Abstract

A lot has been done in the field of data compression, yet we don’t have a proper application for compressing daily usage files. There are appropriate and very specific tools online that provide files to be compressed and saved, but the content we use for streaming our videos, be it a Netflix video or a gaming theater play, data consumed is beyond the calculation of a user. Back-end developers know all about it and as developers we have acknowledged it but not yet achieved it in providing on an ease level. Since the user would not never be concerned about compression, developers can always take initiative while building the application to provide accessibility with compression before-hand. We have decided to create a framework that will provide all the functionality needed for a developer to add this feature. Making use of the python language this process can work. I’m a big fan of Python, mostly because it has a vibrant developer community that has helped produce an unparalleled collection of libraries that enable one to add features to applications quickly. For the DEFLATE lossless compression, has a higher level of abstraction provided by the zlib C library, in Python it is generally provided by the Python zlib library which is an interface, we have a lot to do including the audio, video and subtitles of the file. We also make use of the fabulous ffmpy library.  ffmpy is a Python library that provides access to the ffmpeg command line utility. ffmpeg is a command-line application that can perform several different kinds of transformations on video files, including video compression, which is the most commonly requested feature of ffmpeg. Frame rate and audio synchronization are few other parameters to look closely. This is an ongoing project and there remains few implementation aspects, data compression remains a concern when touched upon the design. We along with python community intend to solve this issue.

Keywords

  • AI-Driven Techniques
  • Big Data Analytics

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