="https://i.stack.imgur.com/BqZOb.jpg" alt="enter image description here">
  <img src="https://i.stack.imgur.com/Xt0Pu.jpg" alt="enter image description here">
  It is a video of general garden with bushes and plants background.<br></p>
  
  <p><strong>My question is</strong>: Will this video(and other similar videos) suffice for being negative samples for successful detection? Is it safe to train the classifier for these flowers at all?(I mean with lot of variation in the background. I also plan to use the rest flowers category images as negatives that I am not detecting except the flower that I am trying to detect which in the case here is the Passion Flower).<br>
  This is my first training and I am asking this because the training is gonna eat my whole day and night. I am skeptical about it beforehand.</p>