I have a matlab function img_process that requires the following parameters : image_name intensity and boundary, so if I run the following on my matlab console :
img_process 'pic1.png' 0.01 1
This will run the function and the image will be processed and I will get a result printed out.
Now I have compiled the script as a windows standalone app named img_process_test. I then try to run it from my command line in windows from the distrib folder like :
img_process_test 'pic1.png' 0.01 1
and it will tell me that error imread , file was not found.
I did try to place the pic1.png in the distrib and src and the img_process_test folders but still it will not work.
Any idea ?
Thank you for looking
I have fixed this. I found a good help here : http://blogs.mathworks.com/loren/2010/12/21/strings-and-numbers-as-arguments/
in case someone stumbles into this and would like to know a workaround.
Related
Currently I am working a project that has have been using the pathlib library so I can work on my Windows desktop when I need too and on my MacBook Pro. Essentially be able to work between both operating systems. I have not have any issues at all until right now. Here is the set up:
I have a pipeline set up to automatically save a .joblib and a whole lot of .png files that will go to a directory called
output_dir = Path('../Trained_Models/Differential_gene_analysis/A Kidney Cancer Transcriptome Molecular Signature Identifies Tumors with Tumor Thrombus/Models train on TCGA data and test on Rodriguez data/Oct-XX-20XX')
For example, if I want to save a .joblib file under the name RandomForest_TumorThrombus_104.joblib,I would use the command
joblib.dump(model ,output_dir / 'RandomForest_TumorThrombus_104.joblib')
On my MacBook Pro, I have no issues when this is ran, but on Windows it gives me the following error
FileNotFoundError: [Errno 2] No such file or directory: '..\\Trained_Models\\Differential_gene_analysis\\A Kidney Cancer Transcriptome Molecular Signature Identifies Tumors with Tumor Thrombus\\Models train on TCGA data and test on Rodriguez data\\Oct-17-2022\\RandomForest_TumorThrombus_104.joblib'
I have tried to use the .resolve() method to get the absolute path but still gives me the same error. I have tried to experiment to try to see what is goin on such as using os.path.exists(). When using the os.path.exists() method I get True for the follwoing command:
os.path.exists(output_dir)
So it does indeed recognize that the directory exists. The next thing I tried was to rename the file to something like dddddd.joblib and that worked. But I find that only a few names for the file would allow me to save the files. During debug I found that the most recent Traceback occurs here:
with open(filename, 'wb') as f:```
I was wondering if anyone here had any idea what was going on here and how I can fix this issue? Please and Thank you.
The solution was to enable long paths on Windows.
I am trying to run the hyphae (fungus) using the code provided here : https://github.com/petercollingridge/code-for-blog/blob/master/hyphae/hyphae.py
But, when I run the code I get this error in terminal: Blocking request with no referer...
Furthemore, does anyone have any simulations on hypahe ?
Thanks again
I am trying to run this simple command on Matlab to load a VST:
hostedPlugin = loadAudioPlugin(pluginpath)
However, I am getting the following error: Undefined function or variable 'loadAudioPlugin'.
What's wrong? I can't seem to figure it out... This is the output I get when I type the "ver" command:
...
Audio System Toolbox Version 1.2 (R2017a)
...
The Audio system toolbox seems to be installed correctly. And the path is set correctly apparently, I can see the "loadAudioPlugin.p" file in the compiled folder.
Any ideas why Matlab says the loadAudioPlugin is not a function??
Using Cudafy version 1.29, which can be downloaded from here
I am executing the examples that are found in the install folder CudafyV1.29\CudafyByExample\
Specifically, "chapter 3" example that begins line 42 of program.cs calls the following:
simple_kernel.Execute();
which is this:
public static void Execute()
{
CudafyModule km = CudafyTranslator.Cudafy(); // <--exception thrown!
GPGPU gpu = CudafyHost.GetDevice(CudafyModes.Target, CudafyModes.DeviceId);
gpu.LoadModule(km);
gpu.Launch().thekernel(); // or gpu.Launch(1, 1, "kernel");
Console.WriteLine("Hello, World!");
}
The indicated line throws this exception:
Compilation error: CUDAFYSOURCETEMP.cu
'C:\Program' is not recognized as an internal or external command,
operable program or batch file. .
Which is immediately obvious that the path has spaces and the programmer did not double quote or use ~ to make it operational.
So, I did not write this code. And I cannot step through the sealed code contained within CudafyModule km = CudafyTranslator.Cudafy();In fact I don't even know the full path that is causing the exception, it is cut-off in the exception message.
Does anyone have a suggestion for how to fix this issue?
Update #1: I discovered where CUDAFYSOURCETEMP.cu lives on my computer, here it is:
C:\Users\humphrt\Desktop\Active Projects\Visual Studio
Projects\CudafyV1.29\CudafyByExample\bin\Debug
...I'm still trying to determine what the program is looking for along the path to 'C:\Program~'.
I was able to apply a workaround to bypass this issue. The workaround is to reinstall all components of cudafy in to folders with paths with no ' ' (spaces). My setup looks like the below screenshot. Notice that I also installed the CUDA TOOLKIT from NVIDIA in the same folder - also with no spaces in folder names.
I created a folder named "C:\CUDA" and installed all components within it, here is the folder structure:
everyone!
I'm trying to parallelize an algorithm that uses mex files from mexopencv (KNearest.m, KNearest_.mexw32).
The program is based vlfeat (vlsift.mex32) + mexopencv (KNearest.m and KNearest_.mexw32).I classify descriptors obtained from images.
All the code is located on the fileshare
\\ LAB-07 \ untitled \ DISTRIB \ (this is the program code)
\\ LAB-07 \ untitled \ + cv (mexopencv)
When I run the program with matlabpool close everything works well.
Then I make matlabpool open (2 computers on 2 cores each. ultimately 4 worker, but now I use for testing only 2 workers on the computer and run the program which)
PathDependencises from fileshare -> \LAB-07\untitled\DISTRIB\ , \LAB-07\untitled+cv
Before parfor loop I train classifier on the local machine
classifiers = cv.KNearest
classifiers.train(Descriptors',Labels','MaxK',1)
Then run parfor
descr=vlsift(img);
PredictClasses = classifiers.predict(descr');
Error
Error in ==> KNearest>KNearest.find_nearest at 173
Invalid MEX-file '\\LAB-07\untitled\+cv\private\KNearest_.mexw32':
The specified module could not be found.
That is KNearest.m finds, but no KNearest_.mexw32. Because KNearest_.mexw32 located in private folder, I changed the code KNearest.m (everywhere where it appeal KNearest_ () changed to cv.KNearest_ (). Example: this.id = сv.KNearest_ ()) and placed in a folder with KNearest_.mexw32 KNearest.m. As a result, get the same error
Immediately after matlabpool open file search on workers
pctRunOnAll which ('KNearest.m')
'KNearest.m' not found.
'KNearest.m' not found.
'KNearest.m' not found.
pctRunOnAll which ('KNearest_.mexw32')
'KNearest_.mexw32' not found.
'KNearest_.mexw32' not found.
'KNearest_.mexw32' not found.
after cd \LAB-07\untitled+cv
pctRunOnAll which ('KNearest.m')
\\LAB-07\untitled\+cv\KNearest.m
\\LAB-07\untitled\+cv\KNearest.m % cv.KNearest constructor
\\LAB-07\untitled\+cv\KNearest.m
>> pctRunOnAll which ('KNearest_.mexw32')
\\LAB-07\untitled\+cv\KNearest_.mexw32
\\LAB-07\untitled\+cv\KNearest_.mexw32
\\LAB-07\untitled\+cv\KNearest_.mexw32
I ran and FileDependecies, but the same result.
I do not know this is related or not, I display during the execution of the program classifiers
after training and before parfor
classifiers =
cv.KNearest handle
Package: cv
Properties:
id: 5
MaxK: 1
VarCount: 128
SampleCount: 9162
IsRegression: 0
Methods, Events, Superclasses
Within parfor before classifiers.predict
classifiers =
cv.KNearest handle
Package: cv
Properties:
id: 5
I tested the file cvtColor.mexw32. I left in a folder only 2 files cvtColor.mexw32 and vl_sift
parfor i=1:2
im1=imread('Copy_of_start40.png');
im_vl = im2single(rgb2gray(im1));
desc=vl_sift(im_vl);
im1 = cvtColor(im1,'RGB2GRAY');
end
The same error, and vl_sift work, cvtColor no...
If the worker machines can see the code in your shared filesystem, you should not need FileDependencies or PathDependencies at all. It looks like you're using Windows. It seems to me that the most likely problem is file permissions. MDCS workers running under a jobmanager on Windows by default run not using your own account (they run using the "LocalSystem" account I think), and so may well simply not have access to files on a shared filesystem. You could try making sure your code is world-readable.
Otherwise, you can add the files to the pool by using something like
matlabpool('addfiledependencies', {'\\LAB-07\untitled\+cv'})
Note that MATLAB interprets directories with a + in as defining "packages", not sure if this is intentional in your case.
EDIT
Ah, re-reading your original post, and your comments below - I suspect the problem is that the workers cannot see the libraries on which your MEX file depends. (That's what the "Invalid MEX-file" message is indicating). You could use http://www.dependencywalker.com/ to work out what are the dependencies of your MEX file, and make sure they're available on the workers (I think they need to be on %PATH%, or in the current directory).
Edric thanks. There was a problem in the PATH for parfor. With http://www.dependencywalker.com/ looked missing files and put them in a folder +cv. Only this method works in parfor.
But predict in parfor gives an error
PredictClasses = classifiers.predict(descr');
??? Error using ==> parallel_function at 598
Error in ==> KNearest>KNearest.find_nearest at 173
Unexpected Standard exception from MEX file.
What() is:..\..\..\src\opencv\modules\ml\src\knearest.cpp:365: error: (-2) The search
tree must be constructed first using train method
I solved this problem by calling each time within parfor train
classifiers = cv.KNearest
classifiers.train(Descriptors',Labels','MaxK',1)
But it's an ugly solution :)