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• How to get frames from HDR video in scRGB color space ?

  5 mars 2018, par Виталий Синявский

  I want to create a simple video player that will show HDR video on HDR TV. For example, this "LG Chess HDR" video. It is encoded with HEVC, its bit depth is 10 bit, pixel format is YUV420P10LE and it has metadata abount BT2020 color space and PQ transfer function.

  In this NVIDIA article I found the next :

  The display driver takes the scRGB back buffer, and converts it to the
  standard expected by the display presently connected. In general, this
  means converting the color space from sRGB primaries to BT. 2020
  primaries, scaling to an appropriate level, and encoding with a
  mechanism like PQ. Also, possibly performing conversions like RGB to
  YCC if that display connection requires it.

  It means that my player should render pixels in the scRGB color space (linear encoding, sRGB primaries, full range is -0.5 through just less than +7.5). So I need to get frames from the source video in this color space somehow, preferably in FP16 pixel format (half float, 16 bits per one color channel). I come to the following simple pipeline to render videos to HDR :

  source HDR video in BT2020 color space with applied PQ -> [some video library] -> 
  
  -> video frames with colors in scRGB color space -> [my program] ->
  
  -> rendered video on HDR TV with applied conversions by display driver

  I’m trying to use FFmpeg as this library and do not understand how to get frames from the source HDR video in scRGB color space.

  I use sws_scale FFmpeg method now to get frames and know about filters API. But I did not found any information and help about how to transparantly get frames in scRGB using these functionality without parsing metadata for all source videos and create custom video filters for them.

  Please, tell me what I can do to get frames in the scRGB color space using FFmpeg. Can someone tell other libraries with which I can do it ?

• (osx) ffmpeg combining mp3 and png to mp4 resulting in mp4 with no audio

  18 juin 2016, par Ian H

  I’m writing a python script that uses unix commands to do some file conversions/renderings. I’m trying to join some mp3 files with png files to get mp4s that are the picture with the mp3 playing over them. However, I’ve tried this with lots of different codecs and settings, and the output mp4 video never seems to have audio in it. I’ve looked at any answer to any question even related to ffmpeg and haven’t found a solution.

  Some commands I’m trying to get working currently :

  ffmpeg -loop 1 -i slide_shot%d.png -i %s -c:v libx264 -pix_fmt yuv420p 
  
  -s 720x540 -t %.3f -c:a aac -b:a 192k -shortest out%d.mp4" 
  
  % (i, aud, slideTime, i)
  
  
  
  ffmpeg -loop 1 -i slide_shot%d.png -i %s -shortest -t %.3f -write_xing 
  
  0 -c:v libx264 -c:a libmp3lame -pix_fmt yuv420p -tune stillimage out%d.mp4" 
  
  % (i, aud, slideTime, i)
  
  
  
  ffmpeg -loop 1 -i slide_shot%d.png -i %s -shortest -t %.3f -write_xing 
  
  0 -c:v libx264 -c:a copy -pix_fmt yuv420p -tune stillimage out%d.mp4" 
  
  % (i, aud, slideTime, i)

  I’m currently using the third one. However, none of them are giving me any audio. For reference, i is a loop iterator for naming consistency, aud is the audio filepath, and slideTime is the number of seconds the video should take.

  Using this command, I’m currently getting this output in the Terminal :

  ffmpeg version 3.0.2 Copyright (c) 2000-2016 the FFmpeg developers
  
  built with Apple LLVM version 7.0.2 (clang-700.1.81)
  
  configuration: --prefix=/usr/local/Cellar/ffmpeg/3.0.2 --enable-shared    
  
  --enable-pthreads --enable-gpl --enable-version3 --enable-hardcoded-
  
  tables --enable-avresample --cc=clang --host-cflags= --host-ldflags= --
  
  enable-opencl --enable-libx264 --enable-libmp3lame --enable-libxvid --
  
  enable-vda
  
  libavutil      55. 17.103 / 55. 17.103
  
  libavcodec     57. 24.102 / 57. 24.102
  
  libavformat    57. 25.100 / 57. 25.100
  
  libavdevice    57.  0.101 / 57.  0.101
  
  libavfilter     6. 31.100 /  6. 31.100
  
  libavresample   3.  0.  0 /  3.  0.  0
  
  libswscale      4.  0.100 /  4.  0.100
  
  libswresample   2.  0.101 /  2.  0.101
  
  libpostproc    54.  0.100 / 54.  0.100
  
  Input #0, png_pipe, from 'slide_shot16.png':
  
  Duration: N/A, bitrate: N/A
  
  Stream #0:0: Video: png, rgba(pc), 720x540, 25 fps, 25 tbr, 25 tbn, 25     
  
  tbc
  
  [mp3 @ 0x7fe4f1817e00] Skipping 0 bytes of junk at 0.
  
  [mp3 @ 0x7fe4f1817e00] Estimating duration from bitrate, this may be inaccurate
  
  Input #1, mp3, from 'pres_projects/Cytokine sepsis 13/data/a24x43.mp3':
  
  Duration: 00:02:04.11, start: 0.000000, bitrate: 23 kb/s
  
  Stream #1:0: Audio: mp3, 22050 Hz, mono, s16p, 24 kb/s
  
  [libx264 @ 0x7fe4f1808000] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX
  
  [libx264 @ 0x7fe4f1808000] profile High, level 3.0
  
  [libx264 @ 0x7fe4f1808000] 264 - core 148 r2668 fd2c324 - H.264/MPEG-4 AVC codec - Copyleft 2003-2016 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:-3:-3 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=2.00:0.70 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-4 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=1:1.20
  
  Output #0, mp4, to 'out16.mp4':
  
  Metadata:
  
  encoder         : Lavf57.25.100
  
  Stream #0:0: Video: h264 (libx264) ([33][0][0][0] / 0x0021), yuv420p, 720x540, q=-1--1, 25 fps, 12800 tbn, 25 tbc
  
  Metadata:
  
    encoder         : Lavc57.24.102 libx264
  
  Side data:
  
    unknown side data type 10 (24 bytes)
  
  Stream #0:1: Audio: mp3 (i[0][0][0] / 0x0069), 22050 Hz, mono, 24 kb/s
  
  Stream mapping:
  
  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))
  
  Stream #1:0 -> #0:1 (copy)
  
  Press [q] to stop, [?] for help
  
  frame=  132 fps=0.0 q=28.0 size=40kB time=00:00:02.96 bitrate=111.8kbits/
  
  frame=  272 fps=271 q=28.0 size=      61kB time=00:00:08.56 bitrate=  58.2kbits/
  
  frame=  404 fps=269 q=28.0 size=     113kB time=00:00:13.84 bitrate=  66.6kbits/
  
  frame=  537 fps=268 q=28.0 size=     132kB time=00:00:19.16 bitrate=  56.2kbits/
  
  frame=  672 fps=268 q=28.0 size=     184kB time=00:00:24.56 bitrate=  61.3kbits/
  
  frame=  808 fps=268 q=28.0 size=     236kB time=00:00:30.00 bitrate=  64.5kbits/
  
  frame=  943 fps=268 q=28.0 size=     255kB time=00:00:35.40 bitrate=  59.1kbits/
  
  frame= 1087 fps=271 q=28.0 size=     309kB time=00:00:41.16 bitrate=  61.5kbits/
  
  frame= 1219 fps=270 q=28.0 size=     328kB time=00:00:46.44 bitrate=  57.8kbits/
  
  frame= 1355 fps=270 q=28.0 size=     380kB time=00:00:51.88 bitrate=  60.0kbits/frame= 1494 fps=271 q=28.0 size=     400kB time=00:00:57.44 bitrate=  57.1kbits/
  
  frame= 1632 fps=271 q=28.0 size=     453kB time=00:01:02.96 bitrate=  58.9kbits/
  
  frame= 1767 fps=271 q=28.0 size=     472kB time=00:01:08.36 bitrate=  56.6kbits/
  
  frame= 1893 fps=269 q=28.0 size=     523kB time=00:01:13.40 bitrate=  58.4kbits/
  
  frame= 2020 fps=268 q=28.0 size=     541kB time=00:01:18.48 bitrate=  56.5kbits/
  
  frame= 2147 fps=267 q=28.0 size=     592kB time=00:01:23.56 bitrate=  58.1kbits/
  
  frame= 2275 fps=267 q=28.0 size=     611kB time=00:01:28.68 bitrate=  56.4kbits/
  
  frame= 2401 fps=266 q=28.0 size=     661kB time=00:01:33.72 bitrate=  57.8kbits/
  
  frame= 2528 fps=265 q=28.0 size=     680kB time=00:01:38.80 bitrate=  56.4kbits/
  
  frame= 2654 fps=264 q=28.0 size=     731kB time=00:01:43.84 bitrate=  57.6kbits/
  
  frame= 2781 fps=264 q=28.0 size=     749kB time=00:01:48.92 bitrate=  56.3kbits/
  
  frame= 2906 fps=263 q=28.0 size=     799kB time=00:01:53.92 bitrate=  57.5kbits/
  
  frame= 3033 fps=263 q=28.0 size=     818kB time=00:01:59.00 bitrate=  56.3kbits/
  
  frame= 3102 fps=261 q=-1.0 Lsize=     983kB time=00:02:04.08 bitrate=  64.9kbits/s speed=10.5x    
  
  video:505kB audio:364kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 13.169518%
  
  [libx264 @ 0x7fe4f1808000] frame I:13    Avg QP:14.07  size: 33159
  
  [libx264 @ 0x7fe4f1808000] frame P:782   Avg QP: 6.24  size:    36
  
  [libx264 @ 0x7fe4f1808000] frame B:2307  Avg QP: 9.67  size:    25
  
  [libx264 @ 0x7fe4f1808000] consecutive B-frames:  0.8%  0.0%  0.0% 9 9.2%
  
  [libx264 @ 0x7fe4f1808000] mb I  I16..4: 44.1% 26.2% 29.6%
  
  [libx264 @ 0x7fe4f1808000] mb P  I16..4:  0.0%  0.0%  0.0%  P16..4:  0.0%  0.0%  0.0%  0.0%  0.0%    skip:100.0%
  
  [libx264 @ 0x7fe4f1808000] mb B  I16..4:  0.0%  0.0%  0.0%  B16..8:  0.1%  0.0%  0.0%  direct: 0.0%  skip:99.9%  L0:40.4% L1:59.6% BI: 0.0%
  
  [libx264 @ 0x7fe4f1808000] 8x8 transform intra:26.1% inter:77.7%
  
  [libx264 @ 0x7fe4f1808000] coded y,uvDC,uvAC intra: 23.8% 9.6% 8.1% inter: 0.0% 0.0% 0.0%
  
  [libx264 @ 0x7fe4f1808000] i16 v,h,dc,p: 60% 33%  7%  0%
  
  [libx264 @ 0x7fe4f1808000] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 57% 12% 29%  0%  0%  0%  0%  0%  2%
  
  [libx264 @ 0x7fe4f1808000] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 36% 29% 14%  2%  3%  4%  4%  3%  4%
  
  [libx264 @ 0x7fe4f1808000] i8c dc,h,v,p: 74% 21%  5%  0%
  
  [libx264 @ 0x7fe4f1808000] Weighted P-Frames: Y:0.0% UV:0.0%
  
  [libx264 @ 0x7fe4f1808000] ref P L0: 95.4%  1.1%  3.5%
  
  [libx264 @ 0x7fe4f1808000] ref B L0:  8.5% 90.2%  1.3%
  
  [libx264 @ 0x7fe4f1808000] kb/s:33.31

  Has anyone ran into a similar problem, and if so, how did you go about fixing it ? Thanks in advance for looking at my question.

• Measuring success for your SEO content

  20 mars 2020, par Jake Thornton — Uncategorized
  With over a billion searches every day in search engines, it’s hard to underestimate the importance of having your business present on page one (ideally in positions 1 – 3) ranking for the keywords that impact your sales and conversions.

  "In 2019, Google received nearly 2.3 trillion searches and on page one alone, the first five organic results accounted for 67.60% of all the clicks."

  So how is your business performing when it comes to ranking in the crucial top three spots of search for your most important keywords ?

  Accurately measuring the success of your content

  Once you’ve done your keyword research, created compelling content, optimised it to be search-friendly, and hit ‘publish’, you then need to accurately measure the success of your efforts.

  4 tips for measuring the success of your SEO content

  1. Create a custom segment for "Visitors from Search Engines only"

  By creating this custom segment, you’ll be able to analyse the behavioural patterns of the visitors who found your website through a search engine. 

  This way you can use many of Matomo’s powerful features (Visitors, Behaviour, Acquisition, Ecommerce, Goals etc.) focused entirely on search engine visitors only.

  

  Once you’ve created this segment, you can begin to see key metrics like which entry pages are responsible for referring visitors to your website. For example : Visit Behaviour – Entry Pages, this is a great way to analyse your most effective SEO pages.You may be surprised at what pages currently bring in the most traffic.

  As well as discovering which content resonates with your search audience, you will also be able to create more content focused on your targeted audience. Do this by learning which locations your search visitors are from, which device they use, what time of the day they visited your website and much more.

  >> Learn more about creating custom segments

  2. Website visits, time on site, pages per session, and bounce rate.

  “The top four ranking factors are website visits, time on site, pages per session, and bounce rate.”

  These four metrics set the benchmark for your SEO success.

  First, you need to get as many of the ‘right’ users to see your content. If you feel you’ve exhausted channels such as social media, email and possibly paid posts ; think about who your ideal audience is. Where are they likely to hang out online ? Are there community groups or forum sites that are interested in what you’re writing about ? 

  Whatever the case, putting yourself out there and getting more traffic to your website will help show search engines that people are interested in your website. As a result, they’ll likely rank you higher for that.

  When we say getting more of the ‘right’ users, we mean users who are generally interested in the topic/subject you’re writing about and interested in the work you do. 

  

  This is important for the next three metrics – increasing users time on your website, increasing the amount of pages your users explore on your website, and reducing the overall bounce rate for users who leave your website in a matter of seconds.

  To evaluate these metrics, go to Behaviour – Pages in your Matomo and see how these metrics vary on previous posts or pages you’ve created. Which pages are already showing you the best results ? Why do they get the results ? Can you focus on creating more content like this ?

  Understanding what content is resonating with your users through these metrics is easy and is the starting point for measuring the success of your SEO content strategy.

  >> Learn more about the Behaviour feature

  3. Row Evolution

  The Row Evolution feature embedded within the Search Engine Keywords Performance plugin lets you see how your ranking positions have changed over time for your important keywords. It also lets you see how the incoming traffic, related to your keywords, has changed over time.

  

  This is valuable when measuring the changes you’ve made to your landing pages to see if it has a positive or negative effect on your ranking efforts. 

  This also lets you see how search engine algorithm changes affect your search rankings over time, and to see if the effects of these algorithm updates are temporary or long lasting.

  Row evolution allows you to report on keyword performance with ease. If you only check your insights once a week or once a fortnight, you’ll see how ranking positions for your important keywords have changed daily (or even weekly, monthly or yearly however you prefer.)

  >> Learn more about Row Evolution

  4. What results are you getting from the lesser known search engines ?

  "In 2019 (to date), Google accounted for just over 75% of all global desktop search traffic, followed by Bing at 9.97%, Baidu at 9.34%, and Yahoo at 2.77%."

  For most of us, we want to be ranking in the top three spots in Google Search because that’s where the majority of search users are. However, don’t shy away from opportunities you could be missing with lesser known search engines.

  If you sell a product aimed at 55-65 year olds who use a PC computer, chances are they are using Bing. If you have customers in China the majority will be using Baidu, or in our case at Matomo, many of our loyal users use a privacy-friendly search engine like DuckDuckGo or Qwant.

  Some of your ideal customers might be finding you through these alternative search engines, so be sure to measure the impact that these referrals may have on your conversions.

  

  Strategically including important keywords that impact your business

  While search is an important acquisition channel for most businesses, it’s also one of the most competitive.

  We recommend analysing your keyword and content performance regularly and alter content that isn’t performing as well as you’d like. You need to continually learn from the content that is successful, and focus on creating more content like this. 

  The final thing to remember with search keyword performance is to be patient. If you have had little success in the past with attracting customers through search, it can take time to build this reputation with search engines.