e3e9b96335b0cb813e51e309b3372bcd157370c2,magenta/models/image_stylization/image_utils.py,,_crop,#Any#Any#Any#Any#Any#,375

Before Change

  // Use tf.slice instead of crop_to_bounding box as it accepts tensors to
  // define the crop size.
  image = tf.control_flow_ops.with_dependencies(
      [size_assertion],
      tf.slice(image, offsets, cropped_shape))
  return tf.reshape(image, cropped_shape)


def _central_crop(image_list, crop_height, crop_width):

After Change

  rank_assertion = tf.Assert(
      tf.equal(tf.rank(image), 3),
      ["Rank of image must be equal to 3."])
  with tf.control_dependencies([rank_assertion]):
    cropped_shape = tf.pack([crop_height, crop_width, original_shape[2]])

  size_assertion = tf.Assert(
      tf.logical_and(
          tf.greater_equal(original_shape[0], crop_height),
          tf.greater_equal(original_shape[1], crop_width)),
      ["Crop size greater than the image size."])

  offsets = tf.to_int32(tf.pack([offset_height, offset_width, 0]))

  // Use tf.slice instead of crop_to_bounding box as it accepts tensors to
  // define the crop size.
  with tf.control_dependencies([size_assertion]):
    image = tf.slice(image, offsets, cropped_shape)
  return tf.reshape(image, cropped_shape)


def _central_crop(image_list, crop_height, crop_width):

Instances