layer_center_crop {keras}

Crop the central portion of the images to target height and width

Description

Crop the central portion of the images to target height and width

Usage

layer_center_crop(object, height, width, ...)

Arguments

object

What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is:

• missing or NULL, the Layer instance is returned.

• a Sequential model, the model with an additional layer is returned.

• a Tensor, the output tensor from layer_instance(object) is returned.

height

Integer, the height of the output shape.

width

Integer, the width of the output shape.

...

standard layer arguments.

Details

Input shape: 3D (unbatched) or 4D (batched) tensor with shape: ⁠(..., height, width, channels)⁠, in "channels_last" format.

Output shape: 3D (unbatched) or 4D (batched) tensor with shape: ⁠(..., target_height, target_width, channels)⁠.

If the input height/width is even and the target height/width is odd (or inversely), the input image is left-padded by 1 pixel.

See Also

• https://www.tensorflow.org/api_docs/python/tf/keras/layers/CenterCrop

• https://keras.io/api/layers/preprocessing_layers/image_preprocessing/center_crop

Other image preprocessing layers: layer_rescaling(), layer_resizing()

Other preprocessing layers: layer_category_encoding(), layer_discretization(), layer_hashing(), layer_integer_lookup(), layer_normalization(), layer_random_brightness(), layer_random_contrast(), layer_random_crop(), layer_random_flip(), layer_random_height(), layer_random_rotation(), layer_random_translation(), layer_random_width(), layer_random_zoom(), layer_rescaling(), layer_resizing(), layer_string_lookup(), layer_text_vectorization()