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La conservation du net art au musée. Les stratégies à l’œuvre
26 mai 2011
Mis à jour : Juillet 2013
Langue : français
Type : Texte
Autres articles (87)
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Qu’est ce qu’un masque de formulaire
13 juin 2013, parUn masque de formulaire consiste en la personnalisation du formulaire de mise en ligne des médias, rubriques, actualités, éditoriaux et liens vers des sites.
Chaque formulaire de publication d’objet peut donc être personnalisé.
Pour accéder à la personnalisation des champs de formulaires, il est nécessaire d’aller dans l’administration de votre MediaSPIP puis de sélectionner "Configuration des masques de formulaires".
Sélectionnez ensuite le formulaire à modifier en cliquant sur sont type d’objet. (...) -
MediaSPIP v0.2
21 juin 2013, parMediaSPIP 0.2 is the first MediaSPIP stable release.
Its official release date is June 21, 2013 and is announced here.
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 (...) -
MediaSPIP Player : les contrôles
26 mai 2010, parLes contrôles à la souris du lecteur
En plus des actions au click sur les boutons visibles de l’interface du lecteur, il est également possible d’effectuer d’autres actions grâce à la souris : Click : en cliquant sur la vidéo ou sur le logo du son, celui ci se mettra en lecture ou en pause en fonction de son état actuel ; Molette (roulement) : en plaçant la souris sur l’espace utilisé par le média (hover), la molette de la souris n’exerce plus l’effet habituel de scroll de la page, mais diminue ou (...)
Sur d’autres sites (5852)
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avcodec/v210enc : add new function for avx2 avx512 avx512icl
25 octobre 2022, par James Darnleyavcodec/v210enc : add new function for avx2 avx512 avx512icl
Negligible speed difference for avx2 on Zen 2 (Ryzen 5700X) and
Broadwell (Xeon E5-2620 v4) :
1690±4.3 decicycles vs. 1693±78.4
1439±31.1 decicycles vs 1429±16.7Moderate speedup with avx512 on Skylake-X (Xeon D-2123IT) :
1.22x faster (793±0.8 vs. 649±5.5 decicycles) compared with avx2Better speedup with avx512icl on Ice Lake (Xeon Silver 4316) :
1.77x faster (784±1.8 vs. 442±11.6 decicycles) compared with avx2Co-authors :
Henrik Gramner <henrik@gramner.com>
Kieran Kunhya <kierank@obe.tv> -
OpenCV 4.5.2 takes a long time (>100ms) to retrieve a single frame from a webcam, C++ on Windows 10
9 juin 2021, par Mustard TigerI've been having a tough time getting my webcam working quickly with opencv. Frames take a very long time to read, (a recorded average of 124ms across 500 frames) I've tried on three different computers (running Windows 10) with a logitech C922 webcam. The most recent machine I tested on has a Ryzen 9 3950X, with 32gbs of ram ; no lack of power.


Here is the code :


cv::VideoCapture cap = cv::VideoCapture(m_cameraNum);

// Check if camera opened successfully
if (!cap.isOpened())
{
 m_logger->critical("Error opening video stream or file\n\r");
 return -1;
}

bool result = true;
result &= cap.set(cv::CAP_PROP_FRAME_WIDTH, 1280);
result &= cap.set(cv::CAP_PROP_FRAME_HEIGHT, 720);

bool ready = false;
std::vector<string> timeLog;
timeLog.reserve(50000);
int i = 0;

while (i < 500)
{
 auto start = std::chrono::system_clock::now();
 
 cv::Mat img;
 ready = cap.read(img);

 // If the frame is empty, break immediately
 if (!ready)
 {
 timeLog.push_back("continue");
 continue;
 }

 i++;
 auto end = std::chrono::system_clock::now();
 timeLog.push_back(std::to_string(std::chrono::duration_cast(end - start).count()));
}

for (auto& entry : timeLog)
 m_logger->info(entry);

cap.release();
return 0;
</string>

Notice that I write the elapsed time to a log file at the end of execution. The average time is 124ms for debug and release, and not one instance of "continue" after half a dozen runs.


It doesn't matter if I use USB 2 or USB 3 ports (the camera is USB2) or if I run a debug build or a release build, the log file will show anywhere from 110ms to 130ms of time for each frame. The camera works fine in other app, OBS can get a smooth 1080@30fps or 720@60fps.


Stepping through the debugger and doing a lot of Googling, I've learned the following about my system :


- 

- The backend chosen by default is DSHOW. GStreamer and FFMPEG are also available.
- DSHOW uses FFMPEG somehow (it needs the FFMPEG dll) but I cannot use FFMPEG directly through opencv. Attempting to use cv::VideoCapture(m_cameraNum, cv::CAP_FFMPEG) always fails. It seems like Opencv's interface to FFMPEG is only capable of opening video files.
- Microsoft really screwed up camera devices in Windows a few years back, not sure if this is related to my problem.








Here's a short list of the fixes I have tried, most taken from older SO posts :


- 

- result &= cap.set(cv::CAP_PROP_FRAME_COUNT, 30) ; // Returns false, does nothing
- result &= cap.set(cv::CAP_PROP_CONVERT_RGB, 0) ; // Returns true, does nothing
- result &= cap.set(cv::CAP_PROP_MODE, cv::VideoWriter::fourcc('M', 'J', 'P', 'G')) ; // Returns false, does nothing
- Set registry key from http://alax.info/blog/1693 that should disable the new Windows camera server.
- Updated from 4.5.0 to 4.5.2, no change.
- Asked device manager to find a newer driver, no newer driver found.














I'm out of ideas. Any help ?


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Hardware acceleration FFMPEG not speeding up rendering at the moment
13 août 2021, par AlphaDjangoI currently have ffmpeg running on a computer (ubuntu server 20.04) with a nvidia MSI GTX 1660 6GB GAMING X TWIN FORZ 7 GRAPHICS CARD and a Ryzen 5 3600 cpu. I have installed the nvidia drivers for linux for it.


Currently when enabling and disabling hardware acceleration the rendering takes the same amount of time which is around 1 minute to render per 1 minute of footage.


When using a similar setup in davinci resolve it takes 1/4 of the time to apply similar background effects and concating the clips which makes me question if I am using hardware acceleration of if my ffmpeg command is not optimised for it ?


This is the code which takes in around 50 mp4 clips and joins them together, scales them in size and applies a background blur on the sides of clips


ffmpeg -hwaccel cuda -f concat -safe 0 -i /home/anon/project/MEDIAFILES/work_ffmpeg_space/concat_file_user_root_projectId_1.txt -s 1920x1080 -filter_complex '[0:v]scale=ih*16/9:-1:flags=bicubic,boxblur=luma_radius=min(h\,w)/20:luma_power=2:chroma_radius=min(cw\,ch)/20:chroma_power=1[bg];[bg][0:v]overlay=(W-w)/2:(H-h)/2,crop=h=iw*9/16' -af aselect=concatdec_select,aresample=async=1 /home/anon/project/MEDIAFILES/created_videos/finalvideo_user_root_projectId_1.mp4


Any tips or ways to optimise the code to use hardware acceleration will be greatly appreciated !


This is my ffmpeg configuration


ffmpeg version N-103221-gc3ef9e0277 Copyright (c) 2000-2021 the FFmpeg developers
 built with gcc 9 (Ubuntu 9.3.0-17ubuntu1~20.04)
 configuration: --pkg-config-flags=--static --enable-nonfree --enable-gpl --enable-version3 --enable-libmp3lame --enable-libvpx --enable-libopus --enable-opencl --enable-libxcb --enable-opengl --enable-nvenc --enable-vaapi --enable-vdpau --enable-ffplay --enable-ffprobe --enable-libxvid --enable-libx264 --enable-libx265 --enable-openal --enable-openssl --enable-cuda-nvcc --enable-cuvid --extra-cflags=-I/usr/lcal/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64 --extra-libs=-lpthread
 libavutil 57. 3.100 / 57. 3.100
 libavcodec 59. 4.101 / 59. 4.101
 libavformat 59. 4.101 / 59. 4.101
 libavdevice 59. 0.100 / 59. 0.100
 libavfilter 8. 1.103 / 8. 1.103
 libswscale 6. 0.100 / 6. 0.100
 libswresample 4. 0.100 / 4. 0.100
 libpostproc 56. 0.100 / 56. 0.100


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