title: In Keras, how do imagenet-pretrained models handled input size different from original 224x224 input size?
body: <p>Since pre-trained models are trained on ImageNet images with a particular width and height, how does Keras model (e.g. ResNet50) allow for a different input_size?</p>
  
  <p>I also would love to know where the magic number '197' comes from:</p>
  
  <blockquote>
    <p>input_shape: optional shape tuple, only to be specified if include_top is False (otherwise the input shape has to be (224, 224, 3) (with 'channels_last' data format) or (3, 224, 224) (with 'channels_first' data format). It should have exactly 3 inputs channels, and width and height should be no smaller than 197. E.g. (200, 200, 3) would be one valid value.</p>
  </blockquote>
  
  <p><a href="https://keras.io/applications/#resnet50" rel="nofollow noreferrer">Source</a></p>