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Rennes Emotion Map 2010-11
19 octobre 2011, par
Mis à jour : Juillet 2013
Langue : français
Type : Texte
Autres articles (24)
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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 (...)
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ANNEXE : Les plugins utilisés spécifiquement pour la ferme
5 mars 2010, parLe site central/maître de la ferme a besoin d’utiliser plusieurs plugins supplémentaires vis à vis des canaux pour son bon fonctionnement. le plugin Gestion de la mutualisation ; le plugin inscription3 pour gérer les inscriptions et les demandes de création d’instance de mutualisation dès l’inscription des utilisateurs ; le plugin verifier qui fournit une API de vérification des champs (utilisé par inscription3) ; le plugin champs extras v2 nécessité par inscription3 (...)
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Encoding and processing into web-friendly formats
13 avril 2011, parMediaSPIP automatically converts uploaded files to internet-compatible formats.
Video files are encoded in MP4, Ogv and WebM (supported by HTML5) and MP4 (supported by Flash).
Audio files are encoded in MP3 and Ogg (supported by HTML5) and MP3 (supported by Flash).
Where possible, text is analyzed in order to retrieve the data needed for search engine detection, and then exported as a series of image files.
All uploaded files are stored online in their original format, so you can (...)
Sur d’autres sites (3781)
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Is it advisable to use FFMpeg on my local server for video conversion ?
7 juin 2019, par Yash DesaiWe are starting a video sharing website where users will be able to upload videos in their native formats. However, since video streaming on the web generally is in the FLV format, we need to convert the videos to FLV.
Also, the site will be hosted on Amazon EC2 and storage using S3.
Can i run FFMpeg on amazon EC2 ? Is this the best way to go ? Are there other alternatives to video encoding rather than doing conversion on our own server ? I also came across www.transloadit.com which seems to do the same but they are charging a bomb. Are there cheaper and more intelligent alternatives ?
We are planning to make this website as one of top 10 biggest niche video streaming websites on the internet.
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Reason for write EPIPE error in my implentation ?
18 mai 2019, par Chrisl446So I currently have a small node.js express application for uploading images using sharp & thumbnails created from .mp4 videos using simple-thumbnail package/ffmpeg.
The app works perfectly when uploading an image, the file is uploaded sharp processes it, then passes it along and it ends up in my amazon s3 bucket as expected. No errors what so ever.
However, when I upload an mp4 video that I use to create and upload a thumbnail from by using simple-thumbnails genThumbnail() function, which uses ffmpeg child process, the thumbnail uploads successully to my s3 bucket, HOWEVER my app returns an EPIPE write error and NOT the url of the uploaded files url on S3.
What is causing this and how can I fix it, considering it’s pretty much working aside from the EPIPE error that is being returned ? Thanks ahead !
The packages of concern used are as follows :
multer-s3 <- this one with the transform option, not the standard multer-s3 package
const express = require('express');
const app = express();
const aws = require('aws-sdk');
const multer = require('multer');
const multerS3 = require('multer-s3'); //github:gmenih341/multer-s3 version of multer-s3 with transform option
const sharp = require('sharp');
const genThumbnail = require('simple-thumbnail');
app.use((req, res, next) => {
res.header('Access-Control-Allow-Origin', '*');
res.header('Access-Control-Allow-Headers', 'Orgin, X-Requested-With, Content-Type, Accept, Authorization');
if (req.method === 'OPTIONS') {
res.header('Access-Control-Allow-Methods', 'POST');
return res.status(200).json({});
}
next();
});
let uniqueFileName;
let s3BucketName = 'bucketname';
let s3 = new aws.S3({
accessKeyId: ACCESS_KEY,
secretAccessKey: SECRET_KEY,
Bucket: s3BucketName
});
let upload = multer({
storage: multerS3({
s3: s3,
bucket: s3BucketName,
acl: 'public-read',
cacheControl: 'max-age=31536000',
contentType: multerS3.AUTO_CONTENT_TYPE,
shouldTransform: true,
transforms: [{
id: 'thumbnail',
key: function (req, file, cb) {
uniqueFileName = Date.now().toString();
cb(null, uniqueFileName + '.jpg')
},
transform: function (req, file, cb) {
if (file.mimetype == 'video/mp4') {
//When using simple-thumbnails' getThumbnail() on an mp4 video it uploads succesfully to S3 but node returns EPIPE write error
cb(null, genThumbnail(null, null, '250x?'))
} else {
//When using sharp to resize an image this works perfectly and retuns the JSON below with the files S3 URL
cb(null, sharp().jpeg())
}
}
}]
})
});
app.post('/upload', upload.array('theFile'), (req, res) => {
res.json({
fileS3Url: 'https://s3.amazonaws.com/'+ s3BucketName +'/' + uniqueFileName
});
});
app.use((req, res, next) => {
const error = new Error('Not found');
error.status = 404;
next(error);
});
app.use((error, req, res, next) => {
res.status(error.status || 500);
res.json({
error: {
message: error.message
}
});
});
module.exports = app; -
swscale/aarch64 : use multiply accumulate and increase vector factor to 4
17 novembre 2019, par Sebastian Popswscale/aarch64 : use multiply accumulate and increase vector factor to 4
This patch implements ff_hscale_8_to_15_neon with NEON fused multiply accumulate
and bumps the vectorization factor from 2 to 4.
The speedup is of 25% on Graviton1 A1 instances based on A-72 cpus :$ ffmpeg -nostats -f lavfi -i testsrc2=4k:d=2 -vf bench=start,scale=1024x1024,bench=stop -f null -
before : t:0.040303 avg:0.040287 max:0.040371 min:0.039214
after : t:0.032168 avg:0.032215 max:0.033081 min:0.032146The speedup is of 39% on Graviton2 m6g instances based on Neoverse-N1 cpus :
$ ffmpeg -nostats -f lavfi -i testsrc2=4k:d=2 -vf bench=start,scale=1024x1024,bench=stop -f null -
before : t:0.019446 avg:0.019423 max:0.019493 min:0.019181
after : t:0.014015 avg:0.014096 max:0.015018 min:0.013971Tested with `make check` on aarch64-linux.
Signed-off-by : Sebastian Pop <spop@amazon.com>
Reviewed-by : Jean-Baptiste Kempf <jb@videolan.org>
Signed-off-by : Michael Niedermayer <michael@niedermayer.cc>