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• How to convert wav audio file to aac in python ?

  2 juin 2021, par yaya49

  I have a project about audio compression, I've been working with pydub I am using the function export() to write and save the file it works perfectly fine from aac to wav but doesn't the other way around it gives me this error : (From what I understood, ffmpeg doesn't support the aac format for this function )

  


  Encoding failed. ffmpeg/avlib returned error code : 1

  


  Command:['ffmpeg', '-y', '-f', 'wav', '-i', '/var/folders/n1/x3tb_rg17pdgss5jb_zr7v380000gn/T/tmp7rv9zmjx', '-f', 'm4a', '/var/folders/n1/x3tb_rg17pdgss5jb_zr7v380000gn/T/tmpco06cpgo']


  


  Output from ffmpeg/avlib :

  


  ffmpeg version 4.3.1 Copyright (c) 2000-2020 the FFmpeg developers
  built with Apple clang version 12.0.0 (clang-1200.0.32.27)
  configuration: --prefix=/usr/local/Cellar/ffmpeg/4.3.1_4 --enable-shared --enable-pthreads --enable-version3 --enable-avresample --cc=clang --host-cflags= --host-ldflags= --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libbluray --enable-libdav1d --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-librtmp --enable-libspeex --enable-libsoxr --enable-videotoolbox --disable-libjack --disable-indev=jack
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
  libpostproc    55.  7.100 / 55.  7.100
Guessed Channel Layout for Input Stream #0.0 : stereo
Input #0, wav, from '/var/folders/n1/x3tb_rg17pdgss5jb_zr7v380000gn/T/tmp7rv9zmjx':
  Duration: 00:00:01.82, bitrate: 1411 kb/s
    Stream #0:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 44100 Hz, stereo, s16, 1411 kb/s
[NULL @ 0x7fbbb7008200] Requested output format 'm4a' is not a suitable output format
/var/folders/n1/x3tb_rg17pdgss5jb_zr7v380000gn/T/tmpco06cpgo: Invalid argument


  


• What is PII ? Your introduction to personally identifiable information

  15 janvier 2020, par Joselyn Khor — Analytics Tips, Privacy, Security
  Most websites you visit collect information about you via tools like Google Analytics and Matomo – sometimes collecting personally identifiable information (PII).

  When it comes to PII, people are becoming more concerned about data privacy. Identifiable information can be used for illegal purposes like identity theft and fraud. 

  So how can you protect yourself as an innocent internet browser ? In the case of website owners – how do you protect users and your company from falling prey to privacy breaches ?

  

  As one of the most trusted analytics companies, we feel our readers would benefit from being as informed as possible about data privacy issues and PII. Learn what it means, and what you can do to keep yours or others’ information safe.

  Table of Contents

  What does PII stand for ?

  PII acronym

  PII is an acronym for personally identifiable information.

  PII definition

  Personally identifiable information (PII) is a term used predominantly in the United States.

  The appendix of OMB M-10-23 (Guidance for Agency Use of Third-Party Website and Applications) gives this definition for PII :

  “The term ‘personally identifiable information’ refers to information which can be used to distinguish or trace an individual’s identity, such as their name, social security number, biometric records, etc. alone, or when combined with other personal or identifying information which is linked or linkable to a specific individual, such as date and place of birth, mother’s maiden name, etc.”

  What can be considered personally identifiable information (PII) ? Some PII examples :

  • Full name/usernames
  • Home address/mailing address
  • Email address
  • Credit card numbers
  • Date of birth
  • Phone numbers
  • Login details

  • Precise locations
  • Account numbers
  • Passwords
  • Security codes (including biometric records)
  • Personal identification numbers
  • Driver license number
  • Get a more comprehensive list here

  What’s non-PII ?

  Anonymous information, or information that can’t be traced back to an individual, can be considered non-PII.

  Who is affected by the exploitation of PII ?

  Anyone can be affected by the exploitation of personal data, where you have identity theft, account fraud and account takeovers. When websites resort to illegally selling or sharing your data and compromising your privacy, the fear is falling victim to such fraudulent activity. 

  PII can also be an issue when employees have access to the database and the data is not encrypted. For example, anyone working in a bank can access your accounts ; anyone working at Facebook may be able to read your messages. This shows how privacy breaches can easily happen when employees have access to PII.

  Website owner’s responsibility for data privacy (PII and analytics)

  To respect your website visitor’s privacy, best practice is to avoid collecting PII whenever possible. If you work in an industry which requires people to disclose personal information (e.g. healthcare, security industries, public sector), then you must ensure this data is collected and handled securely. 

  

  The US National Institute of Standards and Technology states : “The likelihood of harm caused by a breach involving PII is greatly reduced if an organisation minimises the amount of PII it uses, collects, and stores. For example, an organisation should only request PII in a new form if the PII is absolutely necessary.” 

  How you’re held accountable remains up to the privacy laws of the country you’re doing business in. Make sure you are fully aware of the privacy and data protection laws that relate specifically to you. 

  To reduce the risk of privacy breaches, try collecting as little PII as you can ; purging it as soon as you can ; and making sure your IT security is updated and protected against security threats. 

  If you’re using data collection tools like web analytics, data may be tracked through features like User ID, custom variables, and custom dimensions. Sometimes they are also harder to identify when they are present, for example, in page URLs, page titles, or referrers URLs. So make sure you’re optimising your web analytics tools’ settings to ensure you’re asking your users for consent and respecting users’ privacy.

  If you’re using a GDPR compliant tool like Matomo, learn how you can stop processing such personal data

  PII, GDPR and businesses in the US/EU

  Because PII is broad, you may run into confusion when considering PII and GDPR (which applies in the EU). The General Data Protection Regulation (GDPR) provides more safeguards for user privacy.

  GDPR grants people in the EU more rights concerning their “personal data” (more on PII vs personal data below). In the EU the GDPR restricts the collection and processing of personal data. The repercussions are severe penalties and fines for privacy infringements. Businesses are required to handle this personal data carefully. You can be fined up to 4% of their yearly revenue for data breaches or non-compliance. 

  

  Although there isn’t an overarching data protection law in the US, there are hundreds of laws on both the federal and state levels to protect the personal data of US residents. US Congress has also enacted industry-specific statutes related to data privacy, and the state of California passed the California Consumer Privacy Act. 

  To be on the safe side, if you are using analytics, follow matters relating to “personal data” in the GDPR. It’s all-encompassing when it comes to protecting user privacy. GDPR rules still apply whenever an EU citizen visits any non EU site (that processes personal data).

  Personally identifiable information (PII) vs personal data

  PII and “personal data” aren’t used interchangeably. All personal data can be PII, but not all PII can be defined as personal data.

  The definition of “personal data” according to the GDPR :

  

  This means “personal data” encompasses a greater number of identifiers which include the online sphere. Examples include : IP addresses and URL names. As well as seemingly “innocent” data like height, job position, company etc. 

  What’s considered personal data depends on the context. If a piece of information can be combined with others to establish someone’s identity then that can be considered personal data. 

  Under GDPR, when processing personal data, you need explicit consent. You need to ensure you’re compliant according to GDPR definitions of “personal data” not just what’s considered “PII”.

  How Matomo deals with PII and personal data

  Although Matomo Analytics is a web analytics software that tracks user activity on your website, we take privacy and PII very seriously – on both our Cloud and On-Premise offerings. 

  If you’re using Matomo and would like to know how you can be fully GDPR compliant and protect user privacy, read more :
  

  • Learn how to not process any personally identifiable information – Anonymise IP addresses, user IDs, and order IDs
  • Matomo protects user privacy by talking the talk and walking the walk
  • Stay ahead of the GDPR with a privacy-respecting analytics platform
  • 11 ways Matomo helps you protect your visitor’s privacy

  Disclaimer

  We are not lawyers and don’t claim to be. The information provided here is to help give an introduction to issues you may encounter when dealing with PII. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns. 

  Additional resources :

  • https://www.consumeraffairs.com/finance/identity-theft-statistics.html#identity-theft-trends-in-2019
  • https://ec.europa.eu/info/law/law-topic/data-protection_en
  • https://iclg.com/practice-areas/data-protection-laws-and-regulations/usa
  • https://www.csoonline.com/article/3215864/how-to-protect-personally-identifiable-information-pii-under-gdpr.html
  • https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/key-definitions/what-is-personal-data/

• FFMPEG Error while processing the decoded data for stream #0:1

  2 décembre 2020, par Michael Joseph Aubry

  When using the FFMPEG command in my Lambda function I am getting this issue (version 4.2.1). When using it on my local machine it works fine (4.3.1).

  


  Lambda Version Info

  


  {
  data: 'ffmpeg version 4.2.1-static https://johnvansickle.com/ffmpeg/  Copyright (c) 2000-2019 the FFmpeg developers\n' +
    'built with gcc 6.3.0 (Debian 6.3.0-18+deb9u1) 20170516\n' +
    'configuration: --enable-gpl --enable-version3 --enable-static --disable-debug --disable-ffplay --disable-indev=sndio --disable-outdev=sndio --cc=gcc-6 --enable-fontconfig --enable-frei0r --enable-gnutls --enable-gmp --enable-libgme --enable-gray --enable-libaom --enable-libfribidi --enable-libass --enable-libvmaf --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-librubberband --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libvorbis --enable-libopus --enable-libtheora --enable-libvidstab --enable-libvo-amrwbenc --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libdav1d --enable-libxvid --enable-libzvbi --enable-libzimg\n' +
    'libavutil      56. 31.100 / 56. 31.100\n' +
    'libavcodec     58. 54.100 / 58. 54.100\n' +
    'libavformat    58. 29.100 / 58. 29.100\n' +
    'libavdevice    58.  8.100 / 58.  8.100\n' +
    'libavfilter     7. 57.100 /  7. 57.100\n' +
    'libswscale      5.  5.100 /  5.  5.100\n' +
    'libswresample   3.  5.100 /  3.  5.100\n' +
    'libpostproc    55.  5.100 / 55.  5.100\n'
}


  


  Macbook Pro Version Info

  


  {
  data: 'ffmpeg version 4.3.1 Copyright (c) 2000-2020 the FFmpeg developers
built with Apple clang version 11.0.0 (clang-1100.0.33.17)
configuration: --prefix=/usr/local/Cellar/ffmpeg/4.3.1 --enable-shared --enable-pthreads --enable-version3 --enable-avresample --cc=clang --host-cflags= --host-ldflags= --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libbluray --enable-libdav1d --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable- 
  libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable- 
  libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable- 
  librtmp --enable-libspeex --enable-libsoxr --enable-videotoolbox --disable-libjack --disable- 
  indev=jack
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
  libpostproc    55.  7.100 / 55.  7.100'
}


  


  My goal with this command is to generate a thumbnail sprite sheet.

  


  ffmpeg \
  -threads 8 \
  -ignore_editlist 1 \
  -i URL \
  -f image2 \
  -vf "select='not(mod(n,25))',setpts='N/(25*TB)',scale=180:180,tile=5x25" \  
  -pix_fmt yuvj420p \
  -an \
  -qscale:v 28 \
  -vsync 0 \
  -preset veryfast \
  pipe:1


  


  The same error occurs when I have a .jpg output on disk i.e /tmp/test.jpg

  


  This is the exact log from cloudwatch

  


  {&#xA;    "errorType": "Error",&#xA;    "errorMessage": "ffmpeg exited with code 1: Error reinitializing filters!\nFailed to inject frame into filter network: Invalid argument\nError while processing the decoded data for stream #0:1\nConversion failed!\n",&#xA;    "stack": [&#xA;        "Error: ffmpeg exited with code 1: Error reinitializing filters!",&#xA;        "Failed to inject frame into filter network: Invalid argument",&#xA;        "Error while processing the decoded data for stream #0:1",&#xA;        "Conversion failed!",&#xA;        "",&#xA;        "    at ChildProcess.<anonymous> (/var/task/node_modules/fluent-ffmpeg/lib/processor.js:182:22)",&#xA;        "    at ChildProcess.emit (events.js:314:20)",&#xA;        "    at ChildProcess.EventEmitter.emit (domain.js:483:12)",&#xA;        "    at Process.ChildProcess._handle.onexit (internal/child_process.js:275:12)"&#xA;    ]&#xA;}&#xA;</anonymous>

  


  Here is the raw command using fluent-ffmpeg inside node.js

  


      const passThrough = new stream.PassThrough();
    const fps = 25;
    const sWidth = 720 / 4;
    const sHeight = 1920 / 4;

    ffmpeg(s3Url)
      .setFfmpegPath("/opt/ffmpeg")
      .inputOptions([`-threads`, "8", "-ignore_editlist", "1"])
      .outputOptions([
        "-f",
        "image2",
        "-vf",
        `"select='not(mod(n,${fps}))',setpts='N/(${fps}*TB)',scale=${sWidth}:${sHeight},tile=5x25"`,
        "-pix_fmt",
        "yuvj420p",
        "-an",
        "-qscale:v",
        "28",
        "-vsync",
        "0",
        "-preset",
        "veryfast"
      ])
      .output(passThrough)
      .on("start", (cmdline) => console.log(cmdline))
      .on("progress", (progress) => {
        console.log(progress);
      })
      .on("error", (err) => {
        console.log(err);
        reject(err);
      })
      .run();


  


  Additional log from cloudwatch

  


  2020-12-02T18:42:55.023Z    2f334838-f748-4f2e-a639-15df0686ab4b    INFO    Error: ffmpeg exited with code 1: Error reinitializing filters!Failed to inject frame into filter network: Invalid argumentError while processing the decoded data for stream #0:1Conversion failed!    at ChildProcess.<anonymous> (/var/task/node_modules/fluent-ffmpeg/lib/processor.js:182:22)    at ChildProcess.emit (events.js:314:20)    at ChildProcess.EventEmitter.emit (domain.js:483:12)    at Process.ChildProcess._handle.onexit (internal/child_process.js:275:12)&#xA;</anonymous>