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Médias (91)
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Les Miserables
9 décembre 2019, par
Mis à jour : Décembre 2019
Langue : français
Type : Textuel
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VideoHandle
8 novembre 2019, par
Mis à jour : Novembre 2019
Langue : français
Type : Video
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Somos millones 1
21 juillet 2014, par
Mis à jour : Juin 2015
Langue : français
Type : Video
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Un test - mauritanie
3 avril 2014, par
Mis à jour : Avril 2014
Langue : français
Type : Textuel
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Pourquoi Obama lit il mes mails ?
4 février 2014, par
Mis à jour : Février 2014
Langue : français
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IMG 0222
6 octobre 2013, par
Mis à jour : Octobre 2013
Langue : français
Type : Image
Autres articles (100)
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Encodage et transformation en formats lisibles sur Internet
10 avril 2011MediaSPIP transforme et ré-encode les documents mis en ligne afin de les rendre lisibles sur Internet et automatiquement utilisables sans intervention du créateur de contenu.
Les vidéos sont automatiquement encodées dans les formats supportés par HTML5 : MP4, Ogv et WebM. La version "MP4" est également utilisée pour le lecteur flash de secours nécessaire aux anciens navigateurs.
Les documents audios sont également ré-encodés dans les deux formats utilisables par HTML5 :MP3 et Ogg. La version "MP3" (...) -
Monitoring de fermes de MediaSPIP (et de SPIP tant qu’à faire)
31 mai 2013, parLorsque l’on gère plusieurs (voir plusieurs dizaines) de MediaSPIP sur la même installation, il peut être très pratique d’obtenir d’un coup d’oeil certaines informations.
Cet article a pour but de documenter les scripts de monitoring Munin développés avec l’aide d’Infini.
Ces scripts sont installés automatiquement par le script d’installation automatique si une installation de munin est détectée.
Description des scripts
Trois scripts Munin ont été développés :
1. mediaspip_medias
Un script de (...) -
Problèmes fréquents
10 mars 2010, parPHP et safe_mode activé
Une des principales sources de problèmes relève de la configuration de PHP et notamment de l’activation du safe_mode
La solution consiterait à soit désactiver le safe_mode soit placer le script dans un répertoire accessible par apache pour le site
Sur d’autres sites (16070)
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How to extract motion vectors from h264 without a full decode on the CPU
25 septembre 2020, par Adrian MayI'm trying to use my nose as a pointing device. The plan is to encode the video stream from a webcam pointed at my face as h264 or the like, get the motion vectors, cook the numbers a bit and chuck them into /dev/uinput to make the mouse pointer move about. The uinput bit was easy.


This has to work with zero discernable latency. This, for instance :


#!/bin/bash
[ -p pipe.mkv ] || mkfifo pipe.mkv
ffmpeg -y -rtbufsize 1M -s 640x360 -vcodec mjpeg -i /dev/video0 -c h264_nvenc pipe.mkv &
ffplay -flags2 +export_mvs -vf codecview=mv=pf+bf+bb pipe.mkv


shows that the vectors are there but with a latency of several seconds which is unusable in a mouse. I know that the first ffmpeg step is working very fast by using the GPU, so either the pipe or the h264 decode in the second step is introducing the latency.


I tried MV Tractus (same as mpegflow I think) in a similar pipe arrangement and it was also very slow. They do a full h264 decode on the CPU and I think that's the problem cos I can see them imposing a lot of load on one CPU. If the pipe had caused the delay by buffering badly then the CPU wouldn't have been loaded. I guess ffplay also did the decoding on the CPU and I couldn't persuade it not to, but it only wants to draw arrows which are no use to me.


I think there are several approaches, and I'd like advice on which would be best, or if there's something even better I don't know about. I could :


- 

- Decode in hardware and get the motion vectors. So far this has failed. I tried combining ffmpeg's
extract_mvs.candhw_decode.csamples but no motion vectors turn up. vdpau is the only decoder I got working on my linux box. I have a nvidia gpu. - Do a minimal parse of the h264 to fish out the motion vectors only, ignoring all the other data. I think this would mean putting some kind of "motion only" option in libav's parser, but I'm not at all familiar with that code.
- Find some other h264 parsing library that has said option and also unpacks the container.
- Forget about hardware accelerated encoding and use a stripped down encoder to make only the motion vectors on either CPU or GPU. I suspect this would be slow cos I think calculating the motion vectors is the hardest part of the algorithm.










I'm tending towards the second option but I need some help figuring out where in the libav code to do it.


- Decode in hardware and get the motion vectors. So far this has failed. I tried combining ffmpeg's
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Extracting frames from a video does not work correctly [closed]
13 avril 2024, par Al TilmidhUsing the libraries (libav) and (ffmpeg), I try to extract frames as
.jpgfiles from avideo.mp4, the problem is that my program crashes when I use theCV_8UC3parameter, but by changing this parameter toCV_8UC1, the extracted images end up without color (grayscale), I don't really know what I missed, here is a minimal code to reproduce the two situations :

#include <opencv2></opencv2>opencv.hpp>

extern "C"
{
#include <libavformat></libavformat>avformat.h>
#include <libavcodec></libavcodec>avcodec.h>
}

int main()
{
 AVFormatContext *formatContext = nullptr;

 if (avformat_open_input(&formatContext, "video.mp4", nullptr, nullptr) != 0)
 {
 return -1;
 }

 if (avformat_find_stream_info(formatContext, nullptr) < 0)
 {
 return -1;
 }

 AVPacket packet;
 const AVCodec *codec = nullptr;
 AVCodecContext *codecContext = nullptr;

 int videoStreamIndex = av_find_best_stream(formatContext, AVMEDIA_TYPE_VIDEO, -1, -1, &codec, 0);
 if (videoStreamIndex < 0)
 {
 return -1;
 }

 codecContext = avcodec_alloc_context3(codec);
 avcodec_parameters_to_context(codecContext, formatContext->streams[videoStreamIndex]->codecpar);

 if (avcodec_open2(codecContext, codec, nullptr) < 0)
 {
 return -1;
 }

 AVFrame *frame = av_frame_alloc();

 while (av_read_frame(formatContext, &packet) >= 0)
 {
 if (packet.stream_index == videoStreamIndex)
 {
 int response = avcodec_send_packet(codecContext, &packet);
 
 if (response < 0)
 {
 break;
 }

 while (response >= 0)
 {
 response = avcodec_receive_frame(codecContext, frame);
 if (response == AVERROR(EAGAIN))
 {
 // NO FRAMES
 break;
 }

 else if (response == AVERROR_EOF)
 {
 // END OF FILE
 break;
 }

 else if (response < 0)
 {
 break;
 }

 //cv::Mat frameMat(frame->height, frame->width, CV_8UC3, frame->data[0]); // CV_8UC3 → THE PROGRAM CRASHES
 cv::Mat frameMat(frame->height, frame->width, CV_8UC1, frame->data[0]); // CV_8UC1 → WORK BUT IMAGES ARE IN GRAYSCALE
 cv::imwrite("frame_" + std::to_string(frame->pts) + ".jpg", frameMat);
 }
 }

 av_packet_unref(&packet);
 }

 av_frame_free(&frame);
 avcodec_free_context(&codecContext);
 avformat_close_input(&formatContext);

 return 0;
}


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Fast movie creation using MATLAB and ffmpeg
24 février 2018, par hyiltizI have some time series data that I would like to create into movies. The data could be 2D (about 500x10000) or 3D (500x500x10000). For 2D data, the movie frames are simply line plot using
plot, and for 3D data, we can usesurf,imagesc,contouretc. Then we create a video file using these frames in MATLAB, then compress the video file usingffmpeg.To do it fast, one would try not to render all the images to display, nor save the data to disk then read it back again during the process. Usually, one would use
getframeorVideoWriterto create movie in MATLAB, but they seem to easily get tricky if one tries not to display the figures to screen. Some even suggest plotting in hidden figures, then saving them as images to disk as.pngfiles, then compress them usingffmpeg(e.g. withx265encoder into.mp4). However, saving the output ofimagescin my iMac took 3.5s the first time, then 0.5s after. I also find it not fast enough to save so many files to disk only to askffmpegto read them again. One couldhardcopythe data as this suggests, but I am not sure whether it works regardless of the plotting method (e.g.plot,surfetc.), and how one would transfer data over toffmpegwith minimal disk access.This is similiar to this, but
immovieis too slow. This post 3 is similar, but advocates writing images to disk then reading them (slow IO).
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