How can i save data from 1*5 cell array into excel file. I have 5 images in loop and i extract glcm features now i want to save each imgaes features but only the last image data is saved.

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Anjali Acharya 2018-8-24

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https://ww2.mathworks.cn/matlabcentral/answers/416070-how-can-i-save-data-from-1-5-cell-array-into-excel-file-i-have-5-images-in-loop-and-i-extract-glcm

评论： Anjali Acharya 2018-8-25

%path D:\matlab\data\Training\glossy\*.jpg
path='D:\matlab\data\Training\test\';
list=dir([path, '*.jpg']);
for x=1:length(list)
  images{x}=imread([path, list(x).name]); 
  if length(size(images{x}))==3 %check if the image I is color
    I=rgb2gray(images{x});
  end;
  offsets0 = [0 1; -1 1; -1 0; -1 -1];
  glcm1 = graycomatrix(I,'offset',offsets0);
  stats{x} = graycoprops(glcm1,{'all'});
  writetable(struct2table(stats{x}), 'test_glcmfeatures.csv')
end

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dpb 2018-8-24

writetable doesn't append (as you found out) unless you use it to write Excel files and use the 'Range' argument to set a location.

Probably simplest solution is to move the write until after the loop finishes and then write the whole array at once.

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采纳的回答

Adam Danz 2018-8-24

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编辑：Adam Danz 2018-8-24

在 MATLAB Online 中打开

A snippet from your code:

    for x=1:length(list)
        ...
        writetable(struct2table(stats{x}), 'test_glcmfeatures.csv')
    end

You are overwriting test_glcmfeatures.csv on every iteration of the loop.

Instead, one solution would be to change the file name and create a new file on each iteration.

    for x=1:length(list)
        ...
        writetable(struct2table(stats{x}), sprintf('test_glcmfeatures_%d.csv', x))
    end

Alternatively, if you want to write everything to the same file, try using the ' range ' (link) property. [Addendum] Or, as @dpb pointed out, you could just collect all of the stats data within the look at write it all in one file after the loop (which would be simpler than using the 'range' property).

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Anjali Acharya 2018-8-25

test1.m

For now I have features value saved in csv file for last 5th image only in this format as shown in figure below:

Anjali Acharya 2018-8-25

Hello #dbp i want to use these features for training a classifier ad use it for texture classification. I will resize all image to some fix size may be 512*512 before GLCM features.

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