im trying to load a group of images with the extension'.BMP' to matlab to do some process over each, and here is my code:
s=dir('*.jpg')
numel(s)
for n=1:numel(s)
load(s(n).name);
% my processes over each image
end
but i got this errur:
Error using load
Number of columns on line 3 of ASCII file
D:\Study\Memo_Master\Group Images
Comprission\Matlabs\1.bmp must be the same as
previous lines.
where '1.bmp' is a image exist in the file destination.
ANY HELP??
The load function is aimed at loading mat-files (i.e. binary data files), not images. To load images, you should use the imread function instead.
In your code:
s = dir('*.bmp');
for n = 1:numel(s)
Img = imread(s(n).name);
% my processes over each image
end
Best,
Related
I have multiple small *.mat files, each containing 4 input images (template{1:4} and a second channel template2{1:4}) and 4 output images (region_of_interests{1:4}), a binarized ('mask') image to train a deep neural network.
I basically followed an example on Mathworks and it suggests to use a function (in this example #matreader) to read in custom file formats.
However ...
It seems impossible to load multiple images from one *.mat file using any load function as it only allows one output, and imageDatastore doen't seem to allow loading data from workspace. How could this be achieved?
Similarly, it seems impossible to load a pixelLabelDatastore from a workspace variable. As a workaround I ended up saving the contents of my *.mat file to an image (using imwrite, saving to save_dir), and re-loading it from there (in this case, the function doesn't even allow to load *.mat files.). (How) can this be achieved without re-saving the file as image?
Here my failed attempt to do so:
%main script
image_dir = pwd; %location of *.mat files
save_dir = [pwd '/a/']; %location of saved output masks
imds = imageDatastore(image_dir,'FileExtensions','.mat','ReadFcn',#matreader); %load template (input) images
pxds = pixelLabelDatastore(save_dir,{'nothing','something'},[0 255]);%load region_of_interests (output) image
%etc, etc, go on to train network
%matreader function, save as separate file
function data=matreader(filename)
in=1; %give up the 3 other images stored in template{1:4}
load(filename); %loads template and template2, containing 4x input images each
data=cat(3,template{in},template2{in}); %concatinate 2 template input images in 3rd dimension
end
%generate example data for this question, will save into a file 'example.mat' in workspace
for ind=1:4
template{ind}=rand([200,400]);
template2{ind}=rand([200,400]);
region_of_interests{ind}=rand([200,400])>.5;
end
save('example','template','template2','output')
You should be able to achieve this using the standard load and save function. Have a look at this code:
image_dir = pwd;
save_dir = pwd;
imds = imageDatastore(image_dir,'FileExtensions',{'.jpg','.tif'});
pxds = pixelLabelDatastore(save_dir,{'nothing','something'},[0 255]);
save('images.mat','imds', 'pxds')
clear
load('images.mat') % gives you the variable "imds" and "pxds" directly -> might override previous variables
tmp = load('images.mat'); % saves all variables in a struct, access it via tmp.imds and tmp.pxds
If you only want to select the variables you want to load use:
load('images.mat','imds') % loads "imds" variable
load('images.mat','pxds') % loads "pxds" variable
load('images.mat','imds','pxds') % loads both variables
EDIT
Now I get the problem, but I fear this is not how it is going to work. The Idea behind the Datastore objects is, that it is used if the data is too big to fit in memory as a whole, but every little piece is small enough to fit in memory. You can use the Datastore object than to easily process and read multiple files on a disk.
This means for you: Simply save your images not as one big *mat file but as multiple small *.mat files that only contain one image.
EDIT 2
Is it strictly necessary to use an imageDatastore for this task? If not you can use something like the following:
image_dir = pwd;
matFiles = dir([image_dir '*.mat']);
for i=1:length(matFiles)
data = load(matFiles(i).name);
img = convertMatToImage(data); % write custom function which converts the mat input to your image
% or something like this:
% for j=1:4
% img(:,:,j) = cat(3,template{j},template2{j});
% end
% process image
end
another alternative would be to create a "image" in your 'matreader' which does not only have 2 bands but to simply put all bands (all templates) on top of each other providing a "datacube" and then in an second step after iterating over all small mat files and reading them splitting the single images out of the one bigger datacube.
would look something like this:
function data=matreader(filename)
load(filename);
for in=1:4
data=cat(3,template{in},template2{in});
end
end
and in your main file, you have to simply split the data into 4 pieces.
I have never tested it but maybe it is possible to return a cell instead of a matrix?
function data=matreader(filename)
load(filename);
data = cell(1,4)
for in=1:4
data{in}=cat(3,template{in},template2{in});
end
end
Not sure if this would work.
However, the right way to go forward from here really depends on how you plan to use the images from imds and if it is really necessary to use a imageDatastore.
I have 360 3D-nifti files, I want to read all these files and save into one nifti file using Nifti Analyze tool that should yield a 4D file of large size. So far I have written following lines
clear all;
clc;
fileFolder=fullfile(pwd, '\functional');
files=dir(fullfile(fileFolder, '*.nii'));
fileNames={files.name};
for i=1:length(fileNames)
fname=fullfile(fileFolder,fileNames{i});
z(i)=load_nii(fname);
y=z(i).img;
temp(:,:,:,i) = make_nii(y);
save_nii(temp(:,:,:,i), 'myfile.nii')
fprintf('Iter: %d\n', i)
end
This code facilitates with a variable temp that is 4D struct and contains all the images. However, myfile.nii is just one single file its not all the images because its size is just 6mb it should be atleast one 1gb.
Can someone please have a look and let me know where I am wrong?
The way that you have it written, your loop is overwriting myfile.nii since you're calling save_nii every time through the loop with only the latest data. You'll want to instead call save_nii only once outside of the loop and save the entire temp variable at once.
for k = 1:numel(fileNames)
fname = fullfile(fileFolder, fileNames{k});
z(k) = load_nii(fname);
y(:,:,:,k) = z(k).img;
end
% Create the ND Nifti file
output = make_nii(y);
% Save it to a file
save_nii(output, 'myfile.nii')
I'm using MATLAB_R2011a_student. I have some image stacks saved as 32 bit tiffs, some over 1000 frames. I would like to be able to pull out a specific frame from the stack and save it as a 32 bit tiff or some readable format where there would be no data loss from the original. Currently my code looks like this:
clear, clc;
k=163;
image=('/Users/me/Filename.tiff');
A = uint8(imread(image, k));
B=A(:,:,1);
J=imadjust(B,stretchlim(B),[]);
imwrite(J,'/Users/me/163.tif','tif');
(I'm assuming reading it as 8 bit, and the way I'm saving are not the best way to do this)
Either way this code works for a seemingly random number of frames (for example in one file.tiff the above code works for frames 1-165 but none of the frames after 165, for a different file.tiff the code works for frames 1-8 but none of the frames after 8) I'm also getting a strange horizontal line in the output image when this does work:
??? Error using ==> rtifc
Invalid TIFF image index specified.
Error in ==> readtif at 52
[X, map, details] = rtifc(args);
Error in ==> imread at 443
[X, map] = feval(fmt_s.read, filename, extraArgs{:});
Thanks!
The best way (in my opinion) to handle tiff stacks is to use the Tiff library available since a few years. I must admit that I don't know much about OOP but I managed to understand enough to load a tiff stack and manipulate it.That's the kind of simple demo I wish I had seen a year ago haha.
I the following example I load a single stack and store it all into a 3D array. I use imfinfo to fetch infos about the images, notably the number of images/stack and the actual image dimensions. If you want you can choose to load only one image using appropriate indices. Please try the code below and play around with it; you'll understand what I mean.
clear
clc
%// Get tiff files you wish to open
hFiles = dir('*.tif');
%// Here I only have 1 multi-tiff file containing 30 images. Hence hInfo is a 30x1 structure.
hInfo = imfinfo(hFiles(1).name);
%// Set parameters.
ImageHeight = hInfo(1).Height;
ImageWidth = hInfo(1).Width;
SliceNumber = numel(hInfo);
%// Open Tiff object
Stack_TiffObject = Tiff(hFiles.name,'r');
%// Initialize array containing your images.
ImageMatrix = zeros(ImageHeight,ImageWidth,SliceNumber,'uint32');
for k = 1:SliceNumber
%// Loop through each image
Stack_TiffObject.setDirectory(k)
%// Put it in the array
ImageMatrix(:,:,k) = Stack_TiffObject.read();
end
%// Close the Tiff object
Stack_TiffObject.close
Hope that helps.
I have some very large Tiff images that I am trying to use in a MATLAB GUI application. If I try to load the images using imshow, I get an out-of-memory error. (Yes, I know MATLAB is not the best choice for GUIs or loading large images, but there is good reason for using MATLAB in this case).
I can obviously create a reduced resolution data set (rset file) and use imtool to view the image, but this is not helpful as I want a user to be able to interact with the image by clicking on it to extract (x,y) coords into the application. Imshow does not seem to be directly compatible with rset files. Is there a way for me to load an rset'd image in a panable/zoomable figure, or any other way I can achieve the goal?
I looked at the code for imtool but it seems to be using undocumented classes to read rset files and I can't replicate its behaviour.
You can use low-level file I/O functions of MATLAB to read the entirety or parts of the TIFF image in order to avoid the OOM problem.
fileName = 'LargeTiff.tif';
info = imfinfo(fileName)
% Determine number of frames
nFramesStr= regexp(info.ImageDescription, 'images=(\d*)', 'tokens');
nFrames = str2double(nFramesStr{1}{1});
% Use low-level File I/O functions to read the file
fp = fopen(fileName , 'rb');
% The "StripOffsets" field provides the offset to the first strip.
fseek(fp, info.StripOffsets, 'bof');
% Assume that the image format is 16-bit per pixel and is big-endian
% Also assume that the images are stored one after the other
% For example, read the first 100 frames
frameNum = 100;
imData = cell(1, frameNum);
for cnt = 1 : frameNum
imData{cnt} = fread(fp, [info.Width info.Height], 'uint16', 0, 'ieee-be');
end
fclose(fp);
It looks like my problem is that I simply don't have enough memory to load the whole tiff, and that there is no public specification for the rset files format. So I am going to instead solve the problem by creating my own version of a reduced resolution data set. I should be able to load block sections of the image, resave them and then dynamically load and unload only the needed high-res blocks at zoom, and load a reduced resolution overview when zoomed out.
You can write a callback function to get the pixel co-ordinates (X,Y) from imtool then convert to a tile number and tile index using the code below. You can then utilise the readencodedtile function in matlab
function [tileidx,Tile_num] = getTileInfo(tiffile,X,Y)
A = Tiff(tiffile);
tile_width = A.getTag('TileWidth');
tile_length = A.getTag('TileLength');
SizeA = size(A);
tt = sub2ind(SizeA,X,Y);
% Example only
% X = repmat((1:10)',1,10);
% Y = repmat((1:10),10,1);
% A = reshape(1:100,10,10);
% SizeA = size(A);
% tile_width = 3;
% tile_length = 2;
tileidx = rem(tt-(Y-1)*SizeA(1)-1,tile_length)+1 ...
+ tile_length*rem(Y+tile_width-1,tile_width);
Tile_num = ceil(Y/tile_width)+ ...
(ceil(X/tile_length)-1)*ceil(SizeA(2)/tile_width);
I made a program in MATLAB to generate images with different specifications, but each time I change one of theses specifications I had to re-save the image under a different name and path. So, I made a for loop to change these specifications, but I don't know how I can make MATLAB save the generated image with different names and different paths...
How can I write a program to make MATLAB save multiple generated images with different names and different paths as a part of for–loop?
Put something like this at the end of your loop:
for i = 1:n
<your loop code>
file_name=sprintf('%d.jpg',i); % assuming you are saving image as a .jpg
imwrite(your_image, file_name); % or something like this, however you choose to save your image
end
If you want to save JPEG, PNG etc., then see #AGS's post. If you want to save FIG files, use
hgsave(gcf, file_name)
instead of the imwrite line. There's also
print('-djpeg', file_name) %# for JPEG file (lossy)
print('-dpng', file_name) %# for PNG file (lossless)
as an alternative for imwrite.
Since I wanted to save the plots in my loop in a specific folder in my present working directory (pwd), I modified my naming routine as follows:
for s = 1:10
for i = 1:10
<loop commands>
end
end
% prints stimuli to folder created for them
file_name=sprintf('%s/eb_imgs/%0.3f.tif',pwd,s(i)); % pwd = path of present working
% directory and s(i) = the value
% of the changing variable
% that I wanted to document
file_name = /Users/Miriam/Documents/PSYC/eb_imgs/0.700.tif % how my filename appears
print('-dtiff', '-r300', file_name); % this saves my file to my desired location
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