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Valkaama DVD Label
4 octobre 2011, par
Mis à jour : Février 2013
Langue : English
Type : Image
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Podcasting Legal guide
16 mai 2011, par
Mis à jour : Mai 2011
Langue : English
Type : Texte
Autres articles (46)
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Contribute to a better visual interface
13 avril 2011MediaSPIP is based on a system of themes and templates. Templates define the placement of information on the page, and can be adapted to a wide range of uses. Themes define the overall graphic appearance of the site.
Anyone can submit a new graphic theme or template and make it available to the MediaSPIP community. -
Les notifications de la ferme
1er décembre 2010, parAfin d’assurer une gestion correcte de la ferme, il est nécessaire de notifier plusieurs choses lors d’actions spécifiques à la fois à l’utilisateur mais également à l’ensemble des administrateurs de la ferme.
Les notifications de changement de statut
Lors d’un changement de statut d’une instance, l’ensemble des administrateurs de la ferme doivent être notifiés de cette modification ainsi que l’utilisateur administrateur de l’instance.
À la demande d’un canal
Passage au statut "publie"
Passage au (...) -
Supporting all media types
13 avril 2011, parUnlike most software and media-sharing platforms, MediaSPIP aims to manage as many different media types as possible. The following are just a few examples from an ever-expanding list of supported formats : images : png, gif, jpg, bmp and more audio : MP3, Ogg, Wav and more video : AVI, MP4, OGV, mpg, mov, wmv and more text, code and other data : OpenOffice, Microsoft Office (Word, PowerPoint, Excel), web (html, CSS), LaTeX, Google Earth and (...)
Sur d’autres sites (7047)
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DeckLink 4K Extreme capture videos
15 avril 2015, par tomas keddenI have DeckLink 4K extreme Capture card from Black Magic and i want to capture videos from HDMI input from my SET-Top-Box that it output format yuv4:2:2 on HDMI.
I set’up the bmdtool to capture frame and ffmpeg 2.6 to convert captured frames from yuv422 to mpg file (obtain video files - i want mpg or mp4)
I use this command for :
./bmdcapture -m 8 -V 3 -C 1 -F nut -f pipe:1 | ffmpeg -re -s 1920x1080 -pix_fmt yuv422p -i - -r 30 -f mpeg2videio -b:v 5M -y videoCaptured.mpg
Videos format : 1920x1080-30
But i always obtain a corrupted bmp file but when i use MediaExpress Black Magic SOtware it can display the result correctly whith capture file format as - AVI 10bit YUV.
So can you help me on that.
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FFmpeg and Code Coverage Tools
21 août 2010, par Multimedia Mike — FATE Server, PythonCode coverage tools likely occupy the same niche as profiling tools : Tools that you’re supposed to use somewhere during the software engineering process but probably never quite get around to it, usually because you’re too busy adding features or fixing bugs. But there may come a day when you wish to learn how much of your code is actually being exercised in normal production use. For example, the team charged with continuously testing the FFmpeg project, would be curious to know how much code is being exercised, especially since many of the FATE test specs explicitly claim to be "exercising XYZ subsystem".
The primary GNU code coverage tool is called gcov and is probably already on your GNU-based development system. I set out to determine how much FFmpeg source code is exercised while running the full FATE suite. I ran into some problems when trying to use gcov on a project-wide scale. I spackled around those holes with some very ad-hoc solutions. I’m sure I was just overlooking some more obvious solutions about which you all will be happy to enlighten me.
Results
I’ve learned to cut to the chase earlier in blog posts (results first, methods second). With that, here are the results I produced from this experiment. This Google spreadsheet contains 3 sheets : The first contains code coverage stats for a bunch of FFmpeg C files sorted first by percent coverage (ascending), then by number of lines (descending), thus highlighting which files have the most uncovered code (ffserver.c currently tops that chart). The second sheet has files for which no stats were generated. The third sheet has "problems". These files were rejected by my ad-hoc script.Here’s a link to the data in CSV if you want to play with it yourself.
Using gcov with FFmpeg
To instrument a program for gcov analysis, compile and link the target program with the -fprofile-arcs and -ftest-coverage options. These need to be applied at both the compile and link stages, so in the case of FFmpeg, configure with :./configure \ —extra-cflags="-fprofile-arcs -ftest-coverage" \ —extra-ldflags="-fprofile-arcs -ftest-coverage"
The building process results in a bunch of .gcno files which pertain to code coverage. After running the program as normal, a bunch of .gcda files are generated. To get coverage statistics from these files, run
'gcov sourcefile.c'
. This will print some basic statistics as well as generate a corresponding .gcov file with more detailed information about exactly which lines have been executed, and how many times.Be advised that the source file must either live in the same directory from which gcov is invoked, or else the path to the source must be given to gcov via the
'-o, --object-directory'
option.Resetting Statistics
Statistics in the .gcda are cumulative. Should you wish to reset the statistics, doing this in the build directory should suffice :find . -name "*.gcda" | xargs rm -f
Getting Project-Wide Data
As mentioned, I had to get a little creative here to get a big picture of FFmpeg code coverage. After building FFmpeg with the code coverage options and running FATE,for file in `find . -name "*.c"` \ do \ echo "*****" $file \ gcov -o `dirname $file` `basename $file` \ done > ffmpeg-code-coverage.txt 2>&1
After that, I ran the ffmpeg-code-coverage.txt file through a custom Python script to print out the 3 CSV files that I later dumped into the Google Spreadsheet.
Further Work
I’m sure there are better ways to do this, and I’m sure you all will let me know what they are. But I have to get the ball rolling somehow.There’s also TestCocoon. I’d like to try that program and see if it addresses some of gcov’s shortcomings (assuming they are indeed shortcomings rather than oversights).
Source for script : process-gcov-slop.py
PYTHON :-
# !/usr/bin/python
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import re
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lines = open("ffmpeg-code-coverage.txt").read().splitlines()
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no_coverage = ""
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coverage = "filename, % covered, total lines\n"
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problems = ""
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stats_exp = re.compile(’Lines executed :(\d+\.\d+)% of (\d+)’)
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for i in xrange(len(lines)) :
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line = lines[i]
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if line.startswith("***** ") :
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filename = line[line.find(’./’)+2 :]
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i += 1
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if lines[i].find(":cannot open graph file") != -1 :
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no_coverage += filename + ’\n’
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else :
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while lines[i].find(filename) == -1 and not lines[i].startswith("***** ") :
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i += 1
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try :
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(percent, total_lines) = stats_exp.findall(lines[i+1])[0]
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coverage += filename + ’, ’ + percent + ’, ’ + total_lines + ’\n’
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except IndexError :
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problems += filename + ’\n’
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open("no_coverage.csv", ’w’).write(no_coverage)
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open("coverage.csv", ’w’).write(coverage)
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open("problems.csv", ’w’).write(problems)
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FFmpeg parameters for Fisheye image correction
19 janvier 2023, par Julio CesarI am trying to achieve two things (any of them will work for my solution) :


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- Fisheye video to equirectangular (and view it in 360 view)
- Fisheye video to flat (if I understood correctly, it will be just like the fisheye image (maybe I will lose some FoV ?) but without distortions. Of course in this case I will not use 360 view).






Camera specs : https://documentation.meraki.com/MV/Viewing_Video/Understanding_Image_Quality_on_the_MV32


For test purposes I am using an image as input :


For 1), I am using
ffmpeg -i input_file -vf v360=fisheye:e:ih_fov=180:iv_fov=180:pitch=90 output_file
. This command gives me a rectangular image where the half upper is black, and when testing in https://renderstuff.com/tools/360-panorama-web-viewer/ the user can navigate through this black space (I would like to limit user view, so he could not get to the black part). If I crop and remove the black part, the image in the 360 view becomes distorted (loses the aspect ratio).

For 2), I tried
ffmpeg -i input_file -vf v360=fisheye:flat:ih_fov=180:iv_fov=180 output_file
but it doesn't seem to correct the distortions properly.

FYI this video will be published in AntMedia server to be used as an iframe in web applications. I'll try to use 1) in AntMedia since it supports 360 view (https://antmedia.io/play-live-360-degree-video/).


Since I am new to this, please ask for more information if needed.

Thanks in advance.