How can I use tesseract to process image located on Hdfs? can anyone help me wit the mapreduce program for this? The problem is that, the Image file will be located on Hdfs but the tesseract is configured on local machine running as hadoop slave. how will tesseract locate the image file located on hdfs????
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This seems to be a very simple question, but I couldn't find a way to do it. The jyputer notebook has the option to download file one by one. But my training process generates too many files, and I want to download them all at once. Is there any way to do it?
Assuming it is JupyterLab what you are using:
Open a new Launcher (+ icon) and start a new terminal session.
Use zip -r FILE_NAME.zip PATH/TO/OUTPUT/FOLDER/ to compress the required folder.
Download the zip file as you were doing with the other ones.
I have folders on server 1, and i just want to compress files to another server.
So i tried with:
7z a "\server1\plugins\Arhiva_plugins_2018_01.7z
"\server2\jenkinstest*"
7zip compressed everything on \server1\pluigins\
Is it possible to compress folders on the third side with 7zip commands?
p.s. all command using on windows server, via cmd.
figure out.
switch the places
7z a \server2\jenkinstest\Arhiva_plugins_2018_01.7z
\server1\plugins\
I was trying to place a file on to the esxi host while booting up the system using kickstart process.
I created a.txt file in the iso image, and build the image. When i booted up the system all the files which were present on the iso were visible on the datastore/localdisk except the text file.
Where should I mention so that the file the can also be moved into the host? is there any other way of achiving this thing.
thanks in advance
I created a Docker image with Ubuntu 14.04 and compiled FFMPEG to run the streaming of a video asset to a DASH endpoint. On the same image I can run the media analysis script which basically use FFMPEG and other tools to analyse a video asset. Now I want to put a Django app so that assets can be both loaded in the streaming pipeline and run through the media analysis. What would you suggest is the best approach? Have 2 Docker images – one with compiled FFMPEG and the streaming pipeline and another one with django, and then share the code between the two? Or just keep 1 docker image and run both the FFMPEG streaming pipeline and media analysis and Django from there?
I am open to suggestions…
Possible duplicate of https://serverfault.com/questions/706736/sharing-code-base-between-docker-containers
I'm in the process of moving some on-premise app to Azure and struggling with once aspect - GhostScript. We use GhostScript to convert PDF's to multi page TIFF's. At present this is deployed in an Azure VM, but it seems like a WebApp and WebJob would be a better fit - from a management point of view. In all of my testing I've been unable to get a job to run the GhostScript exe.
Has anyone been able to run GhostScript or any third party exe in a WebJob?
I have tried packaging the GhostScript exe, lib and dll into a ZIP file and then unzip to Path.GetTempPath() and then using a new System.Diagnostics.Process to run the exe with the required parameters - this didn't work - the process refused to start with an exit code of -1073741819.
Any help or suggestions would be appreciated.
We got it to work here:
Converting PDFs to Multipage Tiff files Using Azure WebJobs. The key was putting the Ghostscript assemblies in the root of the project and setting "Copy always". This is what allows them to be pushed to the Azure server, and to end up in the correct place, when you publish the project.
Also, we needed to download the file to be processed by Ghostscript to the local Azure WebJob temp directory. This is discovered by using the following code:
Environment.GetEnvironmentVariable("WEBJOBS_PATH");