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Autres articles (69)

  • Websites made ​​with MediaSPIP

    2 mai 2011, par

    This page lists some websites based on MediaSPIP.

  • Personnaliser en ajoutant son logo, sa bannière ou son image de fond

    5 septembre 2013, par

    Certains thèmes prennent en compte trois éléments de personnalisation : l’ajout d’un logo ; l’ajout d’une bannière l’ajout d’une image de fond ;

  • Creating farms of unique websites

    13 avril 2011, par

    MediaSPIP platforms can be installed as a farm, with a single "core" hosted on a dedicated server and used by multiple websites.
    This allows (among other things) : implementation costs to be shared between several different projects / individuals rapid deployment of multiple unique sites creation of groups of like-minded sites, making it possible to browse media in a more controlled and selective environment than the major "open" (...)

Sur d’autres sites (7873)

  • aarch64 : vp9 : use alternative returns in the core loop filter function

    14 novembre 2016, par Janne Grunau
    aarch64 : vp9 : use alternative returns in the core loop filter function

    Since aarch64 has enough free general purpose registers use them to
    
branch to the appropiate storage code. 1-2 cycles faster for the
    
functions using loop_filter 8/16, ... on a cortex-a53. Mixed results
    
(up to 2 cycles faster/slower) on a cortex-a57.
    • [DBH] libavcodec/aarch64/vp9lpf_neon.S

  • tf.contrib.signal.stft returns an empty matrix

    9 décembre 2017, par matt-pielat

    This is the piece of code I run :

    import tensorflow as tf
    

    
sess = tf.InteractiveSession()
    

    
filename = 'song.mp3' # 30 second mp3 file
    
SAMPLES_PER_SEC = 44100
    

    
audio_binary = tf.read_file(filename)
    

    
pcm = tf.contrib.ffmpeg.decode_audio(audio_binary, file_format='mp3', samples_per_second=SAMPLES_PER_SEC, channel_count = 1)
    
stft = tf.contrib.signal.stft(pcm, frame_length=1024, frame_step=512, fft_length=1024)
    

    
sess.close()

    The mp3 file is properly decoded because print(pcm.eval().shape) returns :

    (1323119, 1)

    And there are even some actual non-zero values when I print them with print(pcm.eval()[1000:1010]) :

    [[ 0.18793298]
    
 [ 0.16214484]
    
 [ 0.16022217]
    
 [ 0.15918455]
    
 [ 0.16428113]
    
 [ 0.19858395]
    
 [ 0.22861415]
    
 [ 0.2347789 ]
    
 [ 0.22684409]
    
 [ 0.20728172]]

    But for some reason print(stft.eval().shape) evaluates to :

    (1323119, 0, 513) # why the zero dimension?

    And therefore print(stft.eval()) is :

    []

    According to this the second dimension of the tf.contrib.signal.stft output is equal to the number of frames. Why are there no frames though ?

  • lavc/vaapi_encode : grow packet if vaMapBuffer returns multiple buffers

    31 mai 2019, par Linjie Fu
    lavc/vaapi_encode : grow packet if vaMapBuffer returns multiple buffers

    Currently, assigning new buffer for pkt when multiple buffers were returned
    
from vaMapBuffer will overwrite the previous encoded pkt data and lead
    
to encode issues.
    

    Iterate through the buf_list first to find out the total buffer size
    
needed for the pkt, allocate the whole pkt to avoid repeated reallocation
    
and memcpy, then copy data from each buf to pkt.
    

    Signed-off-by : Linjie Fu <linjie.fu@intel.com>
    • [DH] libavcodec/vaapi_encode.c

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