This layer resizes an image input to a target height and width. The input
should be a 4D (batched) or 3D (unbatched) tensor in "channels_last"
format. Input pixel values can be of any range
(e.g. [0., 1.) or [0, 255]).
Input shape
3D
unbatched) or 4D (batched) tensor with shape
(..., height, width, channels), in "channels_last" format,
or (..., channels, height, width), in "channels_first" format.
Output shape
3D
unbatched) or 4D (batched) tensor with shape
(..., target_height, target_width, channels),
or (..., channels, target_height, target_width),
in "channels_first" format.
Args
height
Integer, the height of the output shape.
width
Integer, the width of the output shape.
interpolation
String, the interpolation method.
Supports "bilinear", "nearest", "bicubic",
"lanczos3", "lanczos5". Defaults to "bilinear".
crop_to_aspect_ratio
If True, resize the images without aspect
ratio distortion. When the original aspect ratio differs
from the target aspect ratio, the output image will be
cropped so as to return the
largest possible window in the image (of size (height, width))
that matches the target aspect ratio. By default
(crop_to_aspect_ratio=False), aspect ratio may not be preserved.
data_format
string, either "channels_last" or "channels_first".
The ordering of the dimensions in the inputs. "channels_last"
corresponds to inputs with shape (batch, height, width, channels)
while "channels_first" corresponds to inputs with shape
(batch, channels, height, width). It defaults to the
image_data_format value found in your Keras config file at
~/.keras/keras.json. If you never set it, then it will be
"channels_last".
**kwargs
Base layer keyword arguments, such as name and dtype.
Attributes
input
Retrieves the input tensor(s) of a symbolic operation.
Only returns the tensor(s) corresponding to the first time
the operation was called.
output
Retrieves the output tensor(s) of a layer.
Only returns the tensor(s) corresponding to the first time
the operation was called.
This method is the reverse of get_config,
capable of instantiating the same layer from the config
dictionary. It does not handle layer connectivity
(handled by Network), nor weights (handled by set_weights).
Args
config
A Python dictionary, typically the
output of get_config.