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  • List of compatible distributions

    26 avril 2011, par

    The table below is the list of Linux distributions compatible with the automated installation script of MediaSPIP. Distribution nameVersion nameVersion number Debian Squeeze 6.x.x Debian Weezy 7.x.x Debian Jessie 8.x.x Ubuntu The Precise Pangolin 12.04 LTS Ubuntu The Trusty Tahr 14.04
    If you want to help us improve this list, you can provide us access to a machine whose distribution is not mentioned above or send the necessary fixes to add (...)

  • Publier sur MédiaSpip

    13 juin 2013

    Puis-je poster des contenus à partir d’une tablette Ipad ?
    Oui, si votre Médiaspip installé est à la version 0.2 ou supérieure. Contacter au besoin l’administrateur de votre MédiaSpip pour le savoir

  • Les formats acceptés

    28 janvier 2010, par

    Les commandes suivantes permettent d’avoir des informations sur les formats et codecs gérés par l’installation local de ffmpeg :
    ffmpeg -codecs ffmpeg -formats
    Les format videos acceptés en entrée
    Cette liste est non exhaustive, elle met en exergue les principaux formats utilisés : h264 : H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10 m4v : raw MPEG-4 video format flv : Flash Video (FLV) / Sorenson Spark / Sorenson H.263 Theora wmv :
    Les formats vidéos de sortie possibles
    Dans un premier temps on (...)

Sur d’autres sites (10282)

  • Introducing the Data Warehouse Connector feature

    30 janvier, par Matomo Core Team

    Matomo is built on a simple truth : your data belongs to you, and you should have complete control over it. That’s why we’re excited to launch our new Data Warehouse Connector feature for Matomo Cloud, giving you even more ways to work with your analytics data. 

    Until now, getting raw data from Matomo Cloud required APIs and custom scripts, or waiting for engineering help.  

    Our new Data Warehouse Connector feature removes those barriers. You can now access your raw, unaggregated data and schedule regular exports straight to your data warehouse. 

    The feature works with all major data warehouses including (but not limited to) : 

    • Google BigQuery 
    • Amazon Redshift 
    • Snowflake 
    • Azure Synapse Analytics 
    • Apache Hive 
    • Teradata 

    You can schedule exports, combine your Matomo data with other data sources in your data warehouse, and easily query data with SQL-like queries. 

    Direct raw data access for greater data portability 

    Waiting for engineering support can delay your work. Managing API connections and writing scripts can be time-consuming. This keeps you from focusing on what you do best—analysing data. 

    BigQuery create-table-menu

    With the Data Warehouse Connector feature, you get direct access to your raw Matomo data without the technical setup. So, you can spend more time analysing data and finding insights that matter. 

    Bringing your data together 

    Answering business questions often requires data from multiple sources. A single customer interaction might span your CRM, web analytics, sales systems, and more. Piecing this data together manually is time-consuming—what starts as a seemingly simple question from stakeholders can turn into hours of work collecting and comparing data across different tools. 

    This feature lets you combine your Matomo data with data from other business systems in your data warehouse. Instead of switching between tools or manually comparing spreadsheets, you can analyse all your data in one place to better understand how customers interact with your business. 

    Easy, custom analysis with SQL-like queries 

    Standard, pre-built reports often don’t address the specific, detailed questions that analysts need to answer.  

    When you use the Data Warehouse Connector feature, you can use SQL-like queries in your data warehouse to do detailed, customised analysis. This flexibility allows you to explore your data in depth and uncover specific insights that aren’t possible with pre-built reports. 

    Here is an example of how you might use SQL-like query to compare the behaviours of paying vs. non-paying users : 

    				
                                            <xmp>SELECT  

    custom_dimension_value AS user_type, -- Assuming 'user_type' is stored in a custom dimension

    COUNT(*) AS total_visits,  

    AVG(visit_total_time) AS avg_duration,

    SUM(conversion.revenue) AS total_spent  

    FROM  

    `your_project.your_dataset.matomo_log_visit` AS visit

    LEFT JOIN  

    `your_project.your_dataset.matomo_log_conversion` AS conversion  

    ON  

    visit.idvisit = conversion.idvisit  

    GROUP BY  

    custom_dimension_value; </xmp>
                                   

    This query helps you compare metrics such as the number of visits, average session duration, and total amount spent between paying and non-paying users. It provides a full view of behavioural differences between these groups. 

    Advanced data manipulation and visualisation 

    When you need to create detailed reports or dive deep into data analysis, working within the constraints of a fixed user interface (UI) can limit your ability to draw insights. 

    Exporting your Matomo data to a data warehouse like BigQuery provides greater flexibility for in-depth manipulation and advanced visualisations, enabling you to uncover deeper insights and tailor your reports more effectively. 

    Getting started 

    To set up data warehouse exports in your Matomo : 

    1. Go to System Admin (cog icon in the top right corner) 
    2. Select ‘Export’ from the left-hand menu 
    3. Choose ‘Data Warehouse Connector’ 

    You’ll find detailed instructions in our data warehouse exports guide 

    Please note, enabling this feature will cost an additional 10% of your current subscription. You can view the exact cost by following the steps above. 

    New to Matomo ? Start your 21-day free trial now (no credit card required), or request a demo. 

  • configure : update copyright year

    1er janvier, par Lynne
    configure : update copyright year
    

    On 01/01/2025 19:05, Peter Ross wrote :
    > FFmpeg turns 25 this year.

    • [DH] configure
  • FFMPEG equalizer clipping audio despite low volume

    23 juillet 2023, par Tom

    I'm using ffmpeg to equalise audio transferred from historic gramophone records, using standard eqs of the era.

    &#xA;

    The frequency and gain values are taken from the graphic eq settings listed on the Audacity website - https://plugins.audacityteam.org/additional-resources/eq-curves/playback-equalization-for-78-rpm-shellacs-and-early-33-lps

    &#xA;

    An example of the Blumlien300 curve here - https://2850314611-files.gitbook.io/ /files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FklCVENFte0GRy5IqVz0W%2Fuploads%2FJHS6Mv121GX1h898xy4K%2FBlumlein300_3.2.2.txt?alt=media&token=8d04df05-366d-47f8-8c82-149fa5eda59a

    &#xA;

    The audio file I'm testing with has a digital peak of -35db, the highest gain value applied on this eq is 17db. When I run the ffmpeg command though, it reports the audio is clipping and the result is a horribly distorted recording.

    &#xA;

    Can anyone advise why this is happening ? I run the same file through the same eq settings in Audacity and the result is as expected.

    &#xA;

    set eq="equalizer=f=22050:g=-0.4,equalizer=f=21203.720228928225:g=-0.4,equalizer=f=20389.920705063967:g=-0.4,equalizer=f=19607.354835383569:g=-0.4,equalizer=f=18854.823871147240:g=-0.4,equalizer=f=18131.175071633737:g=-0.4,equalizer=f=17435.299938351014:g=-0.4,equalizer=f=16766.132517017904:g=-0.4,equalizer=f=16122.647764715837:g=-0.4,equalizer=f=15503.859979709296:g=-0.4,equalizer=f=14908.821291529812:g=-0.4,equalizer=f=14336.620209010769:g=-0.4,equalizer=f=13786.380224048187:g=-0.4,equalizer=f=13257.258468950000:g=-0.4,equalizer=f=12748.444425315412:g=-0.4,equalizer=f=12259.158682468413:g=-0.4,equalizer=f=11788.651743541806:g=-0.4,equalizer=f=11336.202877384472:g=-0.4,equalizer=f=10901.119014532051:g=-0.4,equalizer=f=10482.733685550458:g=-0.4,equalizer=f=10080.406000125797:g=-0.4,equalizer=f=9693.519665336817:g=-0.4,equalizer=f=9321.482041606178:g=-0.4,equalizer=f=8963.723234884175:g=-0.4,equalizer=f=8619.695223674737:g=-0.4,equalizer=f=8288.871019565895:g=-0.4,equalizer=f=7970.743859979441:g=-0.4,equalizer=f=7664.826431902562:g=-0.4,equalizer=f=7370.650125412990:g=-0.4,equalizer=f=7087.764315853595:g=-0.4,equalizer=f=6815.735673557399:g=-0.4,equalizer=f=6554.147500065165:g=-0.4,equalizer=f=6302.599089819104:g=-0.4,equalizer=f=6060.705116354743:g=-0.4,equalizer=f=5828.095042050793:g=-0.4,equalizer=f=5604.412550532827:g=-0.4,equalizer=f=5389.315000861326:g=-0.4,equalizer=f=5182.472902668021:g=-0.394052055589,equalizer=f=4983.569411436476:g=-0.386751590389,equalizer=f=4792.299843153906:g=-0.376185664074,equalizer=f=4608.371207590573:g=-0.362543760251,equalizer=f=4431.501759492006:g=-0.345993198097,equalizer=f=4261.420566996452:g=-0.330710126890,equalizer=f=4097.867096616487:g=-0.318503033191,equalizer=f=3940.590814149046:g=-0.309564283335,equalizer=f=3789.350800902538:g=-0.303741189604,equalizer=f=3643.915384653179:g=-0.300601888512,equalizer=f=3504.061784765236:g=-0.3,equalizer=f=3369.575770931567:g=-0.3,equalizer=f=3240.251335011708:g=-0.3,equalizer=f=3115.890375464830:g=-0.3,equalizer=f=2996.302393894170:g=-0.3,equalizer=f=2881.304203238093:g=-0.3,equalizer=f=2770.719647160795:g=-0.3,equalizer=f=2664.379330212802:g=-0.3,equalizer=f=2562.120358347913:g=-0.3,equalizer=f=2463.786089399117:g=-0.3,equalizer=f=2369.225893131248:g=-0.3,equalizer=f=2278.294920502843:g=-0.3,equalizer=f=2190.853881783698:g=-0.3,equalizer=f=2106.768833188346:g=-0.296437432785,equalizer=f=2025.910971698469:g=-0.290217913930,equalizer=f=1948.156437760116:g=-0.280922418484,equalizer=f=1873.386125553329:g=-0.268550946447,equalizer=f=1801.485500543704:g=-0.253103497820,equalizer=f=1732.344424036255:g=-0.235614749092,equalizer=f=1665.856984462975:g=-0.218076286078,equalizer=f=1601.921335145533:g=-0.200537822606,equalizer=f=1540.439538284674:g=-0.184632657170,equalizer=f=1481.317414937308:g=-0.168779161348,equalizer=f=1424.464400751469:g=-0.152925665153,equalizer=f=1369.793407238189:g=-0.137072168707,equalizer=f=1317.220688367753:g=-0.121218672255,equalizer=f=1266.665712285991:g=-0.105365175802,equalizer=f=1218.051037954117:g=-0.088396941462,equalizer=f=1171.302196523118:g=-0.070858476440,equalizer=f=1126.347577261013:g=-0.053320011417,equalizer=f=1083.118317858216:g=-0.034770724190,equalizer=f=1041.548198942992:g=-0.013200571808,equalizer=f=1001.573542645411:g=0.011445558081,equalizer=f=963.133115054414:g=0.039167665478,equalizer=f=926.168032418592:g=0.069965750383,equalizer=f=890.621670946974:g=0.103839812794,equalizer=f=856.439580071665:g=0.140789852714,equalizer=f=823.569399039473:g=0.180815870141,equalizer=f=791.960776704742:g=0.223158863450,equalizer=f=761.565294400547:g=0.266149082252,equalizer=f=732.336391770094:g=0.311823093692,equalizer=f=704.229295444710:g=0.360237839089,equalizer=f=677.200950459179:g=0.413174176689,equalizer=f=651.209954299352:g=0.471478099167,equalizer=f=626.216493481026:g=0.535493496953,equalizer=f=602.182282562909:g=0.606978871276,equalizer=f=579.070505500287:g=0.684199304160,equalizer=f=556.845759249530:g=0.767096732395,equalizer=f=535.473999537060:g=0.853776460170,equalizer=f=514.922488709709:g=0.943323717867,equalizer=f=495.159745586582:g=1.036571598687,equalizer=f=476.155497235608:g=1.135335711982,equalizer=f=457.880632600910:g=1.237175803242,equalizer=f=440.307157909949:g=1.342335109599,equalizer=f=423.408153792158:g=1.453088412615,equalizer=f=407.157734043353:g=1.569993670188,equalizer=f=391.531005972773:g=1.688508164136,equalizer=f=376.504032271996:g=1.808802987893,equalizer=f=362.053794347337:g=1.934465396527,equalizer=f=348.158157059540:g=2.065823830001,equalizer=f=334.795834816768:g=2.204891058267,equalizer=f=321.946358968944:g=2.352009664049,equalizer=f=309.590046453497:g=2.509552803849,equalizer=f=297.707969644483:g=2.678532979186,equalizer=f=286.281927358906:g=2.856115742576,equalizer=f=275.294416975809:g=3.041612670003,equalizer=f=264.728607625441:g=3.230723044219,equalizer=f=254.568314407418:g=3.422700948357,equalizer=f=244.797973598401:g=3.621312762050,equalizer=f=235.402618811295:g=3.826195809769,equalizer=f=226.367858069467:g=4.034154835453,equalizer=f=217.679851760848:g=4.246639157749,equalizer=f=209.325291438168:g=4.468048945659,equalizer=f=201.291379432825:g=4.698686666092,equalizer=f=193.565809251186:g=4.938552319047,equalizer=f=186.136746723276:g=5.187645904525,equalizer=f=178.992811874976:g=5.445967422525,equalizer=f=172.123061495972:g=5.712025685327,equalizer=f=165.516972376744:g=5.984236264250,equalizer=f=159.164425188922:g=6.258981796419,equalizer=f=153.055688984312:g=6.515823590632,equalizer=f=147.181406288853:g=6.777692051390,equalizer=f=141.532578768664:g=7.044587178695,equalizer=f=136.100553446236:g=7.314095599483,equalizer=f=130.877009445637:g=7.583605034445,equalizer=f=125.853945246444:g=7.853114469407,equalizer=f=121.023666426868:g=8.146285201135,equalizer=f=116.378773877299:g=8.444439101287,equalizer=f=111.912152466211:g=8.742593001439,equalizer=f=107.616960141075:g=9.042209423688,equalizer=f=103.486617447577:g=9.344900874707,equalizer=f=99.514797451091:g=9.650668303691,equalizer=f=95.695416044961:g=9.959511710641,equalizer=f=92.022622630759:g=10.271431095557,equalizer=f=88.490791156230:g=10.586541422511,equalizer=f=85.094511497198:g=10.906991735356,equalizer=f=81.828581170245:g=11.233594002758,equalizer=f=78.687997363448:g=11.556996378650,equalizer=f=75.667949272979:g=11.873211536187,equalizer=f=72.763810733831:g=12.194794278600,equalizer=f=69.971133133372:g=12.521192148224,equalizer=f=67.285638596875:g=12.846501740168,equalizer=f=64.703213434600:g=13.169127539473,equalizer=f=62.219901840358:g=13.492484068742,equalizer=f=59.831899831942:g=13.820346094285,equalizer=f=57.535549424116:g=14.145340590334,equalizer=f=55.327333025244:g=14.467659297988,equalizer=f=53.203868048980:g=14.789401139821,equalizer=f=51.161901732761:g=15.111142981226,equalizer=f=49.198306155165:g=15.437629968456,equalizer=f=47.310073444503:g=15.770860796927,equalizer=f=45.494311171305:g=16.104091624940,equalizer=f=43.748237917649:g=16.412536097232,equalizer=f=42.069179016527:g=16.579143834849,equalizer=f=40.454562454745:g=16.588876722789,equalizer=f=38.901914933067:g=16.461103901687,equalizer=f=37.408858077565:g=16.215674576171,equalizer=f=35.973104796389:g=15.850016386783,equalizer=f=34.592455776352:g=15.350234288456,equalizer=f=33.264796113983:g=14.615823142814,equalizer=f=31.988092075884:g=13.626809695512,equalizer=f=30.760387983412:g=12.332756508563,equalizer=f=29.579803216941:g=10.518513413063,equalizer=f=28.444529335092:g=8.346792732977,equalizer=f=27.352827304528:g=5.833681758551,equalizer=f=26.303024836072:g=3.097942665008,equalizer=f=25.293513823067:g=0.163604913582,equalizer=f=24.322747878043:g=-2.887748621210,equalizer=f=23.389239963935:g=-6.091081601564,equalizer=f=22.491560116216:g=-9.478973229620,equalizer=f=21.628333252442:g=-12.539218030638,equalizer=f=20.798237065887:g=-14.384804507659,equalizer=f=20:g=-15"&#xA;ffmpeg -i "File.wav" -af %eq% -c:a pcm_s24le out.wav&#xA;

    &#xA;