title: Darknet YOLO image size
body: <p>I am trying to train custom object classifier in Darknet YOLO v2
  <a href="https://pjreddie.com/darknet/yolo/" rel="noreferrer">https://pjreddie.com/darknet/yolo/</a></p>
  
  <p>I gathered a dataset for images most of them are 6000 x 4000 px and some lower resolutions as well.</p>
  
  <p>Do I need to resize the images before training to be squared ?</p>
  
  <p>I found that the config uses:</p>
  
  <pre><code>[net]
  batch=64
  subdivisions=8
  height=416
  width=416
  channels=3
  momentum=0.9
  decay=0.0005
  angle=0
  saturation = 1.5
  exposure = 1.5
  hue=.1
  </code></pre>
  
  <p>thats why I was wondering how to use it for different sizes of data sets.</p>