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Richard Stallman et le logiciel libre
19 octobre 2011, par
Mis à jour : Mai 2013
Langue : français
Type : Texte
Autres articles (100)
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MediaSPIP 0.1 Beta version
25 avril 2011, parMediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
The zip file provided here only contains the sources of MediaSPIP in its standalone version.
To get a working installation, you must manually install all-software dependencies on the server.
If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...) -
Personnaliser en ajoutant son logo, sa bannière ou son image de fond
5 septembre 2013, parCertains thèmes prennent en compte trois éléments de personnalisation : l’ajout d’un logo ; l’ajout d’une bannière l’ajout d’une image de fond ;
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Multilang : améliorer l’interface pour les blocs multilingues
18 février 2011, parMultilang est un plugin supplémentaire qui n’est pas activé par défaut lors de l’initialisation de MediaSPIP.
Après son activation, une préconfiguration est mise en place automatiquement par MediaSPIP init permettant à la nouvelle fonctionnalité d’être automatiquement opérationnelle. Il n’est donc pas obligatoire de passer par une étape de configuration pour cela.
Sur d’autres sites (12854)
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Merge commit 'ff007e30d8d45ba1ff2b2a4615f1cd5bafb50626'
16 novembre 2017, par Mark Thompson -
Trouble with hardware-assisted encoding/decoding via FFmpeg on Azure GPU vm's (ubuntu 16.04)
17 avril 2018, par user3776020I am trying to use NVIDIA hardware acceleration with FFmpeg/libav, but can’t get it to work correctly on Azure vm’s running Ubuntu 16.04. For a sample case, I am trying to do a simple decoding of an h264 video into a raw YUV file (as detailed here : https:// developer.nvidia.com/ffmpeg).
So far, I’ve tried it on NC-6, NC-12, and NV-6 machines (in different regions). In each of these instances, it would take about 30-45 seconds to process a single video frame. As a comparison, I also tried it on a P2.xlarge vm on AWS (which has very similar specs to the NC-6), which was able to process about 3000 frames in about 5 seconds. Has anyone else run into this issue with Azure machines, or has any idea why this would be the case ?
Here are the commands I used to install the necessary drivers/libraries/etc (I also verified that each machine as the same NVIDIA driver version installed - 375.51) :
CUDA_REPO_PKG=cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
wget -O /tmp/$CUDA_REPO_PKG
http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/$CUDA_REPO_PKGsudo dpkg -i /tmp/$CUDA_REPO_PKG
sudo apt-get update
sudo apt-get install -y cuda-drivers
sudo apt-get install -y cuda
sudo apt-get install -y nvidia-cuda-toolkit
[reboot]
sudo apt-get update
sudo apt-get upgrade -y
sudo apt-get dist-upgrade -y
[reboot]
git clone https://github.com/FFmpeg/FFmpeg.git
[download the latest video codec SDK from NVIDIA at : https://
developer.nvidia.com/designworks/video_codec_sdk/downloads/v7.1][unzipped codec, and copy header files from
/Video_Codec_SDK_7.1.9/Samples/common/inc/ into /usr/include/]cd /FFmpeg
./configure —enable-nonfree —disable-shared —enable-nvenc
—enable-cuda —enable-cuvid —enable-libnpp —extra-cflags=-Ilocal/include —extra-cflags=-I../nv_sdk —extra-ldflags=-L../nv_sdksudo make && sudo make install
For the FFmpeg command that I used to decode a sample movie file, I used the following :
sudo ffmpeg -vsync 0 -c:v h264_cuvid -i sample_vid.mp4 -f rawvideo outputvid.yuv
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Trouble with hardware-assisted encoding/decoding via FFmpeg on Azure GPU vm's (ubuntu 16.04)
3 mai 2017, par user3776020I am trying to use NVIDIA hardware acceleration with FFmpeg/libav, but can’t get it to work correctly on Azure vm’s running Ubuntu 16.04. For a sample case, I am trying to do a simple decoding of an h264 video into a raw YUV file (as detailed here : https:// developer.nvidia.com/ffmpeg).
So far, I’ve tried it on NC-6, NC-12, and NV-6 machines (in different regions). In each of these instances, it would take about 30-45 seconds to process a single video frame. As a comparison, I also tried it on a P2.xlarge vm on AWS (which has very similar specs to the NC-6), which was able to process about 3000 frames in about 5 seconds. Has anyone else run into this issue with Azure machines, or has any idea why this would be the case ?
Here are the commands I used to install the necessary drivers/libraries/etc (I also verified that each machine as the same NVIDIA driver version installed - 375.51) :
CUDA_REPO_PKG=cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
wget -O /tmp/$CUDA_REPO_PKG
http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/$CUDA_REPO_PKGsudo dpkg -i /tmp/$CUDA_REPO_PKG
sudo apt-get update
sudo apt-get install -y cuda-drivers
sudo apt-get install -y cuda
sudo apt-get install -y nvidia-cuda-toolkit
[reboot]
sudo apt-get update
sudo apt-get upgrade -y
sudo apt-get dist-upgrade -y
[reboot]
git clone https://github.com/FFmpeg/FFmpeg.git
[download the latest video codec SDK from NVIDIA at : https://
developer.nvidia.com/designworks/video_codec_sdk/downloads/v7.1][unzipped codec, and copy header files from
/Video_Codec_SDK_7.1.9/Samples/common/inc/ into /usr/include/]cd /FFmpeg
./configure —enable-nonfree —disable-shared —enable-nvenc
—enable-cuda —enable-cuvid —enable-libnpp —extra-cflags=-Ilocal/include —extra-cflags=-I../nv_sdk —extra-ldflags=-L../nv_sdksudo make && sudo make install
For the FFmpeg command that I used to decode a sample movie file, I used the following :
sudo ffmpeg -vsync 0 -c:v h264_cuvid -i sample_vid.mp4 -f rawvideo outputvid.yuv