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  • Des sites réalisés avec MediaSPIP

    2 mai 2011, par

    Cette page présente quelques-uns des sites fonctionnant sous MediaSPIP.
    Vous pouvez bien entendu ajouter le votre grâce au formulaire en bas de page.

  • Use, discuss, criticize

    13 avril 2011, par

    Talk to people directly involved in MediaSPIP’s development, or to people around you who could use MediaSPIP to share, enhance or develop their creative projects.
    The bigger the community, the more MediaSPIP’s potential will be explored and the faster the software will evolve.
    A discussion list is available for all exchanges between users.

  • Supporting all media types

    13 avril 2011, par

    Unlike 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 (...)

Sur d’autres sites (7319)

  • FFMPEG - how to convert large file to much smaller file to view on LG smart TV

    18 juin 2019, par PAW

    I have edited a home movie thru Davinci Resolve and the output has been rendered/saved on my PC. For some strange reason it seems huge and nothing will play it (apart from within Resolve itself) and none of my conversion software will convert it from the huge file to something smaller I can watch on my LG smart TV (handbrake, video converter).

    I downloaded FFMPEG and installed it, then ran a command to examine the file. Results posted here. Does this mean that FFMPEG has found the codec and I can convert it ? and has anyone any suggestions on what to convert it to ?

    Many thanks

    ffmpeg -i C:\Users\PAW\Videos\Resolve\untitled.mov
    

    
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'C:\Users\PAW\Videos\Resolve\untitled.mo
    
v':
    

    
  Metadata:
    

    
    major_brand     : qt
    
    minor_version   : 512
    
    compatible_brands: qt
    
    encoder         : Lavf57.25.100
    

    
Duration: 01:09:43.81, start: 0.000000, bitrate: 390431 kb/s
    
    Stream #0:0(eng): Video: dnxhd (DNXHR 444) (AVdh / 0x68645641), yuv444p12le(
    
tv, bt709/unknown/unknown), 1280x720, 388894 kb/s, 59.94 fps, 59.94 tbr, 60k tbn
    
, 60k tbc (default)
    

    
    Metadata:
    
      handler_name    : Core Media Data Handler
    
      timecode        : 01:00:00:00
    
    Stream #0:1(eng): Audio: pcm_s16le (sowt / 0x74776F73), 48000 Hz, stereo, s1
    
6, 1536 kb/s (default)
    
    Metadata:
    
      handler_name    : Core Media Data Handler
    
    Stream #0:2(eng): Data: none (tmcd / 0x64636D74)
    
    Metadata:
    
      handler_name    : Core Media Data Handler
    
      timecode        : 01:00:00:00

  • make : *** No rule to make target 'jni/../third_party/lame/libmp3lame/VbrTag.c', needed by 'obj/local/arm64-v8a/objs/lame/VbrTag.o'. Stop

    29 mars 2020, par Pradeep Simba

    my jni folder
    enter image description here

    enter image description here

    when I build ndk it comes like this.

    How can I solve this ?

  • Make a numpy array look like a video file

    1er juillet 2020, par zagaroo

    I am building a Python web app for visualization of video data. The video is a T x X x Y array stored as an HDF5 file and is too large to load into memory. However, I have the following libraries.

    


    Library #1 is an HDF5 reader that allows me to do random access on the video file on disk, so I can get arbitrary frames as numpy arrays.

    


    Library #2 (streamlit) is a web library that allows me to display standard video types (mp4, h264, etc.) [API link].

    


    I am thinking that all I need to do is write an intermediate class that behaves like a BytesIO object and gets frames as they are requested by the web viewer without loading the whole video into RAM. However, what I'm stuck on is how to add the appropriate headers to a numpy array to make it look like it came from an mp4/h264/etc. (and which of these formats would make this easiest).

    


    Any ideas ?

    


    Thanks !

    


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