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• Multiple format changes in FFmpeg for thermal camera

  6 février 2023, par Greynol4

  I'm having trouble generating a command to process output from a uvc thermal camera's raw data so that it can be colorized and then output to a virtual device with the intention of streaming it over rtsp. This is on a raspberry pi 3B+ with 32bit bullseye.

  


  The original code that works perfectly for previewing it is :

  


  ffmpeg -input_format yuyv422 -video_size 256x384 -i /dev/video0 -vf 'crop=h=(ih/2):y=(ih/2)' -pix_fmt yuyv422 -f rawvideo - | ffplay -pixel_format gray16le -video_size 256x192 -f rawvideo -i - -vf 'normalize=smoothing=10, format=pix_fmts=rgb48, pseudocolor=p=inferno'


  


  Essentially what this is doing is taking the raw data, cutting the useful portion out, then piping it to ffplay where it is seen as 16bit grayscale (in this case gray16le), then it is normalized, formatted to 48 bit rgb and then a pseudocolor filter is applied.

  


  I haven't been able to get this to translate into ffmpeg-only because it throws codec errors or format errors or converts the 16bit to 10bit even though I need the 16bit. I have tried using v4l2loopback and two instances of ffmpeg in separate windows to see if I could figure out where the error was actually occuring but I suspect that is introducing more format issues that are distracting from the original problem. The closest I have been able to get is

  


  ffmpeg -input_format yuyv422 -video_size 256x384 -i /dev/video0 -vf 'crop=h=(ih/2):y=(ih/2)' -pix_fmt yuyv422 -f rawvideo /dev/video3

  


  Followed by

  


  ffmpeg -video_size 256x192 -i /dev/video3  -f rawvideo -pix_fmt gray16le -vf 'normalize=smoothing=10,format=pix_fmts=rgb48, pseudocolor=p=inferno' -f rawvideo -f v4l2 /dev/video4

  


  This results in a non colorized but somewhat useful image with certain temperatures showing as missing pixels as opposed to the command with ffplay where it shows a properly colorized stream without missing pixels.

  


  I'll include my configuration and log from the preview command but the log doesn't show errors unless I try to modify parameters and presumably mess up the syntax.

  


   ffmpeg -input_format yuyv422 -video_size 256x384 -i /dev/video0 -vf 'crop=h=(ih/2):y=(ih/2)' -pix_fmt yuyv422 -f rawvideo - | ffplay -pixel_format gray16le -video_size 256x192 -f rawvideo -i - -vf 'normalize=smoothing=10, format=pix_fmts=rgb48, pseudocolor=p=inferno'
ffplay version N-109758-gbdc76f467f Copyright (c) 2003-2023 the FFmpeg developers
  built with gcc 10 (Raspbian 10.2.1-6+rpi1)
  configuration: --prefix=/usr/local --enable-nonfree --enable-gpl --enable-hardcoded-tables --disable-ffprobe --disable-ffplay --enable-libx264 --enable-libx265 --enable-sdl --enable-sdl2 --enable-ffplay
  libavutil      57. 44.100 / 57. 44.100
  libavcodec     59. 63.100 / 59. 63.100
  libavformat    59. 38.100 / 59. 38.100
  libavdevice    59.  8.101 / 59.  8.101
  libavfilter     8. 56.100 /  8. 56.100
  libswscale      6.  8.112 /  6.  8.112
  libswresample   4.  9.100 /  4.  9.100
  libpostproc    56.  7.100 / 56.  7.100
ffmpeg version N-109758-gbdc76f467f Copyright (c) 2000-2023 the FFmpeg developers
  built with gcc 10 (Raspbian 10.2.1-6+rpi1)
  configuration: --prefix=/usr/local --enable-nonfree --enable-gpl --enable-hardcoded-tables --disable-ffprobe --disable-ffplay --enable-libx264 --enable-libx265 --enable-sdl --enable-sdl2 --enable-ffplay
  libavutil      57. 44.100 / 57. 44.100
  libavcodec     59. 63.100 / 59. 63.100
  libavformat    59. 38.100 / 59. 38.100
  libavdevice    59.  8.101 / 59.  8.101
  libavfilter     8. 56.100 /  8. 56.100
  libswscale      6.  8.112 /  6.  8.112
  libswresample   4.  9.100 /  4.  9.100
  libpostproc    56.  7.100 / 56.  7.100
Input #0, video4linux2,v4l2, from '/dev/video0':B sq=    0B f=0/0   
  Duration: N/A, start: 242.040935, bitrate: 39321 kb/s
  Stream #0:0: Video: rawvideo (YUY2 / 0x32595559), yuyv422, 256x384, 39321 kb/s, 25 fps, 25 tbr, 1000k tbn
Stream mapping:.000 fd=   0 aq=    0KB vq=    0KB sq=    0B f=0/0   
  Stream #0:0 -> #0:0 (rawvideo (native) -> rawvideo (native))
Press [q] to stop, [?] for help
Output #0, rawvideo, to 'pipe:':   0KB vq=    0KB sq=    0B f=0/0   
  Metadata:
    encoder         : Lavf59.38.100
  Stream #0:0: Video: rawvideo (YUY2 / 0x32595559), yuyv422(tv, progressive), 256x192, q=2-31, 19660 kb/s, 25 fps, 25 tbn
    Metadata:
      encoder         : Lavc59.63.100 rawvideo
frame=    0 fps=0.0 q=0.0 size=       0kB time=-577014:32:22.77 bitrate=  -0.0kbInput #0, rawvideo, from 'fd:':    0KB vq=    0KB sq=    0B f=0/0   
  Duration: N/A, start: 0.000000, bitrate: 19660 kb/s
  Stream #0:0: Video: rawvideo (Y1[0][16] / 0x10003159), gray16le, 256x192, 19660 kb/s, 25 tbr, 25 tbn
frame=   13 fps=0.0 q=-0.0 size=    1152kB time=00:00:00.52 bitrate=18148.4kbitsframe=   25 fps= 24 q=-0.0 size=    2304kB time=00:00:01.00 bitrate=18874.4kbitsframe=   39 fps= 25 q=-0.0 size=    3648kB time=00:00:01.56 bitrate=19156.7kbitsframe=   51 fps= 24 q=-0.0 size=    4800kB time=00:00:02.04 bitrate=19275.3kbitsframe=   64 fps= 24 q=-0.0 size=    6048kB time=00:00:02.56 bitrate=19353.6kbitsframe=   78 fps= 25 q=-0.0 size=    7392kB time=00:00:03.12 bitrate=19408.7kbits




  


  I'd also like to use the correct option so it isn't scrolling though every frame in the log as well as links to resources for adapting a command to a script for beginners even though that's outside the purview of this question so any direction on those would be much appreciated.

  


• A Comprehensive Guide to Robust Digital Marketing Analytics

  15 novembre 2023, par Erin — Analytics Tips

  First impressions are everything. This is not only true for dating and job interviews but also for your digital marketing strategy. Like a poorly planned job application getting tossed in the “no thank you” pile, 38% of visitors to your website will stop engaging with your content if they find the layout unpleasant. Thankfully, digital marketers can access data that can be harnessed to optimise websites and turn those “no thank you’s” into “absolutely’s.”

  So, how can we transform raw data into valuable insights that pay off ? The key is web analytics tools that can help you make sense of it all while collecting data ethically. In this article, we’ll equip you with ways to take your digital marketing strategy to the next level with the power of web analytics.

  What are the different types of digital marketing analytics ?

  Digital marketing analytics are like a cipher into the complex behaviour of your buyers. Digital marketing analytics help collect, analyse and interpret data from any touchpoint you interact with your buyers online. Whether you’re trying to gauge the effectiveness of a new email marketing campaign or improve your mobile app layout, there’s a way for you to make use of the insights you gain.

  

  As we go through the eight commonly known types of digital marketing analytics, please note we’ll primarily focus on what falls under the umbrella of web analytics. 

  1. Web analytics help you better understand how users interact with your website. Good web analytics tools will help you understand user behaviour while securely handling user data. 
  2. Learn more about the effectiveness of your organisation’s social media platforms with social media analytics. Social media analytics include user engagement, post reach and audience demographics. 
  3. Email marketing analytics help you see how email campaigns are being engaged with.
  4. Search engine optimisation (SEO) analytics help you understand your website’s visibility in search engine results pages (SERPs). 
  5. Pay-per-click (PPC) or campaign analytics measure the performance of paid advertising campaigns.
  6. Content marketing analytics focus on how your content is performing with your audience. 
  7. Customer analytics helps organisations identify and examine buyer behaviour to retain the biggest spenders. 
  8. Mobile app analytics track user interactions within mobile applications. 

  Choosing which digital marketing analytics tools are the best fit for your organisation is not an easy task. When making these decisions, it’s critical to remember the ethical implications of data collection. Although data insights can be invaluable to your organisation, they won’t be of much use if you lose the trust of your users. 

  Tips and best practices for developing robust digital marketing analytics 

  So, what separates top-notch, robust digital marketing analytics from the rest ? We’ve already touched on it, but a big part involves respecting user privacy and ethically handling data. Data security should be on your list of priorities, alongside conversion rate optimisation when developing a digital marketing strategy. In this section, we will examine best practices for using digital marketing analytics while retaining user trust.

  

  Clear objectives

  Before comparing digital marketing analytics tools, you should define clear and measurable goals. Try asking yourself what you need your digital marketing analytics strategy to accomplish. Do you want to improve conversion rates while remaining data compliant ? Maybe you’ve noticed users are not engaging with your platform and want to fix that. Save yourself time and energy by focusing on the most relevant pain points and areas of improvement.

  Choose the right tools for the job

  Don’t just base your decision on what other people tell you. Take the tool for a test drive — free trials allow you to test features and user interfaces and learn more about the platform before committing. When choosing digital marketing analytics tools, look for ones that ensure data accuracy as well as compliance with privacy laws like GDPR.

  Don’t overlook data compliance

  GDPR ensures organisations prioritise data protection and privacy. You could be fined up to €20 million, or 4% of the previous year’s revenue for violations. Without data compliance practices, you can say goodbye to the time and money spent on digital marketing strategies. 

  Don’t sacrifice data quality and accuracy

  Inaccurate and low-quality data can taint your analysis, making it hard to glean valuable insights from your digital marketing analytics efforts. Many analytics tools only show sampled data or use AI and ML to fill data gaps, potentially compromising the accuracy and completeness of your analytics. 

  When your analytics are based on incomplete or inaccurate data, it’s like trying to assemble a puzzle with missing pieces—you might get a glimpse of the whole picture, but it’s never quite clear. Accurate data isn’t just helpful—it’s the backbone of smart marketing strategies. It lets you make confident decisions and enables precise targeting for greater impact.

  Communicate your findings

  Having insights is one thing ; effectively communicating complex data findings is just as important. Customise dashboards to display key metrics aligned with your objectives. Make sure to automate reports, allowing stakeholders to stay updated without manual intervention. 

  Understand the user journey

  To optimise your conversion rates, you need to understand the user journey. Start by analysing visitors interactions with your website — this will help you identify conversion bottlenecks in your sales or lead generation processes. Implement A/B testing for landing page optimisation, refining elements like call-to-action buttons or copy, and leverage Form Analytics to make informed, data-driven improvements to your forms.

  Continuous improvement

  Learn from the data insights you gain, and iterate your marketing strategies based on the findings. Stay updated with evolving web analytics trends and technologies to leverage new growth opportunities. 

  Why you need web analytics to support your digital marketing analytics toolbox

  You wouldn’t set out on a roadtrip without a map, right ? Digital marketing analytics without insights into how users interact with your website are just as useless. Used ethically, web analytics tools can be an invaluable addition to your digital marketing analytics toolbox. 

  The data collected via web analytics reveals user interactions with your website. These could include anything from how long visitors stay on your page to their actions while browsing your website. Web analytics tools help you gather and understand this data so you can better understand buyer preferences. It’s like a domino effect : the more you understand your buyers and user behaviour, the better you can assess the effectiveness of your digital content and campaigns. 

  Web analytics reveal user behaviour, highlighting navigation patterns and drop-off points. Understanding these patterns helps you refine website layout and content, improving engagement and conversions for a seamless user experience.

  

  Concrete CMS harnessed the power of web analytics, specifically Matomo’s Form Analytics, to uncover crucial insights within their user onboarding process. Their data revealed a significant issue : the “address” input field was causing visitors to drop off and not complete the form, severely impacting the overall onboarding experience and conversion rate.

  Armed with these insights, Concrete CMS made targeted optimisations to the form, resulting in a substantial transformation. By addressing the specific issue identified through Form Analytics, they achieved an impressive outcome – a threefold increase in lead generation.

  This case is a great example of how web analytics can uncover customer needs and preferences and positively impact conversion rates. 

  Ethical implications of digital marketing analytics

  As we’ve touched on, digital marketing analytics are a powerful tool to help better understand online user behaviour. With great power comes great responsibility, however, and it’s a legal and ethical obligation for organisations to protect individual privacy rights. Let’s get into the benefits of practising ethical digital marketing analytics and the potential risks of not respecting user privacy : 

  • If someone uses your digital platform and then opens their email one day to find it filled with random targeted ad campaigns, they won’t be happy. Avoid losing user trust — and facing a potential lawsuit — by informing users what their data will be used for. Give them the option to consent to opt-in or opt-out of letting you use their personal information. If users are also assured you’ll safeguard personal information against unauthorised access, they’ll be more likely to trust you to handle their data securely.
  • Protecting data against breaches means investing in technology that will let you end-to-end encrypt and securely store data. Other important data-security best practices include access control, backing up data regularly and network and physical security of assets.

  A fine line separates digital marketing analytics and misusing user data — many companies have gotten into big trouble for crossing it. (By big trouble, we mean millions of dollars in fines.) When it comes to digital marketing analytics, you should never cut corners when it comes to user privacy and data security. This balance involves understanding what data can be collected and what should be collected and respecting user boundaries and preferences.

  

  Learn more 

  We discussed a lot of facets of digital marketing analytics, namely how to develop a robust digital marketing strategy while prioritising data compliance. With Matomo, you can protect user data and respect user privacy while gaining invaluable insights into user behaviour with 100% accurate data. Save your organisation time and money by investing in a web analytics solution that gives you the best of both worlds. 

  If you’re ready to begin using ethical and robust digital marketing analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.

• FFmpeg uses xface to merge videos without transition effects

  30 avril 2024, par soapbar

  ffmpeg -i ./first.mp4 -i ./first.mp4 -filter_complex "xfade=transition=circlecrop:duration=1:offset=4,format=yuv420p" -y output.mp4

  


  FFMPEG version 6.1.1, the video is generated normally without any error prompts, but the generated video does not have any transition effects.

  


  output

  


  
ffmpeg version 6.1.1-tessus  https://evermeet.cx/ffmpeg/  Copyright (c) 2000-2023 the FFmpeg developers
  built with Apple clang version 11.0.0 (clang-1100.0.33.17)
  configuration : —cc=/usr/bin/clang —prefix=/opt/ffmpeg —extra-version=tessus —enable-avisynth —enable-fontconfig —enable-gpl —enable-libaom —enable-libass —enable-libbluray —enable-libdav1d —enable-libfreetype —enable-libgsm —enable-libmodplug —enable-libmp3lame —enable-libmysofa —enable-libopencore-amrnb —enable-libopencore-amrwb —enable-libopenh264 —enable-libopenjpeg —enable-libopus —enable-librubberband —enable-libshine —enable-libsnappy —enable-libsoxr —enable-libspeex —enable-libtheora —enable-libtwolame —enable-libvidstab —enable-libvmaf —enable-libvo-amrwbenc —enable-libvorbis —enable-libvpx —enable-libwebp —enable-libx264 —enable-libx265 —enable-libxavs —enable-libxml2 —enable-libxvid —enable-libzimg —enable-libzmq —enable-libzvbi —enable-version3 —pkg-config-flags=—static —disable-ffplay
  libavutil      58. 29.100 / 58. 29.100
  libavcodec     60. 31.102 / 60. 31.102
  libavformat    60. 16.100 / 60. 16.100
  libavdevice    60.  3.100 / 60.  3.100
  libavfilter     9. 12.100 /  9. 12.100
  libswscale      7.  5.100 /  7.  5.100
  libswresample   4. 12.100 /  4. 12.100
  libpostproc    57.  3.100 / 57.  3.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from './first.mp4' :
  Metadata :
    major_brand : isom
    minor_version : 512
    compatible_brands : isomiso2avc1mp41
    encoder : Lavf61.1.100
  Duration : 00:00:05.00, start : 0.000000, bitrate : 110 kb/s
  Stream #0:0[0x1](und) : Video : h264 (High) (avc1 / 0x31637661), yuv420p(progressive), 1080x1920 [SAR 4095:4096 DAR 36855:65536], 109 kb/s, SAR 14317:14320 DAR 128853:229120, 0.20 fps, 0.20 tbr, 16384 tbn (default)
    Metadata :
      handler_name : VideoHandler
      vendor_id : [0][0][0][0]
      encoder : Lavc61.3.100 libx264
Input #1, mov,mp4,m4a,3gp,3g2,mj2, from './first.mp4' :
  Metadata :
    major_brand : isom
    minor_version : 512
    compatible_brands : isomiso2avc1mp41
    encoder : Lavf61.1.100
  Duration : 00:00:05.00, start : 0.000000, bitrate : 110 kb/s
  Stream #1:0[0x1](und) : Video : h264 (High) (avc1 / 0x31637661), yuv420p(progressive), 1080x1920 [SAR 4095:4096 DAR 36855:65536], 109 kb/s, SAR 14317:14320 DAR 128853:229120, 0.20 fps, 0.20 tbr, 16384 tbn (default)
    Metadata :
      handler_name : VideoHandler
      vendor_id : [0][0][0][0]
      encoder : Lavc61.3.100 libx264
Stream mapping :
  Stream #0:0 (h264) -> xfade
  Stream #1:0 (h264) -> xfade
  format:default -> Stream #0:0 (libx264)
Press [q] to stop, [?] for help
[libx264 @ 0x7f9f99fc87c0] using SAR=4095/4096
[libx264 @ 0x7f9f99fc87c0] using cpu capabilities : MMX2 SSE2Fast SSSE3 SSE4.2
[libx264 @ 0x7f9f99fc87c0] profile High, level 4.0, 4:2:0, 8-bit
[libx264 @ 0x7f9f99fc87c0] 264 - core 164 r3172 c1c9931 - H.264/MPEG-4 AVC codec - Copyleft 2003-2023 - 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=1 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 'output.mp4' :
  Metadata :
    major_brand : isom
    minor_version : 512
    compatible_brands : isomiso2avc1mp41
    encoder : Lavf60.16.100
  Stream #0:0 : Video : h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1080x1920 [SAR 14317:14320 DAR 128853:229120], q=2-31, 0.20 fps, 16384 tbn
    Metadata :
      encoder : Lavc60.31.102 libx264
    Side data :
      cpb : bitrate max/min/avg : 0/0/0 buffer size : 0 vbv_delay : N/A
[out#0/mp4 @ 0x7f9f99fc74c0] video:72kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead : 1.190217%
frame=    2 fps=0.0 q=-1.0 Lsize=      73kB time=00:00:05.00 bitrate= 118.9kbits/s speed=45.5x    
[libx264 @ 0x7f9f99fc87c0] frame I:1     Avg QP:12.25  size : 72527
[libx264 @ 0x7f9f99fc87c0] frame P:1     Avg QP:13.77  size :   216
[libx264 @ 0x7f9f99fc87c0] mb I  I16..4 : 51.4% 34.9% 13.8%
[libx264 @ 0x7f9f99fc87c0] mb P  I16..4 :  0.0%  0.0%  0.0%  P16..4 :  0.8%  0.0%  0.0%  0.0%  0.0%    skip:99.2%
[libx264 @ 0x7f9f99fc87c0] 8x8 transform intra:34.9% inter:0.0%
[libx264 @ 0x7f9f99fc87c0] coded y,uvDC,uvAC intra : 9.2% 9.6% 6.9% inter : 0.0% 0.6% 0.0%
[libx264 @ 0x7f9f99fc87c0] i16 v,h,dc,p : 79% 20%  2%  0%
[libx264 @ 0x7f9f99fc87c0] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu :  1% 97%  2%  0%  0%  0%  0%  0%  0%
[libx264 @ 0x7f9f99fc87c0] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu : 36% 32% 10%  3%  3%  3%  4%  3%  4%
[libx264 @ 0x7f9f99fc87c0] i8c dc,h,v,p : 80% 15%  4%  0%
[libx264 @ 0x7f9f99fc87c0] Weighted P-Frames : Y:0.0% UV:0.0%
[libx264 @ 0x7f9f99fc87c0] kb/s:58.19