as_CNN_image_X: Create a 4-dimensional array for image features (input)

In stschn/deepANN: Neural Network Toolbox

Create a 4-dimensional array for image features (input)

Description

Create a 4-dimensional array for image features (input)

Usage

as_CNN_image_X(images, height, width, channels = 3L, order = c("C", "F"))

Arguments

images	Image data either a 3D array or a list of file names, e.g. returned by list.files.
height	The height of an image, equal to the number of rows.
width	The width of an image, equal to the number of columns.
channels	The number of channels of an image. A color channel is a primary color (like red, green and blue), equal to a color valence (denotes how light effects the color sensation of an eye or in common of the brain). Primary colors can be mixed to produce any color. A channel equal 1 indicates a grayscale image, 3 a color image.
order	The order in which elements of image data should be read during the rearrangement. C (default) means elements should be read in row-major order (C-style), F means elements should be read in column-major order (Fortran-style).

Value

A 4D feature array with the dimensions samples (number of images), height, width and channels.

See Also

list.files, image_load, image_to_array, array_reshape, as_CNN_image_Y.

Other Convolutional Neural Network (CNN): alexnet(), as_CNN_image_Y(), as_CNN_temp_X(), as_CNN_temp_Y(), as_images_array(), as_images_tensor(), images_load(), images_resize(), inception_resnet_v2(), inception_v3(), lenet5(), mobilenet(), mobilenet_v2(), mobilenet_v3(), nasnet(), resnet, unet(), vgg, xception(), zfnet()

stschn/deepANN documentation built on June 25, 2024, 7:27 a.m.