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  • Les autorisations surchargées par les plugins

    27 avril 2010, par

    Mediaspip core
    autoriser_auteur_modifier() afin que les visiteurs soient capables de modifier leurs informations sur la page d’auteurs

  • Contribute to a better visual interface

    13 avril 2011

    MediaSPIP is based on a system of themes and templates. Templates define the placement of information on the page, and can be adapted to a wide range of uses. Themes define the overall graphic appearance of the site.
    Anyone can submit a new graphic theme or template and make it available to the MediaSPIP community.

  • Librairies et binaires spécifiques au traitement vidéo et sonore

    31 janvier 2010, par

    Les logiciels et librairies suivantes sont utilisées par SPIPmotion d’une manière ou d’une autre.
    Binaires obligatoires FFMpeg : encodeur principal, permet de transcoder presque tous les types de fichiers vidéo et sonores dans les formats lisibles sur Internet. CF ce tutoriel pour son installation ; Oggz-tools : outils d’inspection de fichiers ogg ; Mediainfo : récupération d’informations depuis la plupart des formats vidéos et sonores ;
    Binaires complémentaires et facultatifs flvtool2 : (...)

Sur d’autres sites (9818)

  • Why does my Blink based browser play hide and seek ?

    21 janvier 2016, par Caius Jard

    We have a C# tool (that I wrote) that records online broadcasts taking place a custom written (that we wrote) flash app. (There are no DRM or copyright issues here.)

    We’ve coded up a system whereby this tool is installed on a Windows Server 2012 R2 Amazon AWS instance. After we boot the instance, the tool loads, waits for the right time to start recording, launches a browser and passes the command line argument of the URL to access the broadcast. The browser will then load the flash app and the interview audio and video will start arriving at the browser instance on AWS

    By way of a virtual audio cable driver, screen / audio capture directshow filters and ffmpeg a screen recording is taken. The C# tool calls ffmpeg and ffmpeg will record the screen reliably for the entire interview, then the tool shuts the whole thing down

    The problem I’m having is that both Chrome and Electron browser sometimes simply don’t draw themselves on the screen so all ffmpeg ends up recording is a blank desktop and the audio of the broadcast (hence, the browser IS running)

    We found this out when recordings started turning up with X hours of merely recording the windows desktop and the tool’s main window with a countdown timer.

    A screenshotting facility was built into the tool and added to its web control interface, and this way we can test whether the browser is visible - a human looks at the screenshot of every broadcast, just after recording has started (the browser is supposed to be on show by this time)

    We notice that 50% of the time, the browser isn’t drawing itself on screen. By 50% I mean that every other recording that the AWS instance carries out, will be blank : AWS starts, records ok, shuts down. AWS starts again an hour later for a different broadcast, recording is blank, shuts down.. Starts/ok/shutdown. Starts/blank/shutdown. Repeat ad infinitum

    What’s even more strange is that if I run VNCviewer on my dev machine and connect up to an instance that is having a problem, the instant that the VNC connection is up and the remote desktop is showing on my screen, the browser suddenly appears as if nothing was ever wrong. A screenshot from before the VNC connect shows blank desktop, connect VNC, take another screenshot and the browser is there. All through it the audio is fine - the browser connected to the boadcast is fine, for sure

    It’s as though Chrome/Electron thinks "you know what, noone is looking at me so I’m not going to bother drawing myself". No screen saver is set, though the power plan has the setting "turn off the display after 15 minutes".

    Perhaps Chrome/Electron have a test amounts to "if the display is off, don’t draw". I can’t explain the inconsistency though - the recorder launches at least 1 hour before it’s needed, and sits there idle until it’s time to start the browser. You’d hence imagine that the "power off the monitor after 15 mins" setting would reliably have ensured the "monitor" is "off" by the time every recording start comes around

    This behaviour doesn’t happen with any of the other browsers (but unfortunately the app doesn’t and cannot work in them because it uses some weird chrome-only technology/API).

    Can anyone suggest anything to look at to help debug this, or anything I can build into the C# tool to overcome the problem ? Coding it up to connect to itself via VNC for a few seconds after it has launched the browser.. Well that just tastes nasty.

    Naturally, as soon as I connect to the machine via VNC (rather than RDP - RDP isn’t usable because the recording context is in a logged on session for a particular user) the problem goes away, which makes it frustratingly hard to debug.

  • How to make drawtext work in AWS Lambda ffmpeg ?

    22 mars 2020, par codeul

    I have setup an AWS Lambda function to use ffmpeg using layer https://serverlessrepo.aws.amazon.com/applications/arn:aws:serverlessrepo:us-east-1:145266761615:applications~ffmpeg-lambda-layer.

    Some ffmpeg commands work, but noticed when I use drawtext or drawbox, I am not getting a proper mp4 file. The output looks corrupted and is low in size. (FYI : The output file is /tmp/test2.mp4 and then I copy it to an S3 bucket.)

    Whats wrong here ? Would appreciate any help. Thanks.

    ffmpeg command :

    ffmpeg -f lavfi -i color=0x142d3d:s=1280*720:d=10 -vf  "drawtext=fontcolor=white:fontsize=50:fontfile=aladin.ttf:text='test':y=10:x=10"  -movflags +faststart    -y /tmp/test2.mp4

    From log :

    o --cc=gcc-6 --enable-fontconfig --enable-frei0r --enable-gnutls --enable-gmp --enable-gray --enable-libaom --enable-libfribidi --enable-libass --enable-libvmaf --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-librubberband --enable-libsoxr --enable-libspeex --enable-libvorbis --enable-libopus --enable-libtheora --enable-libvidstab --enable-libvo-amrwbenc --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzvbi --enable-libzimg
           libavutil      56. 22.100 / 56. 22.100
           libavcodec     58. 35.100 / 58. 35.100
           libavformat    58. 20.100 / 58. 20.100
           libavdevice    58.  5.100 / 58.  5.100
           libavfilter     7. 40.101 /  7. 40.101
           libswscale      5.  3.100 /  5.  3.100
           libswresample   3.  3.100 /  3.  3.100
           libpostproc    55.  3.100 / 55.  3.100
       Input #0, lavfi, from 'color=0x142d3d:s=1280*720:d=10':
           Duration: N/A, start: 0.000000, bitrate: N/A
           Stream #0:0: Video: rawvideo (I420 / 0x30323449), yuv420p, 1280x720 [SAR 1:1 DAR 16:9], 25 tbr, 25 tbn, 25 tbc
       Stream mapping:
           Stream #0:0 -> #0:0 (rawvideo (native) -> h264 (libx264))
       Press [q] to stop, [?] for help
       [Parsed_drawtext_0 @ 0x5852500] Using "/var/task/fonts/aladin.ttf"
       [libx264 @ 0x5850080] using SAR=1/1
       [libx264 @ 0x5850080] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX
       [libx264 @ 0x5850080] profile Progressive High, level 3.1, 4:2:0, 8-bit
       [libx264 @ 0x5850080] 264 - core 157 r2969 d4099dd - H.264/MPEG-4 AVC codec - Copyleft 2003-2019 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=3 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
       Output #0, mp4, to '/tmp/test2.mp4':
           Metadata:
           encoder         : Lavf58.20.100
           Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuv420p, 1280x720 [SAR 1:1 DAR 16:9], q=-1--1, 25 fps, 12800 tbn, 25 tbc
           Metadata:
               encoder         : Lavc58.35.100 libx264
           Side data:
               cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
       frame=    2 fps=0.0 q=0.0 size=       0kB time=00:00:00.00 bitrate=N/A speed=   0x    
       frame=    9 fps=7.5 q=0.0 size=       0kB time=00:00:00.00 bitrate=N/A speed=   0x    
       frame=   17 fps=9.8 q=0.0 size=       0kB time=00:00:00.00 bitrate=N/A speed=   0x    
       frame=   25 fps= 11 q=0.0 size=       0kB time=00:00:00.00 bitrate=N/A speed=   0x    
       frame=   30 fps=7.4 q=0.0 size=       0kB time=00:00:00.00 bitrate=N/A speed=   0x    
    =================
  • Create mp4 thumbnail in node.js

    21 mai 2015, par trdavidson

    new in node.js and aws framework so I apologize in advance. I am trying to configure the AWS DB of my app to automatically create thumbnails using AWS Lambda. This works great using the example provided by Amazon for regular .jpg images (walkthrough here : https://alestic.com/2014/11/aws-lambda-cli/).

    However to try and do the same operation for mp4 files seems exponentially more difficult. After some searching I found that it seems the way to do this is by using the ffmpeg module. The problem is that I do not at all understand the response object returned by aws, and thus am not sure how to manipulate it so that ffmpeg can use it.

    current code :

    // dependencies
    var async = require('async');
    var AWS = require('aws-sdk');
    var gm = require('gm')
               .subClass({ imageMagick: true }); // Enable ImageMagick integration.
    var util = require('util');
    var ffmpeg = require('ffmpeg');
    var stream = require('stream')

    // constants
    var MAX_WIDTH  = 250;
    var MAX_HEIGHT = 250;

    // get reference to S3 client
    var s3 = new AWS.S3();

    exports.handler = function(event, context) {
       // Read options from the event.
       console.log("Reading options from event:\n", util.inspect(event, {depth: 5}));
       var srcBucket = event.Records[0].s3.bucket.name;
       // Object key may have spaces or unicode non-ASCII characters.
       var srcKey    =
       decodeURIComponent(event.Records[0].s3.object.key.replace(/\+/g, " "));  
       var dstBucket = srcBucket + "small";
       var dstKey    = "small-" + srcKey;
    // Sanity check: validate that source and destination are different buckets.
    if (srcBucket == dstBucket) {
       console.error("Destination bucket must not match source bucket.");
       return;
    }

    // Infer the image type.
    var typeMatch = srcKey.match(/\.([^.]*)$/);
    if (!typeMatch) {
       console.error('unable to infer image type for key ' + srcKey);
       return;
    }
    var imageType = typeMatch[1];
    if (imageType != "mp4" && imageType != "avi") {
       console.log('skipping non-image ' + srcKey);
       return;
    }

    // Download the image from S3, transform, and upload to a different S3 bucket.
    async.waterfall([
       function download(next) {
           // Download the image from S3 into a buffer.

           s3.getObject({
                   Bucket: srcBucket,
                   Key: srcKey
               },
               next);
           },
       function tranform(response, next) {
           var instream = new stream.Readable();
           instream.push(response.Body)
           instream.push(null)

           var outstream = new stream();

           ffmpeg(instream)
           .screenshots({timestamps: 1, size: '200x200'})
           .output('screenshot.png')
           .output(outstream)
           .on('end', function(){
               console.log('screenshots finished processing son!')
           })

           gm(outstream, 'screenshot.png').size(function(err, size) {
               // Infer the scaling factor to avoid stretching the image unnaturally.
               var scalingFactor = Math.min(
                   MAX_WIDTH / size.width,
                   MAX_HEIGHT / size.height
               );
               var width  = scalingFactor * size.width;
               var height = scalingFactor * size.height;

               // Transform the image buffer in memory.
               this.resize(width, height)
                   .toBuffer(imageType, function(err, buffer) {
                       if (err) {
                           next(err);
                       } else {
                           next(null, response.ContentType, buffer);
                       }
                   });
           });
       },
       function upload(contentType, data, next) {
           // Stream the transformed image to a different S3 bucket.
           s3.putObject({
                   Bucket: dstBucket,
                   Key: dstKey,
                   Body: data,
                   ContentType: contentType
               },
               next);
           }
       ], function (err) {
           if (err) {
               console.error(
                   'Unable to resize ' + srcBucket + '/' + srcKey +
                   ' and upload to ' + dstBucket + '/' + dstKey +
                   ' due to an error: ' + err
               );
           } else {
               console.log(
                   'Successfully resized ' + srcBucket + '/' + srcKey +
                   ' and uploaded to ' + dstBucket + '/' + dstKey
               );
           }

           context.done();
       }
    );

    } ;

    Any suggestions are welcome ! Thanks