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• ffmpeg extracting frames from a 60 fps video

  15 juillet 2022, par ggt bnd

  I would like to extract frames from a 60 fps video, all of them I used the ffmpeg code
sevral times on lower fps videos
' ffmpeg -i test.mp4 -qscale:v 1 -qmin 1 -qmax 1 -vsync 0 tmp_frames/frame%08d.jpg "
and it works just fine, knowing that the default fps is 24
how can I change it so it extract at 60 fps
ffmpeg version " ffmpeg-2022-07-06-git-03d81a044a-full_build "

  


• FFMPEG Queue input backward in time

  2 avril 2022, par Spartan 117

  I am trying to combine two audio files, and delaying the second one. Here's my command

  


  ffmpeg -i RTb295d0534191e1acb22a45bb971a12e6.mka -i RT103bfe5f4b129860f69cd8e820f3a10b.mka -filter_complex "[1:a]adelay=13500s:all=1[apad]; [0:a][apad]amix=inputs=2:weights=1|1[aout]" -map [aout] combined_audio.mka


  


  Here is the output that i'm getting, and it's causing an issue where the second audio is delayed by 5 hours and 45 minutes rather than 3 hours and 45 minutes

  


   ffmpeg -i RTb295d0534191e1acb22a45bb971a12e6.mka -i RT103bfe5f4b129860f69cd8e820f3a10b.mka -filter_complex "[1:a]adelay=13500s:all=1[apad]; [0:a][apad]amix=inputs=2:weights=1|1[aout]" -map [aout] combined_audio.mka
ffmpeg version n5.0-4-g911d7f167c-20220311 Copyright (c) 2000-2022 the FFmpeg developers
  built with gcc 11.2.0 (crosstool-NG 1.24.0.533_681aaef)
  configuration: --prefix=/ffbuild/prefix --pkg-config-flags=--static --pkg-config=pkg-config --cross-prefix=x86_64-w64-mingw32- --arch=x86_64 --target-os=mingw32 --enable-gpl --enable-version3 --disable-debug --disable-w32threads --enable-pthreads --enable-iconv --enable-libxml2 --enable-zlib --enable-libfreetype --enable-libfribidi --enable-gmp --enable-lzma --enable-fontconfig --enable-libvorbis --enable-opencl --disable-libpulse --enable-libvmaf --disable-libxcb --disable-xlib --enable-amf --enable-libaom --enable-avisynth --enable-libdav1d --enable-libdavs2 --disable-libfdk-aac --enable-ffnvcodec --enable-cuda-llvm --enable-frei0r --enable-libgme --enable-libass --enable-libbluray --enable-libmp3lame --enable-libopus --enable-librist --enable-libtheora --enable-libvpx --enable-libwebp --enable-lv2 --enable-libmfx --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenh264 --enable-libopenjpeg --enable-libopenmpt --enable-librav1e --enable-librubberband --enable-schannel --enable-sdl2 --enable-libsoxr --enable-libsrt --enable-libsvtav1 --enable-libtwolame --enable-libuavs3d --disable-libdrm --disable-vaapi --enable-libvidstab --enable-vulkan --enable-libshaderc --enable-libplacebo --enable-libx264 --enable-libx265 --enable-libxavs2 --enable-libxvid --enable-libzimg --enable-libzvbi --extra-cflags=-DLIBTWOLAME_STATIC --extra-cxxflags= --extra-ldflags=-pthread --extra-ldexeflags= --extra-libs=-lgomp --extra-version=20220311
  libavutil      57. 17.100 / 57. 17.100
  libavcodec     59. 18.100 / 59. 18.100
  libavformat    59. 16.100 / 59. 16.100
  libavdevice    59.  4.100 / 59.  4.100
  libavfilter     8. 24.100 /  8. 24.100
  libswscale      6.  4.100 /  6.  4.100
  libswresample   4.  3.100 /  4.  3.100
  libpostproc    56.  3.100 / 56.  3.100
Input #0, matroska,webm, from 'RTb295d0534191e1acb22a45bb971a12e6.mka':
  Metadata:
    encoder         : GStreamer matroskamux version 1.16.2
    creation_time   : 2022-03-23T21:20:27.000000Z
  Duration: 03:45:00.47, start: 0.291000, bitrate: 19 kb/s
  Stream #0:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)
    Metadata:
      title           : Audio
Input #1, matroska,webm, from 'RT103bfe5f4b129860f69cd8e820f3a10b.mka':
  Metadata:
    encoder         : GStreamer matroskamux version 1.16.2
    creation_time   : 2022-03-24T01:05:30.000000Z
  Duration: 02:45:03.51, start: 13502.587000, bitrate: 5 kb/s
  Stream #1:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)
    Metadata:
      title           : Audio
Stream mapping:
  Stream #0:0 (opus) -> amix
  Stream #1:0 (opus) -> adelay:default
  amix:default -> Stream #0:0 (libvorbis)
Press [q] to stop, [?] for help
Output #0, matroska, to 'combined_audio.mka':
  Metadata:
    encoder         : Lavf59.16.100
  Stream #0:0: Audio: vorbis (oV[0][0] / 0x566F), 48000 Hz, stereo, fltp
    Metadata:
      encoder         : Lavc59.18.100 libvorbis
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time231x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time184x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time189x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time223x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time275x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time245x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time213x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time209x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time208x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time204x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time199x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time193x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time185x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time181x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time178x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time177x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time176x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time169x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time167x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time163x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time146x
[libvorbis @ 00000229f8a7bbc0] Queue input is backward in time139x
size=   75141kB time=06:07:52.57 bitrate=  27.9kbits/s speed= 130x
video:0kB audio:70470kB subtitle:0kB other streams:0kB global headers:4kB muxing overhead: 6.628071%


  


  The audio files being mixed together - https://www.easyupload.io/m/durisk

  


  How can i resolve this issue ?

  


• 4 Ways to Embed User Privacy & Data Security in Your Business

  15 juillet 2022, par Erin — Privacy

  Customer analytics undeniably plays a vital role for businesses. Product improvements, interface personalisation, content improvements, and creative advertising thrive on data. 

  Yet, there’s a fine line between being a customer-centred company and a privacy-violating one. 

  Due to ubiquitous online tracking, 62% of Americans now believe that it’s impossible to go about their daily lives without companies collecting data about them. Still, despite the importance of privacy in business for consumers, companies are reluctant to act. Privacy initiatives often stay on the back burner due to perceived complexity. That’s true to some extent.

  Privacy in business does assume complex technical changes to your data management. But to be a privacy-centred organisation, you also need to re-think your processes, practices, and culture. 

  Here are four ways to start your journey to better user privacy and data security. 

  1. Revise Your Data Collection Process to Gain Consumer Trust 

  The public is wary of sharing data with businesses because they are suspicious of its subsequent usage. 

  However, not all data collection is bad or wrong. In many cases, you need specific data for service delivery, compliance, or good-natured personalisation. 

  That’s exactly what consumers expect. Almost half of US consumers say they’d trust a company that limits the amount of personal information requested and only asks for data relevant to its products/services. 

  By limiting data collection and offering transparent data usage terms, you can : 

  • Reassure reluctant users to try your product or service — hence, boost conversions and sales. 
  • Retain existing audiences by gaining their trust, which leads to loyalty and higher customer lifetime value (CLV). 

  To gain consumers’ trust, implement proper consent and opt-out mechanisms. Then create educational materials about how you are collecting and using their data.

  2. Perform Data Mapping to Determine Where Sensitive Data Rests 

  Businesses are already pressed with an expanded cyber-security radar, courtesy of remote work, digital payment processing, IoT device adoption, etc. Yet, 41% of the executives don’t think their security initiatives have kept up with the digital transformations.

  Loopholes in security eventually result in a data breach. The average cost of a data breach looms at $4.24 million globally. The sum includes regulatory fines and containment costs, plus indirect losses in the form of reduced brand equity and market share. 

  Lax data protection in business also undermines consumer trust : 87% of consumers wouldn’t transact with a company if they had qualms with its security practices. 

  To improve your security posture, analyse where you are storing sensitive consumer data, who has access to it (internally and externally), and how you are protecting it. Then work with cybersecurity specialists on implementing stronger consumer security mechanisms (e.g. auto-log offs, secure password policy, etc) and extra internal security policies (if needed). 

  At the same time, start practising data minimisation. Ensure that all collected data is : 

  • Adequate – sufficient to meet your stated objectives 
  • Relevant – is rationally linked to the objectives 
  • Limited – no unnecessary data is collected or stored
  • Timely – data is periodically reviewed and removed when unnecessary 

  

  These principles prevent data hoarding. Also, they help improve your security posture and regulatory compliance by reducing the volume of information you need to safeguard.

  3. Do an Inventory of Your Business Tools

  Data leaks and consumer privacy breaches often occur through third parties. Because Google Analytics was deemed in breach of European GDPR in France, Austria and Italy, businesses using it are vulnerable to lawsuits (which are already happening). 

  Investigate your corporate toolkit to determine “weak links” – tools with controversial privacy policies, murky data collection practices, and poor security. 

  Treat it as a journey and pick your battles. By relying on Big Tech products for years, you might have overlooked better alternatives. 

  For example :

  • Matomo is a privacy-centred Google Analytics alternative. Our web analytics is compliant with GDPR, CCPA, and other global privacy laws. Unlike Google Analytics, we don’t exploit any data you collect and provide full transparency into how and where it’s stored. Or if you want a simple analytics solution, Fathom is another great privacy-friendly option.

  

  • For online data storage, you can choose Proton Drive or Nextcloud (open-source). Or host your corporate data with a local cloud hosting provider to avoid cross-border data transfers.

  

  Aim to progressively replace Google products with more privacy-centred alternatives. 

  4. Cultivate a Privacy-Centred Corporate Culture 

  To make privacy a competitive advantage, you need every team member (at every level) to respect its importance. 

  This is a continuous process of inspiring and educating your people. Find “privacy ambassadors” who are willing to lead the conversations, educate others, and provide resources for leading the change. 

  On an operational level, incorporate privacy principles around data minimisation, bounded collection, and usage into your Code of Conduct, standard operating procedures (SOPs), and other policies. 

  Creating a privacy-centric culture takes effort, but it pays off well. Cisco estimates that for each dollar spent on privacy, an average organisation gets $2.70 in associated benefits. Almost half (47%) of organisations gain 2X returns on their privacy initiatives.

  Moving Forward with a Data Privacy Programme 

  Privacy has become a strong differentiator for brands. Consumers crave transparency and ethical data usage. Regulators mandate limited data collection and proper security mechanisms.

  But sweeping changes are hard to implement. So start small and go one step at a time. Understand which first-party data your company collects and how it is stored.

  Then look into the tools and technologies you are using for data collection. Do these provide sufficient privacy controls ? How are they using data collected on your behalf ? Finally, move to wider transformations, pertaining to data management, cybersecurity, and cultural practices. 

  Be consistent with your effort — and eventually, all the pieces will fall into place.