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dlresize

Resize spatial dimensions of dlarray

Description

example

Y = dlresize(X,'Scale',scale) resizes the spatial dimensions of the dlarray object X by a scale factor scale.

Y = dlresize(X,'OutputSize',outputSize) resizes the spatial dimensions of the dlarray object X so that the spatial dimension sizes are equal to outputSize.

Y = dlresize(___,Name,Value) adjusts the resizing operation using name-value pair arguments. If X is not a formatted dlarray, then you must specify the DataFormat name-value pair argument.

Examples

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Read an RGB image.

A = imread('peppers.png');

Convert the image to data type single for use in a dlarray. Then, create a dlarray containing the input image.

A = im2single(A);
dlarrayA = dlarray(A,'SSC');

Rescale the dlarray by a factor of 1.5 vertically.

dlarrayB = dlresize(dlarrayA,'Scale',[1.5 1]);

Extract the image data from the resized dlarray B by using the extractdata (Deep Learning Toolbox) function.

B = extractdata(dlarrayB);

Display the original and resized images as a montage.

montage({A,B},"ThumbnailSize",size(B,[1 2]), ...
    "BorderSize",10,"BackgroundColor","white")

Input Arguments

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Deep learning array to resize, specified as a dlarray (Deep Learning Toolbox) object.

Scale factor to resize input, specified as a positive number or a vector of positive numbers of length equal to the number of spatial dimensions in X. If scale is a scalar, then dlresize applies the same scale factor to all spatial dimensions.

Output size of resized input, specified as a vector of positive integers of length equal to the number of spatial dimensions in X. You can specify one element as a positive integer and specify the other elements as NaN, in which case the layer computes the other elements automatically to preserve the aspect ratio of the input.

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: 'Method',linear

Dimension labels of the input dlarray object X, specified as the comma-separated pair consisting of 'DataFormat' and a string scalar or character vector. Each character in fmt must be one of these labels:

  • S — Spatial

  • C — Channel

  • B — Batch observations

  • T — Time or sequence

  • U — Unspecified

If X is not a formatted dlarray, then you must specify the DataFormat name-value pair argument. For more information, see dlarray (Deep Learning Toolbox).

Example: 'SSC' indicates the array has two spatial dimensions and one channel dimension, appropriate for 2-D RGB image data.

Interpolation method, specified as the comma-separated pair consisting of 'Method' and "nearest" for nearest neighbor interpolation or "linear" for bilinear interpolation.

Geometric transformation mode to map points from input space to output space, specified as the comma-separated pair consisting of 'GeometricTransformMode' and "half-pixel" or "asymmetric".

Rounding mode for nearest neighbor interpolation, specified as the comma-separated pair consisting of 'NearestRoundingMode' and one of the following.

  • "round" — use the same rounding behavior as the MATLAB® round function.

  • "floor" — use the same rounding behavior as the MATLAB floor function.

  • "onnx-10" — reproduce the resizing behavior of the ONNX™ (Open Neural Network Exchange) opset 10 Resize operator.

This argument is used when you specify the Method as 'nearest'.

Output Arguments

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Resized deep learning array, returned as a dlarray (Deep Learning Toolbox) object.

Extended Capabilities

See Also

(Deep Learning Toolbox) | (Deep Learning Toolbox) | (Deep Learning Toolbox)

Introduced in R2020b