dermatologic_preprocessing.py 文件源码

def apply_image_normalization(image, normalize_per_image=0) :
    if normalize_per_image == 0 : 
      image = tf.sub(image, 0.5)
      image = tf.mul(image, 2.0) # All pixels now between -1.0 and 1.0
      return image
    elif normalize_per_image == 1 :
      image = tf.mul(image, 2.0) # All pixels now between 0.0 and 2.0
      image = image - tf.reduce_mean(image, axis=[0, 1]) 
      # Most pixels should be between -1.0 and 1.0
      return image
    elif normalize_per_image == 2 :
      image = tf.image.per_image_standardization(image)
      image = tf.mul(image, 0.4) # This makes 98.8% of pixels between -1.0 and 1.0
      return image
    else :
      raise ValueError('invalid value for normalize_per_image: %d' % normalize_per_image)