util.py

import tensorflow as tf
import numpy as np
from functools import partial

# Utility functions for data processing.

def get_resize_func(method):
  """Resampling."""
  if method == 'bicubic':
    return tf.image.resize_bicubic
  elif method == 'nn':
    return tf.image.resize_nearest_neighbor
  else:
    raise


def image_to_patches(image, scale=1):
  patch_height = 108 / scale
  patch_width = 108 / scale
  patch_overlap = 12 / scale
  patches = tf.extract_image_patches(
      image, [1, patch_height, patch_width, 1],
      [1, patch_height - 2 * patch_overlap, patch_width - 2 * patch_overlap, 1],
      [1, 1, 1, 1],
      padding='VALID')
  return tf.reshape(patches, [
      tf.shape(patches)[0] * tf.shape(patches)[1] * tf.shape(patches)[2],
      patch_height, patch_width, 3
  ])


def crop_center(image, target_shape):
  origin_shape = tf.shape(image)[1:3]
  return tf.slice(image, [
      0, (origin_shape[0] - target_shape[0]) / 2,
      (origin_shape[1] - target_shape[1]) / 2, 0
  ], [-1, target_shape[0], target_shape[1], -1])


def crop_by_pixel(x, num):
  shape = tf.shape(x)[1:3]
  return tf.slice(x, [0, num, num, 0],
                  [-1, shape[0] - 2 * num, shape[1] - 2 * num, -1])


def pad_boundary(image, boundary_size=15):
  return tf.pad(
      image, [[0, 0], [boundary_size, boundary_size],
              [boundary_size, boundary_size], [0, 0]],
      mode="SYMMETRIC")