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• FFmpeg recording works on one laptop but not the other

  30 novembre 2019, par Jason T

  The following command :

  ffmpeg -f dshow -framerate 30 -video_size 640x480 -i video="HD Pro Webcam C920" out.mp4​

  works on one laptop (with C920 LogiTech camera) (Im calling it GOOD LAPTOP). It outputs a recorded video. But it will fail on another laptop (called BAD LAPTOP) and by fail on another I mean - it doesnt output a video (see below for output).

  The suggestions are to change parameters based on the specific error that occur on BAD LAPTOP. I have tried many different suggestions but they dont seem to work. Furthermore, they dont provide much insight into the underlying cause of the problem.

  Ive used the same camera on both laptops. Im using static windows binaries downloaded from FFmpeg web-site (veranoe). Please note the versions used below were different but that doesnt appear to matter.

  Trying to diagnose. Anyone have an idea of where the problem may lie. It seems to indicate a problem at the level of the system / camera setup.

  Please note that I’ve updated BAD LAPTOP but still no dice. Also please note that Ive tried this on several systems already and it seems to run ok (i.e., produce an output video)

  BAD LAPTOP :

  $ ffmpeg -y -f dshow -framerate 30 -video_size 640x480 -t 10 -i video="HD Pro Webcam C920" out.mp4
  
  ffmpeg version git-2019-11-26-59d264b Copyright (c) 2000-2019 the FFmpeg developers
  
    built with gcc 9.2.1 (GCC) 20191125
  
    configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libdav1d --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-libxvid --enable-libaom --enable-libmfx --enable-ffnvcodec --enable-cuvid --enable-d3d11va --enable-nvenc --enable-nvdec --enable-dxva2 --enable-avisynth --enable-libopenmpt --enable-amf
  
    libavutil      56. 36.100 / 56. 36.100
  
    libavcodec     58. 62.100 / 58. 62.100
  
    libavformat    58. 35.100 / 58. 35.100
  
    libavdevice    58.  9.101 / 58.  9.101
  
    libavfilter     7. 67.100 /  7. 67.100
  
    libswscale      5.  6.100 /  5.  6.100
  
    libswresample   3.  6.100 /  3.  6.100
  
    libpostproc    55.  6.100 / 55.  6.100
  
  Input #0, dshow, from 'video=HD Pro Webcam C920':
  
    Duration: N/A, bitrate: N/A
  
      Stream #0:0: Video: rawvideo (YUY2 / 0x32595559), yuyv422, 640x480, 30 fps, 30 tbr, 10000k tbn, 10000k tbc
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (rawvideo (native) -> h264 (libx264))
  
  Press [q] to stop, [?] for help
  
  video=HD Pro Webcam C920: I/O error
  
  [libx264 @ 06cb7a00] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2
  
  [libx264 @ 06cb7a00] profile High 4:2:2, level 3.0, 4:2:2, 8-bit
  
  [libx264 @ 06cb7a00] 264 - core 158 - H.264/MPEG-4 AVC codec - Copyleft 2003-2019 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=12 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
  
  Output #0, mp4, to 'out.mp4':
  
    Metadata:
  
      encoder         : Lavf58.35.100
  
      Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuv422p, 640x480, q=-1--1, 30 fps, 10000k tbn, 30 tbc
  
      Metadata:
  
        encoder         : Lavc58.62.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A
  
  frame=    0 fps=0.0 q=0.0 Lsize=       0kB time=00:00:00.00 bitrate=N/A speed=   0x
  
  video:0kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown

  GOOD LAPTOP :
  ​

  $ ffmpeg -y -f dshow -framerate 30 -video_size 640x480 -t 10 -i video="Logitech HD Pro Webcam C920" out.mp4   
  
  ffmpeg version N-92780-gbb586a9703 Copyright (c) 2000-2018 the FFmpeg developers                              
  
    built with gcc 8.2.1 (GCC) 20181201                                                                         
  
    configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-fontconfig --enable-gnutls --enable-ico
  
  nv --enable-libass --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --en
  
  able-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-lib
  
  soxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx
  
  264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvi
  
  dstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-libxvid --enabl
  
  e-libaom --enable-libmfx --enable-amf --enable-ffnvcodec --enable-cuvid --enable-d3d11va --enable-nvenc --enab
  
  le-nvdec --enable-dxva2 --enable-avisynth --enable-libopenmpt                                                 
  
    libavutil      56. 25.100 / 56. 25.100                                                                      
  
    libavcodec     58. 42.104 / 58. 42.104                                                                      
  
    libavformat    58. 25.100 / 58. 25.100                                                                      
  
    libavdevice    58.  6.101 / 58.  6.101                                                                      
  
    libavfilter     7. 46.101 /  7. 46.101                                                                      
  
    libswscale      5.  4.100 /  5.  4.100                                                                      
  
    libswresample   3.  4.100 /  3.  4.100                                                                      
  
    libpostproc    55.  4.100 / 55.  4.100                                                                      
  
  Input #0, dshow, from 'video=Logitech HD Pro Webcam C920':                                                    
  
    Duration: N/A, start: 35609.500000, bitrate: N/A                                                            
  
      Stream #0:0: Video: mjpeg (Baseline) (MJPG / 0x47504A4D), yuvj422p(pc, bt470bg/unknown/unknown), 640x480, 
  
  30 fps, 30 tbr, 10000k tbn, 10000k tbc                                                                        
  
  Stream mapping:                                                                                               
  
    Stream #0:0 -> #0:0 (mjpeg (native) -> h264 (libx264))                                                      
  
  Press [q] to stop, [?] for help                                                                               
  
  [libx264 @ 000001ec0b750100] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2            
  
  [libx264 @ 000001ec0b750100] profile High 4:2:2, level 3.0, 4:2:2, 8-bit                                      
  
  [libx264 @ 000001ec0b750100] 264 - core 157 r2935 545de2f - H.264/MPEG-4 AVC codec - Copyleft 2003-2018 - http
  
  ://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 ps
  
  y_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma
  
  _qp_offset=-2 threads=12 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 con
  
  strained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 k
  
  eyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 
  
  qpstep=4 ip_ratio=1.40 aq=1:1.00                                                                              
  
  Output #0, mp4, to 'out.mp4':                                                                                 
  
    Metadata:                                                                                                   
  
      encoder         : Lavf58.25.100                                                                           
  
      Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuvj422p(pc), 640x480, q=-1--1, 30 fps, 10000k tbn
  
  , 30 tbc                                                                                                      
  
      Metadata:                                                                                                 
  
        encoder         : Lavc58.42.104 libx264                                                                 
  
      Side data:                                                                                                
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1                                            
  
  frame=   62 fps= 31 q=29.0 size=       0kB time=00:00:00.10 bitrate=   3.8kbits/s dup=1 drop=0 speed=0.0495x  
  
  frame=   77 fps= 30 q=29.0 size=       0kB time=00:00:00.60 bitrate=   0.6kbits/s dup=1 drop=0 speed=0.237x   
  
  frame=   92 fps= 30 q=29.0 size=       0kB time=00:00:01.09 bitrate=   0.3kbits/s dup=1 drop=0 speed=0.363x   
  
  frame=  107 fps= 30 q=29.0 size=       0kB time=00:00:01.59 bitrate=   0.2kbits/s dup=1 drop=0 speed=0.453x   
  
  frame=  168 fps= 30 q=29.0 size=     256kB time=00:00:03.63 bitrate= 577.3kbits/s dup=1 drop=0 speed=0.654x   
  
  frame=  183 fps= 30 q=29.0 size=     256kB time=00:00:04.13 bitrate= 507.5kbits/s dup=1 drop=0 speed=0.683x   
  
  frame=  198 fps= 30 q=29.0 size=     256kB time=00:00:04.63 bitrate= 452.7kbits/s dup=1 drop=0 speed=0.706x   
  
  frame=  213 fps= 30 q=29.0 size=     512kB time=00:00:05.13 bitrate= 817.1kbits/s dup=1 drop=0 speed=0.727x   
  
  frame=  228 fps= 30 q=29.0 size=     512kB time=00:00:05.63 bitrate= 744.6kbits/s dup=1 drop=0 speed=0.744x   
  
  frame=  243 fps= 30 q=29.0 size=     512kB time=00:00:06.13 bitrate= 683.9kbits/s dup=1 drop=0 speed=0.759x   
  
  frame=  259 fps= 30 q=29.0 size=     512kB time=00:00:06.66 bitrate= 629.2kbits/s dup=1 drop=0 speed=0.777x   
  
  frame=  274 fps= 30 q=29.0 size=     512kB time=00:00:07.16 bitrate= 585.3kbits/s dup=1 drop=0 speed=0.789x   
  
  frame=  289 fps= 30 q=29.0 size=     512kB time=00:00:07.66 bitrate= 547.1kbits/s dup=1 drop=0 speed=0.799x   
  
  frame=  301 fps= 30 q=-1.0 Lsize=     973kB time=00:00:09.93 bitrate= 802.7kbits/s dup=1 drop=0 speed=0.975x  
  
  
  
  video:969kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.445649%            
  
  [libx264 @ 000001ec0b750100] frame I:4     Avg QP:24.23  size: 13237                                          
  
  [libx264 @ 000001ec0b750100] frame P:77    Avg QP:24.67  size:  7807                                          
  
  [libx264 @ 000001ec0b750100] frame B:220   Avg QP:26.09  size:  1534                                          
  
  [libx264 @ 000001ec0b750100] consecutive B-frames:  2.3%  0.7%  0.0% 97.0%                                    
  
  [libx264 @ 000001ec0b750100] mb I  I16..4: 19.6% 70.5%  9.9%                                                  
  
  [libx264 @ 000001ec0b750100] mb P  I16..4:  3.6%  3.3%  0.3%  P16..4: 54.9% 11.7%  9.5%  0.0%  0.0%    skip:16
  
  .8%                                                                                                           
  
  [libx264 @ 000001ec0b750100] mb B  I16..4:  0.1%  0.2%  0.0%  B16..8: 28.2%  1.1%  0.2%  direct: 7.9%  skip:62
  
  .2%  L0:51.0% L1:45.9% BI: 3.1%                                                                               
  
  [libx264 @ 000001ec0b750100] 8x8 transform intra:56.1% inter:69.3%                                            
  
  [libx264 @ 000001ec0b750100] coded y,uvDC,uvAC intra: 35.2% 85.0% 30.8% inter: 9.3% 38.8% 1.5%                
  
  [libx264 @ 000001ec0b750100] i16 v,h,dc,p: 32% 34%  8% 27%                                                    
  
  [libx264 @ 000001ec0b750100] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 33% 18% 28%  2%  3%  5%  3%  5%  3%               
  
  [libx264 @ 000001ec0b750100] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 40% 19%  8%  3%  6% 11%  4%  6%  3%               
  
  [libx264 @ 000001ec0b750100] i8c dc,h,v,p: 48% 16% 31%  5%                                                    
  
  [libx264 @ 000001ec0b750100] Weighted P-Frames: Y:3.9% UV:1.3%                                                
  
  [libx264 @ 000001ec0b750100] ref P L0: 39.0%  6.6% 38.0% 16.3%  0.1%                                          
  
  [libx264 @ 000001ec0b750100] ref B L0: 61.8% 30.3%  7.9%                                                      
  
  [libx264 @ 000001ec0b750100] ref B L1: 84.4% 15.6%                                                            
  
  [libx264 @ 000001ec0b750100] kb/s:790.62                 

• Data Privacy in Business : A Risk Leading to Major Opportunities

  9 août 2022, par Erin — Privacy

  Data privacy in business is a contentious issue. 

  Claims that “big data is the new oil of the digital economy” and strong links between “data-driven personalisation and customer experience” encourage leaders to set up massive data collection programmes.

  However, many of these conversations downplay the magnitude of security, compliance and ethical risks companies face when betting too much on customer data collection. 

  In this post, we discuss the double-edged nature of privacy issues in business — the risk-ridden and the opportunity-driven. ​​

  3 Major Risks of Ignoring Data Privacy in Business

  As the old adage goes : Just because everyone else is doing it doesn’t make it right.

  Easy data accessibility and ubiquity of analytics tools make data consumer collection and processing sound like a “given”. But the decision to do so opens your business to a spectrum of risks. 

  1. Compliance and Legal Risks 

  Data collection and customer privacy are protected by a host of international laws including GDPR, CCPA, and regional regulations. Only 15% of countries (mostly developing ones) don’t have dedicated laws for protecting consumer privacy. 

  

  Global legislature includes provisions on : 

  • Collectible data types
  • Allowed uses of obtained data 
  • Consent to data collection and online tracking 
  • Rights to request data removal 

  Personally identifiable information (PII) processing is prohibited or strictly regulated in most jurisdictions. Yet businesses repeatedly circumnavigate existing rules and break them on occasion.

  In Australia, for example, only 2% of brands use logos, icons or messages to transparently call out online tracking, data sharing or other specific uses of data at the sign-up stage. In Europe, around half of small businesses are still not fully GDPR-compliant — and Big Tech companies like Google, Amazon and Facebook can’t get a grip on their data collection practices even when pressed with horrendous fines. 

  Although the media mostly reports on compliance fines for “big names”, smaller businesses are increasingly receiving more scrutiny. 

  As Max Schrems, an Austrian privacy activist and founder of noyb NGO, explained in a Matomo webinar :

  “In Austria, my home country, there are a lot of €5,000 fines going out there as well [to smaller businesses]. Most of the time, they are just not reported. They just happen below the surface. [GDPR fines] are already a reality.”​

  In April 2022, the EU Court of Justice ruled that consumer groups can autonomously sue businesses for breaches of data protection — and nonprofit organisations like noyb enable more people to do so. 

  Finally, new data privacy legislation is underway across the globe. In the US, Colorado, Connecticut, Virginia and Utah have data protection acts at different stages of approval. South African authorities are working on the Protection of Personal Information Act (POPI) act and Brazil is working on a local General Data Protection Law (LGPD).

  Re-thinking your stance on user privacy and data protection now can significantly reduce the compliance burden in the future. 

  2. Security Risks 

  Data collection also mandates data protection for businesses. Yet, many organisations focus on the former and forget about the latter. 

  Lenient attitudes to consumer data protection resulted in a major spike in data breaches.

  Check Point research found that cyberattacks increased 50% year-over-year, with each organisation facing 925 cyberattacks per week globally.

  Many of these attacks end up being successful due to poor data security in place. As a result, billions of stolen consumer records become publicly available or get sold on dark web marketplaces.

  What’s even more troublesome is that stolen consumer records are often purchased by marketing firms or companies, specialising in spam campaigns. Buyers can also use stolen emails to distribute malware, stage phishing and other social engineering attacks – and harvest even more data for sale. 

  One business’s negligence creates a snowball effect of negative changes down the line with customers carrying the brunt of it all. 

  In 2020, hackers successfully targeted a Finnish psychotherapy practice. They managed to steal hundreds of patient records — and then demanded a ransom both from the firm and its patients for not exposing information about their mental health issues. Many patients refused to pay hackers and some 300 records ended up being posted online as Associated Press reported.

  Not only did the practice have to deal with the cyber-breach aftermath, but it also faced vocal regulatory and patient criticisms for failing to properly protect such sensitive information.

  Security negligence can carry both direct (heavy data breach fines) and indirect losses in the form of reputational damages. An overwhelming 90% of consumers say they wouldn’t buy from a business if it doesn’t adequately protect their data. This brings us to the last point. 

  3. Reputational Risks 

  Trust is the new currency. Data negligence and consumer privacy violations are the two fastest ways to lose it. 

  Globally, consumers are concerned about how businesses collect, use, and protect their data. 

  

  • According to Forrester, 47% of UK adults actively limit the amount of data they share with websites and apps. 49% of Italians express willingness to ask companies to delete their personal data. 36% of Germans use privacy and security tools to minimise online tracking of their activities. 
  • A GDMA survey also notes that globally, 82% of consumers want more control over their personal information, shared with companies. 77% also expect brands to be transparent about how their data is collected and used. 

  When businesses fail to hold their end of the bargain — collect just the right amount of data and use it with integrity — consumers are fast to cut ties. 

  Once the information about privacy violations becomes public, companies lose : 

  • Brand equity 
  • Market share 
  • Competitive positioning 

  An AON report estimates that post-data breach companies can lose as much as 25% of their initial value. In some cases, the losses can be even higher. 

  In 2015, British telecom TalkTalk suffered from a major data breach. Over 150,000 customer records were stolen by hackers. To contain the issue, TalkTalk had to throw between $60-$70 million into containment efforts. Still, they lost over 100,000 customers in a matter of months and one-third of their company value, equivalent to $1.4 billion, by the end of the year. 

  Fresher data from Infosys gives the following maximum cost estimates of brand damage, companies could experience after a data breach (accidental or malicious).

  

  3 Major Advantages of Privacy in Business 

  Despite all the industry mishaps, a reassuring 77% of CEOs now recognise that their companies must fundamentally change their approaches to customer engagement, in particular when it comes to ensuring data privacy. 

  Many organisations take proactive steps to cultivate a privacy-centred culture and implement transparent data collection policies. 

  Here’s why gaining the “privacy advantage” pays off.

  1. Market Competitiveness 

  There’s a reason why privacy-focused companies are booming. 

  Consumers’ mounting concerns and frustrations over the lack of online privacy, prompt many to look for alternative privacy-centred products and services. 

  The following B2C and B2B products are moving from the industry margins to the mainstream : 

  • Private search engines (Duckduckgo)
  • Password managers (1password, Dashlane)
  • Online identity networks (id.me)
  • Web analytics solutions (Matomo) 
  • And secure messaging apps (Signal) among others 

  Across the board, consumers express greater trust towards companies, protective of their privacy : 

  

  And as we well know : trust translates to higher engagement, loyalty, and – ultimately revenue. 

  By embedding privacy into the core of your product, you give users more reasons to select, stay and support your business. 

  2. Higher Operational Efficiency

  Customer data protection isn’t just a policy – it’s a culture of collecting “just enough” data, protecting it and using it responsibly. 

  Sadly, that’s the area where most organisations trail behind. At present, some 90% of businesses admit to having amassed massive data silos. 

  Siloed data is expensive to maintain and operationalise. Moreover, when left unattended, it can evolve into a pressing compliance issue. 

  A recently leaked document from Facebook says the company has no idea where all of its first-party, third-party and sensitive categories data goes or how it is processed. Because of this, Facebook struggles to achieve GDPR compliance and remains under regulatory pressure. 

  Similarly, Google Analytics is riddled with privacy issues. Other company products were found to be collecting and operationalising consumer data without users’ knowledge or consent. Again, this creates valid grounds for regulatory investigations. 

  Smaller companies have a better chance of making things right at the onset. 

  By curbing customer data collection, you can : 

  • Reduce data hosting and Cloud computation costs (aka trim your Cloud bill) 
  • Improve data security practices (since you would have fewer assets to protect) 
  • Make your staff more productive by consolidating essential data and making it easy and safe to access

  Privacy-mindful companies also have an easier time when it comes to compliance and can meet new data regulations faster. 

  3. Better Marketing Campaigns 

  The biggest counter-argument to reducing customer data collection is marketing. 

  How can we effectively sell our products if we know nothing about our customers ? – your team might be asking. 

  This might sound counterintuitive, but minimising data collection and usage can lead to better marketing outcomes. 

  Limiting the types of data that can be used encourages your people to become more creative and productive by focusing on fewer metrics that are more important.

  Think of it this way : Every other business uses the same targeting parameters on Facebook or Google for running paid ad campaigns on Facebook. As a result, we see ads everywhere — and people grow unresponsive to them or choose to limit exposure by using ad blocking software, private browsers and VPNs. Your ad budgets get wasted on chasing mirage metrics instead of actual prospects. 

  Case in point : In 2017 Marc Pritchard of Procter & Gamble decided to first cut the company’s digital advertising budget by 6% (or $200 million). Unilever made an even bolder move and reduced its ad budget by 30% in 2018. 

  Guess what happened ?

  P&G saw a 7.5% increase in organic sales and Unilever had a 3.8% gain as HBR reports. So how come both companies became more successful by spending less on advertising ? 

  They found that overexposure to online ads led to diminishing returns and annoyances among loyal customers. By minimising ad exposure and adopting alternative marketing strategies, the two companies managed to market better to new and existing customers. 

  The takeaway : There are more ways to engage consumers aside from pestering them with repetitive retargeting messages or creepy personalisation. 

  You can collect first-party data with consent to incrementally improve your product — and educate them on the benefits of your solution in transparent terms.

  Final Thoughts 

  The definitive advantage of privacy is consumers’ trust. 

  You can’t buy it, you can’t fake it, you can only cultivate it by aligning your external appearances with internal practices. 

  Because when you fail to address privacy internally, your mishaps will quickly become apparent either as social media call-outs or worse — as a security incident, a data breach or a legal investigation. 

  By choosing to treat consumer data with respect, you build an extra layer of protection around your business, plus draw in some banging benefits too. 

  Get one step closer to becoming a privacy-centred company by choosing Matomo as your web analytics solution. We offer robust privacy controls for ensuring ethical, compliant, privacy-friendly and secure website tracking. 

• [ffmpeg][asyncio] main process is held by ffmpeg command

  5 octobre 2024, par Michael Lopez

  I created a python program for handling my Arlo Camera. To do that I have been using the pyaarlo library (https://github.com/twrecked/pyaarlo) to catch camera's events.
The goal is to monitor if there is an active stream on cameras, get the RTSP stream url and reStream it to a HLS playlist for local usage.

  


  Here the python code :

  


  import asyncio
from decouple import config
import logging
from my_pyaarlo import PyArlo
import urllib.parse
from queue import Queue
import signal

# Read config from ENV (unchanged)
ARLO_USER = config('ARLO_USER')
ARLO_PASS = config('ARLO_PASS')
IMAP_HOST = config('IMAP_HOST')
IMAP_USER = config('IMAP_USER')
IMAP_PASS = config('IMAP_PASS')
DEBUG = config('DEBUG', default=False, cast=bool)
PYAARLO_BACKEND = config('PYAARLO_BACKEND', default=None)
PYAARLO_REFRESH_DEVICES = config('PYAARLO_REFRESH_DEVICES', default=0, cast=int)
PYAARLO_STREAM_TIMEOUT = config('PYAARLO_STREAM_TIMEOUT', default=0, cast=int)
PYAARLO_STORAGE_DIR = config('PYAARLO_STORAGE_DIR', default=None)
PYAARLO_ECDH_CURVE = config('PYAARLO_ECDH_CURVE', default=None)

# Initialize logging
logging.basicConfig(
    level=logging.DEBUG if DEBUG else logging.INFO,
    format='%(asctime)s [%(levelname)s] %(name)s: %(message)s'
)
logger = logging.getLogger(__name__)

ffmpeg_processes = {}
event_queue = Queue()
shutdown_event = asyncio.Event()

async def handle_idle_event(camera):
    logger.info(f"Idle event detected for camera: {camera.name}")
    await stop_ffmpeg_stream(camera.name)

async def get_stream_url(camera):
    try:
        # Attempt to get the stream URL
        stream_url = await asyncio.to_thread(camera.get_stream()
        if stream_url:
            return stream_url
        else:
            logger.warning(f"Unable to get stream URL for {camera.name}. Stream might not be active.")
            return None
    except Exception as e:
        logger.error(f"Error getting stream URL for {camera.name}: {e}")
        return None

async def handle_user_stream_active_event(camera):
    logger.info(f"User stream active event detected for camera: {camera.name}")

    # Get the stream URL
    stream_url = await get_stream_url(camera)
    if stream_url:
        logger.info(f"Stream URL for {camera.name}: {stream_url}")
        await start_ffmpeg_stream(camera.name, stream_url)
    else:
        logger.warning(f"No stream URL available for {camera.name}")

async def event_handler(device, attr, value):
    logger.debug(f"Event: {device.name}, Attribute: {attr}, Value: {value}")
    if attr == 'activityState':
        if value == 'idle':
            await handle_idle_event(device)
        elif value in ['userStreamActive']:
            await handle_user_stream_active_event(device)
    elif attr == 'mediaUploadNotification':
        logger.info(f"Media uploaded for camera: {device.name}")

def sync_event_handler(device, attr, value):
    # This function will be called by PyArlo's synchronous callbacks
    event_queue.put((device, attr, value))

async def process_event_queue():
    while not shutdown_event.is_set():
        try:
            if not event_queue.empty():
                device, attr, value = event_queue.get()
                await event_handler(device, attr, value)
            await asyncio.sleep(0.1)  # Small delay to prevent busy-waiting
        except asyncio.CancelledError:
            break
        except Exception as e:
            logger.error(f"Error processing event: {e}")

async def display_status(arlo):
    while not shutdown_event.is_set():
        print("\n--- Camera Statuses ---")
        for camera in arlo.cameras:
            print(f"{camera.name}: {camera.state}")
        print("------------------------")
        await asyncio.sleep(5)

async def start_ffmpeg_stream(camera_name, stream_url):
    if camera_name not in ffmpeg_processes:
        output_hls = f"/tmp/{camera_name}.m3u8"

        try:
            new_url = urllib.parse.quote(stream_url.encode(), safe=':/?&=')
            logger.info(f"NEW_URL: {new_url}")

            ffmpeg_cmd = [
                "ffmpeg", "-hide_banner", "-loglevel", "quiet", "-nostats", "-nostdin", "-y", "-re",
                "-i", new_url,
                "-c:v", "libx264", "-preset", "veryfast",
                "-an", "-sn",
                "-f", "hls", "-hls_time", "4", "-hls_list_size", "10",
                "-hls_flags", "delete_segments", output_hls,
            ]
            logger.info(f"Starting FFmpeg command: {ffmpeg_cmd}")
            
            process = await asyncio.create_subprocess_exec(
                *ffmpeg_cmd,
                stdout=asyncio.subprocess.DEVNULL,
                stderr=asyncio.subprocess.DEVNULL
            )
            ffmpeg_processes[camera_name] = process
            logger.info(f"Started ffmpeg process with PID: {process.pid}")

        except Exception as e:
            logger.error(f"Error starting FFmpeg for {camera_name}: {e}")

async def stop_ffmpeg_stream(camera_name):
    logger.info(f"Stopping ffmpeg process for {camera_name}")
    ffmpeg_process = ffmpeg_processes.pop(camera_name, None)
    if ffmpeg_process:
        ffmpeg_process.terminate()

        try:
            await ffmpeg_process.wait()
            logger.info(f"{camera_name} stopped successfully")
        except Exception as e:
            print(f"FFMPEG Process didn't stop in time, forcefully terminating: {e}")
            ffmpeg_process.kill()
    else:
        logger.info(f"FFmpeg process for {camera_name} already stopped")

async def shutdown(signal, loop):
    logger.info(f"Received exit signal {signal.name}...")
    shutdown_event.set()
    tasks = [t for t in asyncio.all_tasks() if t is not asyncio.current_task()]
    [task.cancel() for task in tasks]
    logger.info(f"Cancelling {len(tasks)} outstanding tasks")
    await asyncio.gather(*tasks, return_exceptions=True)
    loop.stop()

async def main():
    # Initialize PyArlo
    arlo_args = {
        'username': ARLO_USER,
        'password': ARLO_PASS,
        'tfa_source': 'imap',
        'tfa_type': 'email',
        'tfa_host': IMAP_HOST,
        'tfa_username': IMAP_USER,
        'tfa_password': IMAP_PASS,
        'save_session': True,
        'verbose_debug': DEBUG
    }

    # Add optional arguments
    for arg, value in [
        ('refresh_devices_every', PYAARLO_REFRESH_DEVICES),
        ('stream_timeout', PYAARLO_STREAM_TIMEOUT),
        ('backend', PYAARLO_BACKEND),
        ('storage_dir', PYAARLO_STORAGE_DIR),
        ('ecdh_curve', PYAARLO_ECDH_CURVE)
    ]:
        if value:
            arlo_args[arg] = value
    
    try:
        arlo = await asyncio.to_thread(PyArlo, **arlo_args)
    except Exception as e:
        logger.error(f"Failed to initialize PyArlo: {e}")
        return

    logger.info("Connected to Arlo. Monitoring events...")

    # Register event handlers for each camera
    for camera in arlo.cameras:
        camera.add_attr_callback('*', sync_event_handler)

    # Start the status display task
    status_task = asyncio.create_task(display_status(arlo))

    # Start the event processing task
    event_processing_task = asyncio.create_task(process_event_queue())

    # Set up signal handlers
    loop = asyncio.get_running_loop()
    for s in (signal.SIGHUP, signal.SIGTERM, signal.SIGINT):
        loop.add_signal_handler(
            s, lambda s=s: asyncio.create_task(shutdown(s, loop)))

    try:
        # Keep the main coroutine running
        while not shutdown_event.is_set():
            try:
                await asyncio.sleep(1)
            except asyncio.CancelledError:
                break
    except Exception as e:
        logger.error(f"Unexpected error in main loop: {e}")
    finally:
        logger.info("Shutting down...")
        for camera_name in list(ffmpeg_processes.keys()):
            await stop_ffmpeg_stream(camera_name)
        
        # Cancel and wait for all tasks
        tasks = [status_task, event_processing_task]
        for task in tasks:
            if not task.done():
                task.cancel()
        await asyncio.gather(*tasks, return_exceptions=True)
        
        logger.info("Program terminated.")

if __name__ == "__main__":
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        logger.info("Keyboard interrupt received. Exiting.")
    except Exception as e:
        logger.error(f"Unhandled exception: {e}")
    finally:
        logger.info("Program exit complete.")


  


  My issue is about the ffmpeg command which is hold the main process (or the event loop) when it runs, blocking the events coming from the pyaarlo library. The state of the camera continues to work with the good information.

  


  I tried lot of things, without asyncio, with multiprocessing, with subprocess, ... the behavior is always the same. In some cases, I received the idle event after the key interrupt.

  


  Another information :

  


  

  • When I stop the active stream, the event is not received but when I start the stream just after, that event is received.

  


  • When I run the same ffmpeg command but with a local long video file, everything is Ok. So, it why I guess that the ffmpeg command is impacting the main process.

  


  


  I succedeed in running the ffmpeg command with rtsp url stream but without a loop event monitoring :

  


  import asyncio
import signal
import sys
import os

async def run_infinite_command():
    # Start a simple HTTP server as our "infinite" command
    url = "rstp://localhost:8554/camera1/stream" # it is a fake url
    ffmpeg_cmd = [
        "ffmpeg", "-re", "-i", url,
        "-c:v", "libx264", "-preset", "veryfast",
        "-c:a", "copy",
        "-f", "hls", "-hls_time", "4", "-hls_list_size", "10",
        "-hls_flags", "delete_segments", "/tmp/output.m3u8"
    ]
    
    process = await asyncio.create_subprocess_exec(
        *ffmpeg_cmd,
        stdout=asyncio.subprocess.DEVNULL,
        stderr=asyncio.subprocess.DEVNULL
    )
    
    print(f"Started HTTP server with PID: {process.pid}")
    return process

async def main():
    # Start the infinite command
    process = await run_infinite_command()

    # Run the main loop for a few seconds
    for i in range(10):
        print(f"Main loop iteration {i+1}")
        await asyncio.sleep(1)

    # Stop the infinite command
    print("Stopping the HTTP server...")
    if sys.platform == "win32":
        # On Windows, we need to use CTRL_C_EVENT
        os.kill(process.pid, signal.CTRL_C_EVENT)
    else:
        # On Unix-like systems, we can use SIGTERM
        process.send_signal(signal.SIGTERM)

    # Wait for the process to finish
    try:
        await asyncio.wait_for(process.wait(), timeout=5.0)
        print("HTTP server stopped successfully")
    except asyncio.TimeoutError:
        print("HTTP server didn't stop in time, forcefully terminating")
        process.kill()

    print("Program finished")

if __name__ == "__main__":
    asyncio.run(main())


  


  With this script, the ffmpeg command is correctly launched and terminated after the for loop.

  


  Could you help ?