Resizing layer

[source]

Resizing class

keras.layers.Resizing(
    height,
    width,
    interpolation="bilinear",
    crop_to_aspect_ratio=False,
    pad_to_aspect_ratio=False,
    fill_mode="constant",
    fill_value=0.0,
    data_format=None,
    **kwargs
)

A preprocessing layer which resizes images.

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.

Note: This layer is safe to use inside a tf.data pipeline (independently of which backend you're using).

Arguments

• 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.
• pad_to_aspect_ratio: If True, pad the images without aspect ratio distortion. When the original aspect ratio differs from the target aspect ratio, the output image will be evenly padded on the short side.
• fill_mode: When using pad_to_aspect_ratio=True, padded areas are filled according to the given mode. Only "constant" is supported at this time (fill with constant value, equal to fill_value).
• fill_value: Float. Padding value to use when pad_to_aspect_ratio=True.
• 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.