title: Why Pytorch officially use mean=[0.485, 0.456, 0.406] and std=[0.229, 0.224, 0.225] to normalize images?
body: <p>In this page (<a href="https://pytorch.org/vision/stable/models.html" rel="noreferrer">https://pytorch.org/vision/stable/models.html</a>), it says that &quot;All pre-trained models expect input images normalized in the same way, i.e. mini-batches of 3-channel RGB images of shape (3 x H x W), where H and W are expected to be at least 224. The images have to be loaded in to a range of [0, 1] and then normalized using <code>mean = [0.485, 0.456, 0.406]</code> and <code>std = [0.229, 0.224, 0.225]</code>&quot;.</p>
  <p>Shouldn't the usual <code>mean</code> and <code>std</code> of normalization be <code>[0.5, 0.5, 0.5]</code> and <code>[0.5, 0.5, 0.5]</code>? Why is it setting such strange values?</p>