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Updated docstring for util module

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-02-08 21:22:00 +01:00
parent 9bf7229b1e
commit 81f245be99
1 changed files with 33 additions and 11 deletions
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44
src/twomartens/masterthesis/aae/util.py
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@ -14,7 +14,13 @@
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
"""aae.util.py: contains utility functions""" """
Utility functionality for visualizing predictions.
Functions:
prepare_image(...): prepares a tensor to be visualized as an image
"""
import math import math
from typing import Sequence, Tuple, Union from typing import Sequence, Tuple, Union
@ -24,17 +30,33 @@ import tensorflow as tf
k = tf.keras.backend k = tf.keras.backend
def prepare_image(tensor: Union[tf.Tensor, Sequence[tf.Tensor]], **kwargs) -> tf.Tensor: def prepare_image(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:
""" """
Prepares a tensor to be saved as image and returns it. 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. Args:
If given a mini-batch tensor, saves the tensor as a grid of images by calling make_grid. tensor: Image to be saved.
:return: the prepared tensor given a mini-batch tensor, saves the tensor as a grid of images by calling make_grid.
nrow: Number of images displayed in each row of the grid.
The Final grid size is (B / nrow, nrow). Default is 8.
padding: amount of padding. Default is 2.
normalize: If True, shift the image to the range (0, 1),
by subtracting the minimum and dividing by the maximum pixel value.
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.
scale_each: If True, scale each image in the batch of
images separately rather than the (min, max) over all images.
pad_value: Value for the padded pixels.
Returns:
the prepared tensor
""" """
grid = make_grid(tensor, **kwargs) grid = _make_grid(tensor, nrow, padding, normalize, range_value,
scale_each, pad_value)
min_pixel_value = 0 min_pixel_value = 0
max_pixel_value = 255 max_pixel_value = 255
grid *= max_pixel_value grid *= max_pixel_value
@ -44,9 +66,9 @@ def prepare_image(tensor: Union[tf.Tensor, Sequence[tf.Tensor]], **kwargs) -> tf
return grid return grid
def make_grid(tensor: Union[tf.Tensor, Sequence[tf.Tensor]], nrow: int = 8, padding: int = 2, 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, normalize: bool = False, range_value: Tuple[float, float] = None,
scale_each: bool = False, pad_value: float = 0.0) -> tf.Tensor: scale_each: bool = False, pad_value: float = 0.0) -> tf.Tensor:
""" """
Make a grid of images. Make a grid of images.