Python full_image_to_patch Examples

Example #1

def make_inference_graph(model_name, patch_dim):
  """Build the inference graph for either the X2Y or Y2X GAN.

  Args:
    model_name: The var scope name 'ModelX2Y' or 'ModelY2X'.
    patch_dim: An integer size of patches to feed to the generator.

  Returns:
    Tuple of (input_placeholder, generated_tensor).
   知识点：
    tf.variable_scope：

    tf.get_variable(<name>, <shape>, <initializer>) 创建或返回给定名称的变量
    tf.variable_scope(<scope_name>) 管理传给get_variable()的变量名称的作用域

    tf.expand_dims：

    想要维度增加一维，可以使用tf.expand_dims(input, dim, name=None)函数。
    当然，我们常用tf.reshape(input, shape=[])也可以达到相同效果，
    但是有些时候在构建图的过程中，placeholder没有被feed具体的值，这时就会包下面的错误：TypeError: Expected binary or unicode string, got 1 
  """
  input_hwc_pl = tf.placeholder(tf.float32, [None, None, 3])

  # Expand HWC to NHWC
  images_x = tf.expand_dims(
      data_provider.full_image_to_patch(input_hwc_pl, patch_dim), 0)

  with tf.variable_scope(model_name):
    with tf.variable_scope('Generator'):
      generated = networks.generator(images_x)
  return input_hwc_pl, generated

Example #2

File: inference_demo.py Project: murez/sketch-path-GAN

def make_inference_graph(model_name, patch_dim):
  """Build the inference graph for either the X2Y or Y2X GAN.
  Args:
    model_name: The var scope name 'ModelX2Y' or 'ModelY2X'.
    patch_dim: An integer size of patches to feed to the generator.
  Returns:
    Tuple of (input_placeholder, generated_tensor).
  """
  input_hwc_pl = tf.placeholder(tf.float32, [None, None, 3])

  # Expand HWC to NHWC
  images_x = tf.expand_dims(
      data_provider.full_image_to_patch(input_hwc_pl, patch_dim), 0)

  with tf.variable_scope(model_name):
    with tf.variable_scope('Generator'):
      generated = networks.generator(images_x)
  return input_hwc_pl, generated

Example #3

File: inference_demo.py Project: 812864539/models

def make_inference_graph(model_name, patch_dim):
  """Build the inference graph for either the X2Y or Y2X GAN.

  Args:
    model_name: The var scope name 'ModelX2Y' or 'ModelY2X'.
    patch_dim: An integer size of patches to feed to the generator.

  Returns:
    Tuple of (input_placeholder, generated_tensor).
  """
  input_hwc_pl = tf.placeholder(tf.float32, [None, None, 3])

  # Expand HWC to NHWC
  images_x = tf.expand_dims(
      data_provider.full_image_to_patch(input_hwc_pl, patch_dim), 0)

  with tf.variable_scope(model_name):
    with tf.variable_scope('Generator'):
      generated = networks.generator(images_x)
  return input_hwc_pl, generated