I am writing a program in IDL that requires reading n images (each of m pixels) from a directory, convert them to grayscale, concatenate each image as a single vector, and then form a an m * n matrix from the data.
So far I have managed to read and convert a single image to a grayscale vector, but I can't figure out how to extend this to reading multiple image files.
Can anyone advise on how I could adapt my code in order to do this?
(The image files will all be of the same size, and stored in the same directory with convenient filenames - i.e. testpicture1, testpicture2, etc)
Thanks
pro readimage
image = READ_IMAGE('Z:\My Documents\testpicture.jpg')
redChannel = REFORM(image[0, *, *])
greenChannel = REFORM(image[1, * , *])
blueChannel = REFORM(image[2, *, *])
grayscaleImage = BYTE(0.299*FLOAT(redChannel) + $
0.587*FLOAT(greenChannel) + 0.114*FLOAT(blueChannel))
imageVec = grayscaleImage[*]
end
Use FILE_SEARCH to find the names and number of the images of the given name:
filenames = FILE_SEARCH('Z:\My Documents\testpicture*.jpg', count=nfiles)
You will probably also want to declare an array to hold your results:
imageVec = bytarr(m, nfiles)
Then loop over the files with a FOR loop doing what you are doing already:
for f = 0L, nfiles - 1L do begin
; stuff you are already doing
imageVec[*, f] = grayscaleImage[*]
endfor
Related
Hello dear programmers,
I have a sequence of images and I would like to perform dilation on each of them with different dilation parameters. Then, I would like to save the processed images with new name including both the old name and the corresponding dilation parameter. My codes are as follows.
Input_folder =
Output_folder =
D = dir([Input_folder '*.jpg']);
Inputs = {D.name}';
Outputs = Inputs; % preallocate
%print(length(Inputs));
for k = 1:length(Inputs)
X = imread([Input_folder Inputs{k}]);
dotLocations = find(Inputs{k} == '.');
name_img = Inputs{k}(1:dotLocations(1)-1);
image1=im2bw(X);
vec = [3;6;10];
vec_l = length(vec);
for i = 1:vec_l
%se = strel('disk',2);
fprintf(num2str(vec(i)));
se = strel('diamond',vec(i)); %imdilate
im = imdilate(image1,se);
image2 = im - image1;
Outputs{k} = regexprep(Outputs{k}, name_img, strcat(name_img,'_', num2str(vec(i))));
imwrite(image2, [Output_folder Outputs{k}])
end
end
As it can be seen, I would like to apply dilation with parameters 3,6 and 10. Let us assume that an image has as name "image1", after processing it, I would like to have "image1_3", "image1_6" and "image1_10". However, I am getting as results "image1_3", "image1_6_3" and "image1_10_6_3". Please, how can I modify my codes to fix this problem?
This is because you rewrite each item of the Outputs variable three times, each time using the previous value to create a new value. Instead, you should use the values stored in Inputs new names. Another mistake in your code is that the size of Inputs and Outputs are equal, while for every file in the input folder, three files must be stored in the output folder.
I also suggest using fileparts function, instead of string processing, to get different parts of a file path.
vec = [3;6;10];
vec_l = length(vec);
Outputs = cell(size(Inputs, 1)*vec_l, 1); % preallocate
for k = 1:length(Inputs)
[~,name,ext] = fileparts([Input_folder Inputs{k}]);
% load image
for i = 1:vec_l
% modify image
newName = sprintf('%s_%d%s', name, vec(i), ext);
Outputs{(k-1)*vec_l+i} = newName;
imwrite(image2, [Output_folder newName])
end
end
I'm writing a program in IDL to read DICOM images, then store them in a big matrix and finally save them in .dat file. The DICOMs are under the name IM0,IM1,IM2,..IM21777. I wrote the code below but I am getting an error. I am using IDL version 6.4.
files = file_search('E:\SE7\IM*)
n_files = n_elements(files)
full_data = fltarr(256,256,n_files)
for i=0L, n_files-1 do begin
full_data[*,*,i] = read_dicom('E:\SE7\IM')
endfor
path = 'E:\'
open, 1, path + "full_data.dat'
writeu, 1, full_data
close, 1
I am not sure how to loop over the DICOM name i.e. IM0, IM1,IM2 etc
After I store them in the big matrix (i.e. full_data =[256,256,2178]) I would like to make the 3D matrix 4D. Is that possible? I would like to make it have the dimensions [256, 256, 22, 99] i.e. 2178/99.
I'm not sure what error you are getting, but you are missing a quotation mark in the first line. It should be:
files = file_search('E:\SE7\IM*')
To loop over the DICOM name, you can string concatenate the loop index using + and STRTRIM() as follows:
for i=0L, n_files-1 do begin
full_data[*,*,i] = read_dicom('E:\SE7\IM'+STRTRIM(i,2))
endfor
Finally, to turn your (256,256,2178) matrix into a (256,256,22,99) matrix, use REBIN:
final_data = REBIN(full_data, 256, 256, 20, 99)
Depending on the way you want the dimensions arranged, you may need additional operations. This post is a great primer on how to manipulate arrays and their dimensionality: Coyote Dimensional Juggling Tutorial.
I've been using MATLAB to read through a bunch of output files and have noticed that it was reading the files fairly slowly in comparison to a reader that I wrote in Python for the same files (on the order of 120s for MATLAB, 4s for Python on the same set). The files have a combination of letters and numbers, where the numbers I actually want each have a unique string on the same line, but there is no real pattern to the rest of the file. Is there a faster way to read in non-uniformly formatted text files in MATLAB?
I tried using the code profiler in MATLAB to see what takes the most time, and it seemed to be the strfind and strsplit functions. Deeper down, the strfun\private\strescape seems to be the culprit which takes up around 50% of the time, which is called by strsplit function.
I am currently using a combination of strfind and strsplit in order to search through a file for 5 specific strings, then convert the string after it into a double.
lots of text before this
#### unique identifying text here
lots of text before this
sometext X = #####
Y = #####
Z = #####
more text = ######
I am iterating through the file with approximately the following code, repeated for each number that is being found.
fid=fopen(filename)
tline=fgets(fid)
while ischar(tline)
if ~isempty(strfind(tline('X =')))
tempstring=strsplit(tline(13:length(tline)),' ');
result=str2double(char(tempstring(2)));
end
tline=fgets(fid);
end
I'm guessing this will be a bit faster, but maybe not by much.
s = fileread('texto');
[X,s] = strtok(strsplit(s, "X = "){2}); X = str2num(X);
[Y,s] = strtok(strsplit(s, "Y = "){2}); Y = str2num(Y);
[Z,s] = strtok(strsplit(s, "Z = "){2}); Z = str2num(Z);
Obviously this is highly specific to your text example. You haven't given me any more info on how the variables might change etc so presumably you'll have to implement try/catch blocks if files are not consistent etc.
PS. This is octave syntax which allows chaining operations. For matlab, split them into separate operations as appropriate.
EDIT: ach, nevermind, here's the matlab compatible one too. :)
s = fileread('texto');
C = strsplit(s, 'X = '); [X,s] = strtok(C{2}); X = str2num(X);
C = strsplit(s, 'Y = '); [Y,s] = strtok(C{2}); Y = str2num(Y);
C = strsplit(s, 'Z = '); [Z,s] = strtok(C{2}); Z = str2num(Z);
I have matrix with 400 rows and 40 columns.
I would like to create a new matrix from this data where I calculate the concordance between 2 variables, i.e., concord [A1,B1]=number1; concord [A1,B2]=number2; [A1,B39]=number39. So, number1 should now be the first number of the first row of a new matrix; number 2 is the second number in the first row....
The end result is a new matrix that shows the rho_c for each pair of numbers in the original data matrix.
The original matrix has a lot of empty cells. I can also create multiple matrix of subsections of concordance calculations, it doesn't matter much. However, I don't quite understand how to write this command in mata.
I've searched here: http://jasoneichorst.com/wp-content/uploads/2012/01/BeginMatrix.pdf
EDIT: The data looks like this (variable "Score1" is a rater). Not all raters rate the same item.
enter image description here
Assuming I fully understand the question, there are methods to do this. One which comes to mind involves the use of concord available from SSC (ssc install concord) along with some local macros and loops.
/* Clear and set up sample data */
clear *
set obs 60
forvalues i = 1/6 {
gen A`i' = runiform()
}
replace A2 = . in 10/L
replace A3 = . in 1/5
replace A3 = . in 20/L
replace A4 = . in 1/20
replace A4 = . in 30/L
replace A5 = . in 1/15
replace A5 = . in 40/L
replace A6 = . in 1/40
/* End data set-up */
* describe, varlist will allow you to store your variables in a local macro
qui describe, varlist
local vars `r(varlist)'
* get number of variables in local macro vars
local varcount : word count `vars'
* Create a matrix to hold rho_c
mat rho = J(6,6,.)
mat rownames rho = `vars'
mat colnames rho = `vars'
* Loop through vars to run concord on all unique combinations of A1-A6
* using the position of each variable in local vars to assign the var name
* to local x and local y
* concord is executed only for j >= i so that you don't end up with two sets
* of the same variables being ran (eg., A1,A2 and A2,A1)
forvalues i = 1/`varcount' {
local y `: word `i' of `vars''
forvalues j = 1/`varcount' {
local x `: word `j' of `vars''
if `j' >= `i' {
capture noisily concord `y' `x'
mat rho[`i',`j'] = r(rho_c)
}
}
}
* Display the results stored in the matrix, rho.
mat list rho
The above code should get you started, but there may need to be changes made depending on exactly what you want to do.
You will notice that inside of the loop, I have included capture noisily before concord. The reason for this is because in the image you linked to, your variables were missing values across entire sections of observations. This will likely result in an error message being thrown (specifically, r(2000): no observations). The capture piece forces Stata to continue to execute the loop if an error occurs there. The noisily piece tells Stata to display the output from concord even though capture was specified.
Also, if you search help concord in Stata, you will be directed to the help page which indicates that the concordance correlation coefficient is stored in r(rho_c). You can store these as individual scalars inside the loop or do as in the example and create a kxk matrix of values.
I have certain images in a directory and I want to load all those images to do some processing. I tried using the load function.
imagefiles = dir('F:\SIFT_Yantao\demo-data\*.jpg');
nfiles = length(imagefiles); % Number of files found
for i=1:nfiles
currentfilename=imagefiles(i).name;
I2 = imread(currentfilename);
[pathstr, name, ext] = fileparts(currentfilename);
textfilename = [name '.mat'];
fulltxtfilename = [pathstr textfilename];
load(fulltxtfilename);
descr2 = des2;
frames2 = loc2;
do_match(I1, descr1, frames1, I2, descr2, frames2) ;
end
I am getting an error as unable to read xyz.jpg no such file or directory found, where xyz is my first image in that directory.
I also want to load all formats of images from the directory instead of just jpg...how can i do that?
You can easily load multiple images with same type as follows:
function Seq = loadImages(imgPath, imgType)
%imgPath = 'path/to/images/folder/';
%imgType = '*.png'; % change based on image type
images = dir([imgPath imgType]);
N = length(images);
% check images
if( ~exist(imgPath, 'dir') || N<1 )
display('Directory not found or no matching images found.');
end
% preallocate cell
Seq{N,1} = []
for idx = 1:N
Seq{d} = imread([imgPath images(idx).name]);
end
end
I believe you want the imread function, not load. See the documentation.
The full path (inc. directory) is not held in imgfiles.name, just the file name, so it can't find the file because you haven't told it where to look. If you don't want to change directories, use fullfile again when reading the file.
You're also using the wrong function for reading the images - try imread.
Other notes: it's best not to use i for variables, and your loop is overwriting I2 at every step, so you will end up with only one image, not four.
You can use the imageSet object in the Computer Vision System Toolbox. It loads image file names from a given directory, and gives you the ability to read the images sequentially. It also gives you the option to recurse into subdirectories.