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class copy() function don't copy all elements?

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ababa
ababa 2023-7-30
below code is a matlab example of custom datastore.
I edited the code to extract label information from imageDatastore.
If the part of 'obj.NumObservations = numel(obj.ImagesX.Files)' is commented, The suffle function part is broken.
But It outputs label(labelsX variable in code).
If the part of 'obj.NumObservations = numel(obj.ImagesX.Files)' is not commented, The suffle function part is not broken.
but It don't output label.
I think its problem is on obj.copy() in shuffle function.
If the part of 'obj.NumObservations = numel(obj.ImagesX.Files)' is commented, the suffle function part don't execute copy() function.
If the part of 'obj.NumObservations = numel(obj.ImagesX.Files)' is not commented, the suffle function part executes copy() function.
because the part of 'obj.NumObservations = numel(obj.ImagesX.Files)' is not commented, the label don't be outputted.
I think obj.copy() don't copy all element to NewObj, I think. Therefore the label don't come out.
what's the problem of obj.copy()? how to copy all elements? I think it is same manners in subset() fucntion.
So Why I comment the subset part in the class initial part.
----------------------------------------------------------------------------------------------------------------------------------------------
classdef cycleGanImageDatastore < matlab.io.Datastore & ...
matlab.io.datastore.Shuffleable
% cycleGanImageDatastore Create a Datastore to work with collections of images in 2 directory.
% IMDS = cycleGanImageDatastore(Xsize,Ysize,dirX, dirY) creates a Datastore,
% where Xsize/Ysize show the output size of images in X or Y directory
% and dirX/dirY are the path of the directory having image data to be used for training cycleGAN model.
% By calling read(IMDS), you can get unpaired images from each directory.
% Copyright 2019-2020 The MathWorks, Inc.
properties
Xsize
Ysize
DirX
DirY
ImagesX
ImagesY
MiniBatchSize
end
properties (SetAccess = protected)
NumObservations
end
methods
function obj = cycleGanImageDatastore(Xsize,Ysize,dirX, dirY)
obj.Xsize = Xsize;
obj.Ysize = Ysize;
obj.DirX = dirX;
obj.DirY = dirY;
obj.ImagesX = imageDatastore(obj.DirX,'IncludeSubfolders',true,'LabelSource','foldernames');
obj.ImagesY = imageDatastore(obj.DirY,"IncludeSubfolders",true,'LabelSource','foldernames');
obj.MiniBatchSize = 1;
obj.ImagesX.ReadSize = 1;
obj.ImagesY.ReadSize = 1;
%num = min(numel(obj.ImagesX.Files),numel(obj.ImagesY.Files));
%obj.ImagesX = obj.ImagesX.subset(1:num);
%obj.ImagesY = obj.ImagesY.subset(1:num);
%obj.NumObservations = numel(obj.ImagesX.Files);
end
function tf = hasdata(obj)
tf = obj.ImagesX.hasdata() && obj.ImagesY.hasdata();
end
function [data] = read(obj) % 画像の呼び出し:read a image
obj.ImagesX.ReadSize = obj.MiniBatchSize;
obj.ImagesY.ReadSize = obj.MiniBatchSize;
[ImagesX,infoX] = obj.ImagesX.read();
[ImagesY,infoY] = obj.ImagesY.read();
labelsX = infoX.Label;
labelsY = infoY.Label;
ImagesX = imresize(ImagesX,[128,128]);
ImagesY = imresize(ImagesY,[128,128]);
%imshow(ImagesX)
% 出力をCellでそろえる:set data type to cell
if ~iscell(ImagesX)
ImagesX = {ImagesX};
ImagesY = {ImagesY};
end
% 画像の前処理:do the preprocessing
%[transformedX, transformedY] = transformImagePair(obj,ImagesX, ImagesY);
transformedX = ImagesX;
transformedY = ImagesY;
% 正規化する:call function for normalization
[X, Y] = obj.normalizeImages(transformedX, transformedY);
% テーブル化して出力
data = table(X, Y);
end
function reset(obj)
obj.ImagesX.reset();
obj.ImagesY.reset();
end
function objNew = shuffle(obj)
objNew = obj.copy();
numObservations = objNew.NumObservations;
idx1 = randperm(numObservations);
objNew.ImagesX.Files = objNew.ImagesX.Files(idx1);
idx2 = randperm(numObservations);
objNew.ImagesY.Files = objNew.ImagesY.Files(idx2);
end
function [xOut, yOut] = normalizeImages(obj, xIn, yIn)
% 各最大値を元に正規化する:normalization with the max value
xOut = cellfun(@(x) rescale(x,'InputMin',0,'InputMax',255), xIn, 'UniformOutput', false);
yOut = cellfun(@(x) rescale(x,'InputMin',0,'InputMax',255), yIn, 'UniformOutput', false);
end
end
end
function [transformedX, transformedY] = transformImagePair(obj,ImagesX, ImagesY)
arguments
obj
ImagesX (:,1) cell
ImagesY (:,1) cell
end
finalSize = obj.Xsize(1:2); % 最終出力を指定:define the size of output
initialSize = finalSize + 30; % 最初にリサイズする大きさを指定:initial image size before cropping
mirror = rand(1) < 0.5; % 50%の確率で反転:flip or not
% データ拡張を適用:Apply augmentation
transformedX = cellfun(@(im) applyAugmentation(im, initialSize, finalSize, mirror), ...
ImagesX, ...
'UniformOutput', false);
transformedY = cellfun(@(im) applyAugmentation(im, initialSize, finalSize, mirror), ...
ImagesY, ...
'UniformOutput', false);
end
function imOut = applyAugmentation(imIn, initialSize, finalSize, mirror)
imInit = imresize(imIn, initialSize); % 画像をリサイズ
win = randomCropWindow2d(initialSize,finalSize);
imOut = imcrop(imInit,win);
if mirror
imOut = fliplr(imOut); % 左右反転:flip the image
end
end

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