title: YOLOv4 training: Cannot detect multiple classes on a single image
body: <p>I used the Open Images dataset to train the CNN for two classes: Person, Mobile phone. The problem is that Yolo detects only 1 class per image. For example, if an image contains a human and a mobile phone, only mobile phones will be detected. <a href="https://i.stack.imgur.com/YGdhM.png" rel="nofollow noreferrer">Example Output</a>. If there are only humans, then all humans will be detected successfully. I think the problem is that the dataset has only images with 1 class marked per image. I have many images in dataset where both classes are present, but only one of them is marked with labels. Can that be the problem?</p>
  <p><strong>How can I solve the problem?</strong></p>
  <ol>
  <li>Add several images with both classes marked</li>
  <li>Mark all images to make sure that every image that contains both phone and person has appropriate label for each object</li>
  <li>Or maybe there is a way to download the dataset so that both classes are marked correctly?</li>
  </ol>
  <p>Here is what in my .names file:</p>
  <pre><code>Person
  Mobile_phone
  </code></pre>
  <p>And here is .data file:</p>
  <pre><code>classes = 2
  train = data/train.txt
  valid = data/test.txt
  names = data/obj.names
  backup = /mydrive/yolov4/backup
  </code></pre>
  <p>Thanks for your help!</p>