I am trying to setup gotify server on my Raspberry Pi 3 B+ .I am following this tutorial.I downloaded,unzipped and made executable the gotify-linux-arm-7.zip file /
When I do ls
Result is
But after sudo ./gotify-linux-arm-7
I get
Please suggest how to overcome this error.
The issue was minor but needs to be remembered. My RPi 3B + supports arm64 and I had downloaded arm 7 version looking at youtube and other online sources. Installing the arm64 version solved the issue .
Related
Followed instructions given in https://doc.omnetpp.org/omnetpp/InstallGuide.pdf
OMNeT++ Version - omnetpp-5.6.2
Device - MacBook Air M1 (MacOS Big Sur Version 11.4)
Encountered the following problems.
$. setenv -> didn't work (worked after replacing "." with "source")
$./configure -> gives the following error.
configure: error: Qtenv cannot find qmake -- maybe it is not in the PATH or has some exotic name (tested names were: qmake qmake-qt5 qmake5) - disabling Qtenv. You can try setting the QT_PATH variable in configure.user to a valid location
$ make -> gives the following error.
Makefile:54: Makefile.inc: No such file or directory
make: *** No rule to make target `Makefile.inc'. Stop.
Is it possible to get OMNeT++ working on M1 Macs? Any help would be greatly appreciated.
Thanks in advance.
There is no native support for M1 processors, especially because omnet++ 5.6 was released way before the M1 release, but you can run omnet with Rosetta2 in x86_64 mode. You would still get pretty decent performance. With x86_64 emulation I measured similar performance like on my last year high end AMD laptop. Native mode would give you a 25% boost compared to that.
To turn on the emulation for a shell window, start a new shell with
$ arch -x86_64 /bin/zsh --login
and then continue in that shell with
$ source setenv
$ ./configure
$ make
run everything from that shell window (as usual).
NOTE: OMNeT++ 5.6 relies on the system-wide installed JRE to run the IDE. That may NOT be present on your system if you are running on ARM. OMNeT++ 6 and 5.7 comes with a built-in private JRE, so the IDE should work with those versions also in intel emulation mode.
ps: OMNeT++ 6 may get native M1 support (this depends on the availability of some dependencies (JavaVM, Qt etc.). I'm also considering an ARM based docker image, that would allow running at native performance (as long as you have an XServer installed).
I've been using Veins (v5.1) along with SUMO (v1.8) and OMNeT++ (v5.6.2) in Linux Ubuntu 20.04 and 18.04. When I try to run the example provided by veins I keep getting the same error both in Ubuntu 20.04 and 18.04.
According to the information in OMNeT, the error code is 133 or 137 and there isn't much information about the error in the above lines.
Sumo seems to be running correctly, listening on port 9999, and sumo-gui is actually launching. However, a few seconds later it terminates with the following error log
"Error: Storage::readChar(): invalid position". There's also an error code in the terminal.
In the past I faced this problem in Ubuntu 14.04 due to incompatibility issues between the versions I was using. This time I'm using the recommended versions from veins webpage.
Has anyone faced this problem before? Could this be an incompatibility issue with the operating system and if so, does anyone know what the compatible versions are for Ubuntu 18.04 or 20.04? I haven't used Linux before so I'm not sure if there's something else I'm missing.
I've included a screenshot with the errors I'm getting in case that helps.
Thanks!
I faced the same issue when using ubuntu 20.04, Omnet++ 5.6.2 and SUMO 1.9.0, and I managed to solve it by downgrading sumo to an older version.
First remove the current sumo:
$sudo apt-get remove sumo
Then install the old version:
$sudo apt-get install sumo=1.4.0+dfsg1-1
I don't know if that is actually an answer to the problem or why this works. I've tried it both in my laptop (Ubuntu 18.04) and in two different virtual machines (Ubuntu 18.04 and Ubuntu 20.04) and this seems to fix the problem.
Veins should be saved in a folder called src and then imported to OMNeT++ to avoid the error. The path to Veins should be similar to the following.
/home/<me>/<folder>/src/veins-5.1
I have a problem with building TF r2.3 when I would like to build a version with CUDA support. When I configure the build for CPU without CUDA everything build fine. With the CUDA support turned on I got Bad address (Exit 126) error for bash commands like this. I use windows 10 with MSVC 2019 v16.6.5. I also use python 3.6.8 and Bazel 3.3.1. I have encountered with this problem with both CUDA v10.2, cudnn-10.2-windows10-x64-v7.6.5.32 and CUDA 10.1 and cuDNN 7.4. I have tried to build with the following command after I have configured the project.
bazel build --config=opt --define=no_tensorflow_py_deps=true //tensorflow:libtensorflow_cc.so
I put the content of the command.log file to this pastebin link.
I have opened a github issue for this error on the tensorflow repo but so far they haven't provided any solution for this issue. I hope here someone point me in the right direction.
I had the same issue, try to build TF 2.4 with Cuda 11 and cuDNN 8. I was able to build with this configuration on Windows finally.
I have been working on some video playing/streaming pipelines for Computer Vision work on Nvidia Jetson TX2. It had Ubuntu 16.04 with latest Jetpack.
I have already installed opencv 3.3 and to test some of the pipelines, with .MP$ video files, I need h264parse plugin which is a part of gst-bad-plugins. However, when I try to install it using apt-get, it shows that following packages will be installed:
freepats gstreamer1.0-plugins-bad-faad gstreamer1.0-plugins-bad-videoparsers
libbs2b0 libde265-0 libflite1 libfluidsynth1 libgstreamer-plugins-bad1.0-0
libmimic0 libmjpegutils-2.1-0 libmms0 libmpeg2encpp-2.1-0 libmplex2-2.1-0
libofa0 libopenal-data libopenal1 libopencv-calib3d2.4v5
libopencv-contrib2.4v5 libopencv-core2.4v5 libopencv-features2d2.4v5
libopencv-flann2.4v5 libopencv-highgui2.4v5 libopencv-imgproc2.4v5
libopencv-legacy2.4v5 libopencv-ml2.4v5 libopencv-objdetect2.4v5
libopencv-video2.4v5 libsoundtouch1 libspandsp2 libsrtp0 libvo-aacenc0
libvo-amrwbenc0 libwildmidi-config libwildmidi1 libzbar0
Here it tries to install an older version of opencv and this really messes up with my current opencv (v3.3) install.
Does anyone have any idea on how should I overcome this problem. I would not want the option to just ignore all the dependencies. But somehow, if it detects the installed opencv version, that would be awesome.
Any help is appreciated.
Thanks!
I am working on Jetson Tx1 , and have problem installing opencv 3.3 in virtual environment onto it due to space issues. I tried to compile the build file from external sd card and make from there. Then Sym-link (cv2.so) file to appropriate path. Can you tell me how you were able to install opencv3.3 ??
I'm trying to install openCV on university's iMac,
but the problem is our university's network is so strict.
and I couldn't install openCV using MacPorts.
I tried google to look for a way to install but it all failed
i guess because it is kind of old ways and because my network is so strict.
So if anybody knows a way that I can download a ready framework with how to use it inside
Xcode. or at least a framework with how to install it to work with Xcode.
or a way to download from the source and compile it then install it in Xcode
please.
Because I tried the cmake way and I still have no luck to get it work.
thanks in advance.
sources I used:
http://salemsayed.me/?p=240
http://opencv.willowgarage.com/wiki/InstallGuide
http://opencv.willowgarage.com/wiki/Mac_OS_X_OpenCV_Port
http://www.ient.rwth-aachen.de/cms/software/opencv/
I'm using Lion + Xcode 4.x branch, with OpenCV svn trunk. Everything works fine. You have to install cmake first, then get the code from the svn following the instructions at http://code.opencv.org . The compilation process worked fine for me for all the core modules + the Qt module + the GPU module + TBB acceleration.
The instructions are the same as the Linux platform.
After setting up cmake configuration in a terminal (using ccmake for a more interactive tool),
I set the architecture to x86_64 (on my MBP Core 2 Duo), the target directory to /usr/local/(the default), and I have Intel TBB installed in /usr/local/.
Cmake generates the makefiles for you, so you just have to type make -j2 to compile, then sudo make install. If you're working on a workstation, then you have more CPU power, and you can replace the value 2 by more, e.g. 8.