Recherche avancée

Sur d’autres sites (9194)

• Zlib vs. XZ on 2SF

  21 juillet 2012, par Multimedia Mike — General, psf, saltygme, xz, zlib

  I recently released my Game Music Appreciation website. It allows users to play an enormous range of video game music directly in their browsers. To do this, the site has to host the music. And since I’m a compression bore, I have to know how small I can practically make these music files. I already published the results of my effort to see if XZ could beat RAR (RAR won, but only slightly, and I still went with XZ for the project) on the corpus of Super Nintendo chiptune sets. Next is the corpus of Nintendo DS chiptunes.

  Repacking Nintendo DS 2SF
  The prevailing chiptune format for storing Nintendo DS songs is the .2sf format. This is a subtype of the Portable Sound Format (PSF). The designers had the foresight to build compression directly into the format. Much of payload data in a PSF file is compressed with zlib. Since I already incorporated Embedded XZ into the player project, I decided to try repacking the PSF payload data from zlib -> xz.

  In an effort to not corrupt standards too much, I changed the ’PSF’ file signature (seen in the first 3 bytes of a file) to ’psf’.

  Results
  There are about 900 Nintendo DS games currently represented in my website’s archive. Total size of the original PSF archive, payloads packed with zlib : 2.992 GB. Total size of the same archive with payloads packed as xz : 2.059 GB.

  Using xz vs. zlib saved me nearly a gigabyte of storage. That extra storage doesn’t really impact my hosting plan very much (I have 1/2 TB, which is why I’m so nonchalant about hosting the massive MPlayer Samples Archive). However, smaller individual files translates to a better user experience since the files are faster to download.

  Here is a pretty picture to illustrate the space savings :

  
  
  

  The blue occasionally appears to dip below the orange but the data indicates that xz is always more efficient than zlib. Here’s the raw data (comes in vanilla CSV flavor too).

  Interface Impact
  So the good news for the end user is that the songs are faster to load up front. The downside is that there can be a noticeable delay when changing tracks. Even though all songs are packaged into one file for download, and the entire file is downloaded before playback begins, each song is individually compressed. Thus, changing tracks triggers another decompression operation. I’m toying the possibility of some sort of background process that decompresses song (n+1) while playing song (n) in order to help compensate for this.

  I don’t like the idea of decompressing everything up front because A) it would take even longer to start playing ; and B) it would take a huge amount of memory.

  Corner Case
  There was at least one case in which I found zlib to be better than xz. It looks like zlib’s minimum block size is smaller than xz’s. I think I discovered xz to be unable to compress a few bytes to a block any smaller than about 60-64 bytes while zlib got it down into the teens. However, in those cases, it was more efficient to just leave the data uncompressed anyway.

• Revision f8630c78d1 : configure : remove php test + the remnants in the build system & README the doc

  10 mai 2014, par James Zern

  Changed Paths :
   Modify /README

  
   Modify /configure

  
   Modify /docs.mk

  
  
  configure : remove php test

  + the remnants in the build system & README

  the documentation that required php was removed in :
  50fa585 Removing examples code generation and making them static.

  Change-Id : Ibf00dca9ab2715fc21e8de358807b63d1445662c

• How to read a MP3 audio file into a numpy array / save a numpy array to MP3 ?

  15 juin 2021, par Basj

  Is there a way to read/write a MP3 audio file into/from a numpy array with a similar API to scipy.io.wavfile.read and scipy.io.wavfile.write :

  



  sr, x = wavfile.read('test.wav')
wavfile.write('test2.wav', sr, x)


  



   ?

  



  Note : pydub's AudioSegment object doesn't give direct access to a numpy array.

  



  ^{PS : I have already read Importing sound files into Python as NumPy arrays (alternatives to audiolab), tried all the answers, including those which requires to Popen ffmpeg and read the content from stdout pipe, etc. I have also read Trying to convert an mp3 file to a Numpy Array, and ffmpeg just hangs, etc., and tried the main answers, but there was no simple solution. After spending hours on this, I'm posting it here with "Answer your own question – share your knowledge, Q&A-style". I have also read How to create a numpy array from a pydub AudioSegment ? but this does not easily cover the multi channel case, etc.}