I am trying to create .fits files using the matlab.io.fits functions, following the example given here: matlab.io.fits.createFile.
However, this gives me the following error:
>> import matlab.io.*
>> fptr = fits.createFile('myfile.fits');
??? Undefined variable "fits" or class "fits.createFile".
Importing the fits class directly also gives an error:
>> import matlab.io.fits
??? Import argument 'matlab.io.fits' cannot be found or cannot be imported
I get the same result in Matlab2009 and 2015.
What am I doing wrong? Do I need to install a specific class? I am new to Matlab, so it might be a very easy mistake, but some of my more Matlab proficient colleagues has not been able to solve the problem.
This error indicate that the function cannot be found. This is usually caused by the MATLAB path being corrupted. You can restore it with:
>> restoredefaultpath
>> rehash toolboxcache
You can figure out if the file is found by executing:
>> which -all matlab.io.fits.createFile
The file should be in <matlabroot>/toolbox/matlab/imagesci/+matlab/+io/+fits/createFile.m. If it is not there, you probably need to reinstall MATLAB.
Related
I have a Julia module in which I would like to import the Python function sympy.physics.wigner.wigner_9j. My minimal example module is as follows:
module my_module
using PyCall
using SymPy
export test
test()=sympy.physics.wigner.wigner_9j(1,1,1,1,1,1,1,1,1)
end
Then in my Julia notebook running:
using my_module
test()
gives
KeyError: key :physics not found
However adding to the notebook
#pyimport sympy.physics.wigner as sympy_wigner
sympy_wigner.wigner_9j(1,1,1,1,1,1,1,1,1)
gives the correct output. For some reason using #pyimport inside modules gives errors, which I typically avoid by using an __init__ inside my module, e.g adding to my_module.jl
const camb=PyNULL()
function __init__() # this should probably go in SFBBispectrum.jl
copy!(camb, pyimport_conda("camb", "camb", "conda-forge"))
pars=camb.CAMBparams()
end
which allows me to access camb.CAMBparams. Unfortunately I am failing to do something similar for sympy.physics.wigner.wigner_9j.
It has been awhile, but does this help https://github.com/JuliaPy/SymPy.jl/blob/master/src/physics.jl
I'm a beginner at OpenCV, and trying to run an open-source program.
http://asrl.utias.utoronto.ca/code/gpusurf/index.html
I currently have the Computer Vision Toolbox OpenCV Interface 20.1.0 installed and Computer Vision Toolbox 9.2.
I cannot run this simple open-source feature matching algorithm without encountering errors.
import cv2
import matplotlib.pyplot as plt
%matplotlib inline
% read images
img1 = cv2.imread('[INSERT PATH #1]');
img2 = cv2.imread('[INSERT PATH #2]');
img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY);
img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY);
%sift
sift = cv2.xfeatures2d.SIFT_create();
keypoints_1, descriptors_1 = sift.detectAndCompute(img1,None);
keypoints_2, descriptors_2 = sift.detectAndCompute(img2,None);
len(keypoints_1), len(keypoints_2)
The following message is returned:
Error: File: Keypoints.m Line: 1 Column: 8
The import statement 'import cv2' cannot be found or cannot be imported. Imported names must end with '.*' or be
fully qualified.
However, when I remove Line 1, I instead get the following error.
Error: File: Keypoints.m Line: 2 Column: 8
The import statement 'import matplotlib.pyplot' cannot be found or cannot be imported. Imported names must end
with '.*' or be fully qualified.
Finally, following the error message only results in a sequence of further errors from the cv2 library. Any ideas?
That's because the code you've used isn't MATLAB code, it's python code.
As per the website you've linked:
From within Matlab
The parallel implementation coded in Matlab can be run by using the surf_find_keypoints() function. The output keypoints can be sorted by strength using surf_best_n_keypoints(), and plotted using surf_plot_keypoints().
Check that you've downloaded the correct files and try again.
Furthermore, the Matlab OpenCV Interface is designed to integrate C++ OpenCV code, not python. Documentations here.
Yes, it is correct that this is Python code. I would recommend checking your dependencies/libraries. The PyCharm IDE is what I personally use since it takes care of all the libraries easily.
If you do end up trying out PyCharm click on the red icon when hovering on CV2. It’ll then give you a prompt to download the library.
Edit:
Using Python some setup can be done. Using pip:
Install opencv-python
pip install opencv-python
Install opencv-contrib-python
pip install opencv-contrib-python
Unfortunately, there is some issue with the sift feature since by default it is excluded from newer free versions of OpenCV.
sift = cv2.xfeatures2d.SIFT_create() not working even though have contrib installed
import cv2
Image_1 = cv2.imread("Image_1.png", cv2.IMREAD_COLOR)
Image_2 = cv2.imread("Image_2.jpg", cv2.IMREAD_COLOR)
Image_1 = cv2.cvtColor(Image_1, cv2.COLOR_BGR2GRAY)
Image_2 = cv2.cvtColor(Image_2, cv2.COLOR_BGR2GRAY)
sift = cv2.SIFT_create()
keypoints_1, descriptors_1 = sift.detectAndCompute(Image_1,None)
keypoints_2, descriptors_2 = sift.detectAndCompute(Image_2,None)
len(keypoints_1), len(keypoints_2)
The error I received:
"/Users/michael/Documents/PYTHON/Test Folder/venv/bin/python" "/Users/michael/Documents/PYTHON/Test Folder/Testing.py"
Traceback (most recent call last):
File "/Users/michael/Documents/PYTHON/Test Folder/Testing.py", line 9, in <module>
sift = cv2.SIFT_create()
AttributeError: module 'cv2.cv2' has no attribute 'SIFT_create'
Process finished with exit code 1
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??
Trying to package my custom built MongoDB 2.6.6 (with SSL), I'm using the packager.py script from buildscript/ in the sources I got from www.mongodb.org.
I've changed it in a few places, based on this and on errors I've had because of file locations.
I've come along way, but now the error I'm getting is from within rpmbuild:
error: File not found: /tmp/tmp7vZvNP/rpmbuild/BUILDROOT/mongodb-org-2.6.6-1.%{_arch}/usr/bin/mongod
Put aside the fact I searched and couldn't find where the %{_arch} thing came from, the mongod binary file exists in /tmp/tmp7vZvNP/rpmbuild/BUILDROOT/mongodb-org-2.6.6-1.%\{_arch\}/usr/bin/mongodb-linux-x86_64-2.6.6/bin/
Where is {_bindir} defined for the spec file?
Any other idea what's the next thing I should be pursuing?
So after reading #Etan Reisner's comment, I did the following:
Changed write_rpm_macros_file to look like this:
def write_rpm_macros_file(path, topdir, arch):
f=open(path, 'w')
try:
f.write("%%_topdir %s\n" % topdir)
f.write("%%_arch %s\n" % arch)
f.write("%%_bindir %s" % "/usr/bin/mongodb-linux-x86_64-2.6.6/bin/")
finally:
f.close()
And now I have an RPM built correctly.
Edit:
I changed the binaries tar.gz file and now the %_bindir macro is not needed...
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 :)