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Removed the actual image saving and improved docstrings

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-02-08 12:23:39 +01:00
parent fc1aa20396
commit 7adb703292
1 changed files with 28 additions and 29 deletions
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55
src/twomartens/masterthesis/aae/util.py
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@ -24,50 +24,49 @@ import tensorflow as tf
k = tf.keras.backend
def save_image(tensor: tf.Tensor, filename: str, **kwargs) -> None:
"""Save a given Tensor into an image file.
Args:
tensor (Tensor or list): Image to be saved. If given a mini-batch tensor,
saves the tensor as a grid of images by calling ``make_grid``.
filename (string): name of image
**kwargs: Other arguments are documented in ``make_grid``.
def prepare_image(tensor: Union[tf.Tensor, Sequence[tf.Tensor]], **kwargs) -> tf.Tensor:
"""
Prepares a tensor to be saved as image and returns it.
``**kwargs``: Other arguments are documented in `make_grid()`.
:param tensor: Image to be saved.
If given a mini-batch tensor, saves the tensor as a grid of images by calling make_grid.
:return: the prepared tensor
"""
from PIL import Image
grid = make_grid(tensor, **kwargs)
min_pixel_value = 0
max_pixel_value = 255
grid *= max_pixel_value
grid = tf.clip_by_value(grid, min_pixel_value, max_pixel_value)
grid = tf.cast(grid, tf.uint8)
ndarr = grid.cpu().numpy()
im = Image.fromarray(ndarr)
im.save(filename)
return grid
def make_grid(tensor: Union[tf.Tensor, Sequence[tf.Tensor]], nrow: int = 8, padding: int = 2,
normalize: bool = False, range_value: Tuple[float, float] = None,
scale_each: bool = False, pad_value: float = 0.0) -> tf.Tensor:
"""Make a grid of images.
Args:
tensor (Tensor or list): 4D mini-batch Tensor of shape (B x C x H x W)
or a list of images all of the same size.
nrow (int, optional): Number of images displayed in each row of the grid.
The Final grid size is (B / nrow, nrow). Default is 8.
padding (int, optional): amount of padding. Default is 2.
normalize (bool, optional): If True, shift the image to the range (0, 1),
by subtracting the minimum and dividing by the maximum pixel value.
range_value (tuple, optional): tuple (min, max) where min and max are numbers,
then these numbers are used to normalize the image. By default, min and max
are computed from the tensor.
scale_each (bool, optional): If True, scale each image in the batch of
images separately rather than the (min, max) over all images.
pad_value (float, optional): Value for the padded pixels.
"""
Make a grid of images.
Example:
See this notebook `here <https://gist.github.com/anonymous/bf16430f7750c023141c562f3e9f2a91>`_
:param tensor: 4D mini-batch Tensor of shape (B x C x H x W)
or a list of images all of the same size.
:param nrow: Number of images displayed in each row of the grid.
The Final grid size is (B / nrow, nrow). Default is 8.
:param padding: amount of padding. Default is 2.
:param normalize: If True, shift the image to the range (0, 1),
by subtracting the minimum and dividing by the maximum pixel value.
:param range_value: tuple (min, max) where min and max are numbers,
then these numbers are used to normalize the image. By default, min and max
are computed from the tensor.
:param scale_each: If True, scale each image in the batch of
images separately rather than the (min, max) over all images.
:param pad_value: Value for the padded pixels.
:return: tensor containing image grid
"""
if not (tf.contrib.framework.is_tensor(tensor) or
(isinstance(tensor, list) and all(tf.contrib.framework.is_tensor(t) for t in tensor))):