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Autres articles (54)
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Les autorisations surchargées par les plugins
27 avril 2010, parMediaspip core
autoriser_auteur_modifier() afin que les visiteurs soient capables de modifier leurs informations sur la page d’auteurs -
List of compatible distributions
26 avril 2011, parThe 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 (...) -
Automated installation script of MediaSPIP
25 avril 2011, parTo overcome the difficulties mainly due to the installation of server side software dependencies, an "all-in-one" installation script written in bash was created to facilitate this step on a server with a compatible Linux distribution.
You must have access to your server via SSH and a root account to use it, which will install the dependencies. Contact your provider if you do not have that.
The documentation of the use of this installation script is available here.
The code of this (...)
Sur d’autres sites (10397)
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Merge commit ’86eee85daddb682fa072c2e2657c90a514b855e3’
12 juillet 2015, par Michael Niedermayer -
avcodec/av1dec : Pass AVCodecContext* as logctx in get_sw_pixel_format()
10 septembre 2023, par Andreas Rheinhardt -
Make a numpy array look like a video file
1er juillet 2020, par zagarooI 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 !