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Websites made with MediaSPIP
2 mai 2011, parThis page lists some websites based on MediaSPIP.
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Possibilité de déploiement en ferme
12 avril 2011, parMediaSPIP peut être installé comme une ferme, avec un seul "noyau" hébergé sur un serveur dédié et utilisé par une multitude de sites différents.
Cela permet, par exemple : de pouvoir partager les frais de mise en œuvre entre plusieurs projets / individus ; de pouvoir déployer rapidement une multitude de sites uniques ; d’éviter d’avoir à mettre l’ensemble des créations dans un fourre-tout numérique comme c’est le cas pour les grandes plate-formes tout public disséminées sur le (...) -
Ajouter des informations spécifiques aux utilisateurs et autres modifications de comportement liées aux auteurs
12 avril 2011, parLa manière la plus simple d’ajouter des informations aux auteurs est d’installer le plugin Inscription3. Il permet également de modifier certains comportements liés aux utilisateurs (référez-vous à sa documentation pour plus d’informations).
Il est également possible d’ajouter des champs aux auteurs en installant les plugins champs extras 2 et Interface pour champs extras.
Sur d’autres sites (13026)
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AWS Lambda execution time for FFMPEG transcoding
4 janvier 2023, par FlamingMoeI'm using AWS Lambda for converting files from WEBM to MP4


I'm using ffmpeg version 4.3.1-static https://johnvansickle.com/ffmpeg/ (I have done the following tests also with the ffmpeg in serverless AWS ffmpeg layer (that includes de 4.1.3), but results are even worse (about 25% slower)


I'm using Node 10x as container.


WEBM size Time to convert. Memory Lambda. Memory used (as shown in log)

80Mb ~44s 3008 410
40Mb ~44s 3008 375

80Mb ~70s 1024 321
40Mb ~70s 1024 279



All videos are 80s length. So as far as I can see, it does not matter the size of the WEBM, if the length of the video is the same, it takes the same to convert. So ffmpeg takes more time if the video length is higher, not if the file size is higher ... curious ;-)


But in the other hand, I'm confused with Lambda memory. I know memory and CPU comes together in Lambda ... the more memory you choose, the more CPU is assigned.


But...


- 

- Why ffmpeg just take about 300/400Mb if it has more to run ?
- How can I tell ffmpeg to use more memory ?
- Is there any option to accelerate the process in Lambda ?








Btw, In all tests, all ffmpeg are the same, and


cpu-used paramenter)


- 

- I added to ffmpeg parameters cpu-used=100, and it does not matter at all if I put cpu-used=5 ... times are the same, so I guess that parameter is useless (i don't know why)




threads parameter)


- 

- Also I did some tests with "threads" parameters, but it's useless also.




I know it's not a good comparison, but same files takes about 5 seconds to be converted in a simple dedicated server (8 vCores and 8GB RAM in OVH Centos VPS).


Btw, Amazon Elastic Transcoder is not an option :
a) it's extremely more expensive
b) it has just his profiles to convert, and my ffmpeg commands are very complex (watermarks, effects, etc ...)


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AWS Lambda in Node JS with FFMPEG Lambda Layer
29 mars 2023, par mwcwge23I'm trying to make a Lambda that takes a video and puts a watermark image on it.
I'm using Lambda with NodeJS and FFMPEG Lambda Layer I took from here :
https://serverlessrepo.aws.amazon.com/applications/us-east-1/145266761615/ffmpeg-lambda-layer


I got these two errors and I don't have a clue what do I did wrong :
errors


Please help me :)


(by the way, if you have an easier solution to put a watermark image on video that'll also be great)


That's my code (trying to put a watermark image on a video file) :


const express = require("express");
const childProcess = require("child_process");
const path = require("path");
const fs = require("fs");
const util = require("util");
const os = require("os");
const { fileURLToPath } = require("url");
const { v4: uuidv4 } = require("uuid");
const bodyParser = require("body-parser");
const awsServerlessExpressMiddleware = require("aws-serverless-express/middleware");
const AWS = require("aws-sdk");
const workdir = os.tmpdir();

const s3 = new AWS.S3();

// declare a new express app
const app = express();
app.use(bodyParser.json());
app.use(awsServerlessExpressMiddleware.eventContext());

// Enable CORS for all methods
app.use(function (req, res, next) {
 res.header("Access-Control-Allow-Origin", "*");
 res.header("Access-Control-Allow-Headers", "*");
 next();
});

const downloadFileFromS3 = function (bucket, fileKey, filePath) {
 "use strict";
 console.log("downloading", bucket, fileKey, filePath);
 return new Promise(function (resolve, reject) {
 const file = fs.createWriteStream(filePath),
 stream = s3
 .getObject({
 Bucket: bucket,
 Key: fileKey,
 })
 .createReadStream();
 stream.on("error", reject);
 file.on("error", reject);
 file.on("finish", function () {
 console.log("downloaded", bucket, fileKey);
 resolve(filePath);
 });
 stream.pipe(file);
 });
};

const uploadFileToS3 = function (bucket, fileKey, filePath, contentType) {
 "use strict";
 console.log("uploading", bucket, fileKey, filePath);
 return s3
 .upload({
 Bucket: bucket,
 Key: fileKey,
 Body: fs.createReadStream(filePath),
 ACL: "private",
 ContentType: contentType,
 })
 .promise();
};

const spawnPromise = function (command, argsarray, envOptions) {
 return new Promise((resolve, reject) => {
 console.log("executing", command, argsarray.join(" "));
 const childProc = childProcess.spawn(
 command,
 argsarray,
 envOptions || { env: process.env, cwd: process.cwd() }
 ),
 resultBuffers = [];
 childProc.stdout.on("data", (buffer) => {
 console.log(buffer.toString());
 resultBuffers.push(buffer);
 });
 childProc.stderr.on("data", (buffer) => console.error(buffer.toString()));
 childProc.on("exit", (code, signal) => {
 console.log(`${command} completed with ${code}:${signal}`);
 if (code || signal) {
 reject(`${command} failed with ${code || signal}`);
 } else {
 resolve(Buffer.concat(resultBuffers).toString().trim());
 }
 });
 });
};

app.post("/api/addWatermark", async (req, res) => {
 try {
 const bucketName = "bucketName ";
 const uniqeName = uuidv4() + Date.now();
 const outputPath = path.join(workdir, uniqeName + ".mp4");
 const key = "file_example_MP4_480_1_5MG.mp4";
 const localFilePath = path.join(workdir, key);
 const watermarkPngKey = "watermark.png";
 const watermarkLocalFilePath = path.join(workdir, watermarkPngKey);

 downloadFileFromS3(bucketName, key, localFilePath)
 .then(() => {
 downloadFileFromS3(bucketName, watermarkPngKey, watermarkLocalFilePath)
 .then(() => {
 fs.readFile(localFilePath, (err, data) => {
 if (!err && data) {
 console.log("successsss111");
 }
 });
 fs.readFile(watermarkLocalFilePath, (err, data) => {
 if (!err && data) {
 console.log("successsss222");
 }
 });

 fs.readFile(outputPath, (err, data) => {
 if (!err && data) {
 console.log("successsss3333");
 }
 });

 spawnPromise(
 "/opt/bin/ffmpeg",
 [
 "-i",
 localFilePath,
 "-i",
 watermarkLocalFilePath,
 "-filter_complex",
 `[1]format=rgba,colorchannelmixer=aa=0.5[logo];[0][logo]overlay=5:H-h-5:format=auto,format=yuv420p`,
 "-c:a",
 "copy",
 outputPath,
 ],
 { env: process.env, cwd: workdir }
 )
 .then(() => {
 uploadFileToS3(
 bucketName,
 uniqeName + ".mp4",
 outputPath,
 "mp4"
 );
 });
 });
 });
 } catch (err) {
 console.log({ err });
 res.json({ err });
 }
});

app.listen(8136, function () {
 console.log("App started");
});

module.exports = app;




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ffmpeg transcode to live stream
14 septembre 2016, par brayancastropI need to display a ip camera stream in an html video tag, i have figured out how to transcode to a file from the rtsp stream like this
ffmpeg -i "rtsp://user:password@ip" -s 640x480 /tmp/output.mp4
now i need to be able to be able to live stream the rtsp input in a video tag like this
<video src="http://domain:port/output.mp4" autoplay="autoplay"></video>
I was trying to do something like this in my server (an ubuntu micro instance on amazon) in order to reproduce the video in the video tag but didn’t work
ffmpeg -i "rtsp://user:password@ip" -s 640x480 http://localhost:8080/stream.mp4
instead i got this log
[tcp @ 0x747b40] Connection to tcp://localhost:8080 failed: Connection refused
http://localhost:8080/stream.mp4: Connection refusedi don’t really understand what’s happening, not sure if it’s sending the output to that url or serving the output there and this, i’ve been checking the ffmpeg man docs but i didn’t find any example related to this use case and also other questiones like this one FFmpeg Stream Transcoding which is similar to my last try without success
btw, this is the camera i’m using DS-2CD2020F-I(W) - http://www.hikvision.com/en/Products_accessries_157_i5847.html
they offer an httppreview but it’s just an img tag source which updates but appears to be unstableThis is my first time trying to do something like this so any insight about how to achieve it will be really usefull and appreciated