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• Screen capture (video screencast) with FFMPEG with very low FPS

  20 septembre 2023, par jesusda

  I recently changed PCs, I went from having an Intel Core i5 4460 with integrated graphics card to a Xeon E5 2678 v3 with AMD RADEON RX 550 graphics.

  


  On paper, the new PC is on the order of 3 to 7 times more powerful than the old one and I can attest that this is the case in daily use, video and image editing etc. The advantage of having so many cores and threads available is palpable. In terms of games I haven't tried it because I'm not really a gamer and the few games I use are the typical free ones that come with Debian and some emulators that, honestly, already worked fine with the old PC.

  


  However there is one task that brings me head over heels for its terrible performance : video screen capture.

  


  With my old PC I was able to capture at over 60 fps at full screen while doing any task I needed to record.

  


  Even with my lenovo thinkpad x230 I am able to capture screen at over 80fps with total fluency.

  


  The command I have always used is :

  


  ffmpeg  -f x11grab -draw_mouse 1 -framerate 60 -video_size 1920x1200 -i :0.0+1680,0  -qscale 0 -pix_fmt yuv420p -c:v libx264 -preset medium -qp 0 -q:v 1 -s 1920x1200 -f matroska -threads 4 video.mkv


  


  notes :

  


  -video_size 1920x1200 -i :0.0+1680,0 y -s 1920x1200 are the dimensions and position of the region to capture (my right monitor).

  


  Notice that I even used -preset medium and software encoding, so I got very good quality even with that parameter setting and without ever going below 60 fps.

  


  What happens to me now ?

  


  The equipment is unable to capture more than 20 fps which makes any video invalid, with frame drops and not even reach 30fps, which would be the minimum required.

  


  In addition, it is quite noticeable the decrease in responsiveness of the PC as soon as I launch the command. That is, all that fluidity and smoothness that is appreciated when working normally, disappears and even moving a window from one side to another is rough and stumbling.

  


  I have tried with different parameters of ffmpeg, to capture raw, without encoding.

  


  I have tried saving the resulting video directly to RAM disk in order to avoid the possible bottleneck of writing to disk. It doesn't affect it at all.

  


  So, does anyone have any suggestions as to at least where I can dig further to find a solution to the problem ?

  


  Additional data, in case it helps :

  


  $ → inxi
CPU: 12-Core Intel Xeon E5-2678 v3 (-MT MCP-)
speed/min/max: 1201/1200/3300 MHz Kernel: 5.10.0-0.bpo.4-amd64 x86_64
Up: 1d 6h 55m Mem: 6427.6/32012.4 MiB (20.1%)
Storage: 13.76 TiB (55.9% used) Procs: 433 Shell: bash 5.0.18 inxi: 3.0.32


$ → ffmpeg -v
ffmpeg version 4.1.6 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 8 (Debian 8.3.0-6)
  configuration: --disable-decoder=amrnb --disable-decoder=libopenjpeg --disable-libopencv --disable-outdev=sdl2 --disable-podpages --disable-sndio --disable-stripping --enable-libaom --enable-avfilter --enable-avresample --enable-gcrypt --disable-gnutls --enable-openssl --enable-gpl --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libfdk-aac --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libilbc --enable-libkvazaar --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenh264 --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvo-amrwbenc --enable-libvorbis --enable-libvpx --enable-libx265 --enable-libzimg --enable-libxvid --enable-libzvbi --enable-nonfree --enable-opencl --enable-opengl --enable-postproc --enable-pthreads --enable-shared --enable-version3 --enable-libwebp --incdir=/usr/include/x86_64-linux-gnu --libdir=/usr/lib/x86_64-linux-gnu --prefix=/usr --toolchain=hardened --enable-frei0r --enable-chromaprint --enable-libx264 --enable-libiec61883 --enable-libdc1394 --enable-vaapi --enable-libmfx --enable-libvmaf --disable-altivec --shlibdir=/usr/lib/x86_64-linux-gnu
  libavutil      56. 22.100 / 56. 22.100
  libavcodec     58. 35.100 / 58. 35.100
  libavformat    58. 20.100 / 58. 20.100
  libavdevice    58.  5.100 / 58.  5.100
  libavfilter     7. 40.101 /  7. 40.101
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  3.100 /  5.  3.100
  libswresample   3.  3.100 /  3.  3.100
  libpostproc    55.  3.100 / 55.  3.100


  


  I have the free amdgpu drivers (not amdgpu-pro), but I activated OpenCL just in case.

  


  I followed this tutorial.

  


  $ → glxinfo | grep OpenGL
OpenGL vendor string: AMD
OpenGL renderer string: Radeon RX550/550 Series (POLARIS12, DRM 3.40.0, 5.10.0-0.bpo.4-amd64, LLVM 11.0.1)
OpenGL core profile version string: 4.6 (Core Profile) Mesa 20.3.4
OpenGL core profile shading language version string: 4.60
OpenGL core profile context flags: (none)
OpenGL core profile profile mask: core profile
OpenGL core profile extensions:
OpenGL version string: 4.6 (Compatibility Profile) Mesa 20.3.4
OpenGL shading language version string: 4.60
OpenGL context flags: (none)
OpenGL profile mask: compatibility profile
OpenGL extensions:
OpenGL ES profile version string: OpenGL ES 3.2 Mesa 20.3.4
OpenGL ES profile shading language version string: OpenGL ES GLSL ES 3.20
OpenGL ES profile extensions:





$ → clinfo
Number of platforms                               1
  Platform Name                                   Clover
  Platform Vendor                                 Mesa
  Platform Version                                OpenCL 1.1 Mesa 20.3.4
  Platform Profile                                FULL_PROFILE
  Platform Extensions                             cl_khr_icd
  Platform Extensions function suffix             MESA

  Platform Name                                   Clover
Number of devices                                 1
  Device Name                                     Radeon RX550/550 Series (POLARIS12, DRM 3.40.0, 5.10.0-0.bpo.4-amd64, LLVM 11.0.1)
  Device Vendor                                   AMD
  Device Vendor ID                                0x1002
  Device Version                                  OpenCL 1.1 Mesa 20.3.4
  Driver Version                                  20.3.4
  Device OpenCL C Version                         OpenCL C 1.1
  Device Type                                     GPU
  Device Profile                                  FULL_PROFILE
  Device Available                                Yes
  Compiler Available                              Yes
  Max compute units                               8
  Max clock frequency                             1183MHz
  Max work item dimensions                        3
  Max work item sizes                             256x256x256
  Max work group size                             256
  Preferred work group size multiple              64
  Preferred / native vector sizes
    char                                                16 / 16
    short                                                8 / 8
    int                                                  4 / 4
    long                                                 2 / 2
    half                                                 0 / 0        (n/a)
    float                                                4 / 4
    double                                               2 / 2        (cl_khr_fp64)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     No
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 No
    Round to infinity                             No
    IEEE754-2008 fused multiply-add               No
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  No
  Double-precision Floating-point support         (cl_khr_fp64)
    Denormals                                     Yes
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
  Address bits                                    64, Little-Endian
  Global memory size                              3221225472 (3GiB)
  Error Correction support                        No
  Max memory allocation                           1717986918 (1.6GiB)
  Unified memory for Host and Device              No
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       32768 bits (4096 bytes)
  Global Memory cache type                        None
  Image support                                   No
  Local memory type                               Local
  Local memory size                               32768 (32KiB)
  Max number of constant args                     16
  Max constant buffer size                        67108864 (64MiB)
  Max size of kernel argument                     1024
  Queue properties
    Out-of-order execution                        No
    Profiling                                     Yes
  Profiling timer resolution                      0ns
  Execution capabilities
    Run OpenCL kernels                            Yes
    Run native kernels                            No
  Device Extensions cl_khr_byte_addressable_store cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_fp64

NULL platform behavior
  clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  Clover
  clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   Success [MESA]
  clCreateContext(NULL, ...) [default]            Success [MESA]
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT)  Success (1)
    Platform Name                                 Clover
    Device Name                                   Radeon RX550/550 Series (POLARIS12, DRM 3.40.0, 5.10.0-0.bpo.4-amd64, LLVM 11.0.1)
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  Success (1)
    Platform Name                                 Clover
    Device Name                                   Radeon RX550/550 Series (POLARIS12, DRM 3.40.0, 5.10.0-0.bpo.4-amd64, LLVM 11.0.1)
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL)  Success (1)
    Platform Name                                 Clover
    Device Name                                   Radeon RX550/550 Series (POLARIS12, DRM 3.40.0, 5.10.0-0.bpo.4-amd64, LLVM 11.0.1)

ICD loader properties
  ICD loader Name                                 OpenCL ICD Loader
  ICD loader Vendor                               OCL Icd free software
  ICD loader Version                              2.2.12
  ICD loader Profile                              OpenCL 2.2


  


  This would not be a tearing problem, as no tearing is visible when playing videos and the TearFree driver policy is enabled.

  


  $ → xrandr --verbose | grep TearFree
    TearFree: on
    TearFree: on
    TearFree: on


  


• Game Music Appreciation, One Year Later

  1er août 2013, par Multimedia Mike — General

  I released my game music website last year about this time. It was a good start and had potential to grow in a lot of directions. But I’m a bit disappointed that I haven’t evolved it as quickly as I would like to. I have made a few improvements, like adjusting the play lengths of many metadata-less songs and revising the original atrocious design of the website using something called Twitter Bootstrap (and, wow, once you know what Bootstrap is, you start noticing it everywhere on the modern web). However, here are a few of the challenges that have slowed me down over the year :

  Problems With Native Client – Build System
  The technology which enables this project — Google’s Native Client (NaCl) — can be troublesome. One of my key frustrations with the environment is that every single revision of the NaCl SDK seems to adopt a completely new build system layout. If you want to port your NaCl project forward to newer revisions, you have to spend time wrapping your head around whatever the favored build system is. When I first investigated NaCl, I think it was using vanilla GNU Make. Then it switched to SCons. Then I forgot about NaCl for about a year and when I came back, the SDK had reverted back to GNU Make. While that has been consistent, the layout of the SDK sometimes changes and a different example Makefile shows the way.

  The very latest version of the API has required me to really overhaul the Makefile and to truly understand the zen of Makefile programming. I’m even starting to grasp the relationship it has to functional programming.

  Problems With Native Client – API Versions and Chrome Bugs
  I built the original Salty Game Music Player when NaCl API version 16 was current. By the time I published the v16 version, v19 was available. I made the effort to port forward (a few APIs had superfically changed, nothing too dramatic). However, when I would experiment with this new player, I would see intermittent problems on my Windows 7 desktop. Because of this, I was hesitant to make a new player release.

  Around the end of May, I started getting bug reports from site users that their Chrome browsers weren’t allowing them to activate the Salty Game Music Player — the upshot was that they couldn’t play music unless they manually flipped a setting in their browser configuration. It turns out that Chrome 27 introduced a bug that caused this problem. Not only that, but my player was one of only 2 known NaCl apps that used the problematic feature (the other was developed by the Google engineer who entered the bug).

  After feeling negligent for a long while about not doing anything to fix the bug, I made a concerted and creative effort to work around the bug and pushed out a new version of the player (based on API v25). My effort didn’t work and I had to roll it back somewhat (but still using the new player binaries). The bug was something that I couldn’t work around. However, at about the same time that I was attempting to do this, Google was rolling out Chrome 28 which fixed the bug, rendering my worry and effort moot.

  Problems With Native Client – Still Not In The Clear
  I felt reasonably secure about releasing the updated player since I couldn’t make my aforementioned problem occur on my Windows 7 setup anymore. I actually have a written test plan for this player, believe it or not. However, I quickly started receiving new bug reports from Windows users. Mostly, these are Windows 8 users. The player basically doesn’t work at all for them now. One user reports the problem on Windows 7 (and another on Windows 2008 Server, I think). But I can’t see it.

  I have a theory about what might be going wrong, but of course I’ll need to test it, and determine how to fix it.

  Database Difficulties
  The player is only half of the site ; the other half is the organization of music files. Working on this project has repeatedly reminded me of my fundamental lack of skill concerning databases. I have a ‘production’ database– now I’m afraid to do anything with it for fear of messing it up. It’s an an SQLite3 database, so it’s easy to make backups and to create a copy in order to test and debug a new script. Still, I feel like I’m missing an entire career path worth of database best practices.

  There is also the matter of ongoing database maintenance. There are graphical frontends for SQLite3 which make casual updates easier and obviate the need for anything more sophisticated (like a custom web app). However, I have a slightly more complicated database entry task that I fear will require, well, a custom web app in order to smoothly process hundreds, if not thousands of new song files (which have quirks which prohibit the easy mass processing I have been able to get away with so far).

  Going Forward
  I remain hopeful that I’ll gradually overcome these difficulties. I still love this project and I have received nothing but positive feedback over the past year (modulo the assorted recommendations that I port the entire player to pure JavaScript).

  You would think I would learn a lesson about building anything on top of a Google platform in the future, especially Native Client. Despite all this, I have another NaCl project planned.

• Custom Segmentation Guide : How it Works & Segments to Test

  13 novembre 2023, par Erin — Analytics Tips, Uncategorized

  Struggling to get the insights you’re looking for with premade reports and audience segments in your analytics ?

  Custom segmentation can help you better understand your customers, app users or website visitors, but only if you know what you’re doing.

  You can derive false insights with the wrong segments, leading your marketing campaigns or product development in the wrong direction.

  In this article, we’ll break down what custom segmentation is, useful custom segments to consider, how new privacy laws affect segmentation options and how to create these segments in an analytics platform.

  What is custom segmentation ?

  Custom segmentation is when you divide your audience (customers, users, website visitors) into bespoke segments of your own design, not premade segments designed by the analytics or marketing platform provider.

  To do this, you single out “custom segment input” — data points you will use to pinpoint certain users. For example, it could be everyone who has visited a certain page on your site.

  

  Segmentation isn’t just useful for targeting marketing campaigns and also for analysing your customer data. Creating segments is a great way to dive deeper into your data beyond surface-level insights.

  You can explore how various factors impact engagement, conversion rates, and customer lifetime value. These insights can help guide your higher-level strategy, not just campaigns.

  How custom segments can help your business

  As the global business world clamours to become more “data-driven,” even smaller companies collect all sorts of data on visitors, users, and customers.

  However, inexperienced organisations often become “data hoarders” without meaningful insights. They have in-house servers full of data or gigabytes stored by Google Analytics and other third-party providers.

  

  One way to leverage this data is with standard customer segmentation models. This can help you get insights into your most valuable customer groups and other standard segments.

  Custom segments, in turn, can help you dive deeper. They help you unlock insights into the “why” of certain behaviours. They can help you segment customers and your audience to figure out :

  • Why and how someone became a loyal customer
  • How high-order-value customers interact with your site before purchases
  • Which behaviours indicate audience members are likely to convert
  • Which traffic sources drive the most valuable customers

  This specific insight’s power led Gartner to predict that 70% of companies will shift focus from “big data” to “small and wide” by 2025. The lateral detail is what helps inform your marketing strategy. 

  You don’t need the same volume of data if you’re analysing and segmenting it effectively.

  Custom segment inputs : 6 data points you can use to create valuable custom segments 

  To help you get started, here are six useful data points you can use as a basis to create segments — AKA customer segment inputs :

  

  Visits to certain pages

  A basic data point that’s great for custom segments is visits to certain pages. Create segments for popular middle-of-funnel pages and compare their engagement and conversion rates. 

  For example, if a user visits a case study page, you can compare their likelihood to convert vs. other visitors.

  This is a type of behavioural segmentation, but it is the easiest custom segment to set up in terms of analysis and marketing efforts.

  Visitors who perform certain actions

  The other important type of behavioural segment is visitors or users who take certain actions. Think of things like downloading a file, clicking a link, playing a video or scrolling a certain amount.

  For instance, you can create a segment of all visitors who have downloaded a white paper. This can help you explore, for example, what drives someone to download a white paper. You can look at the typical user journey and make it easier for them to access the white paper — especially if your sales reps indicate many inbound leads mention it as a key driver of their interest.

  User devices

  Device-based segmentation lets you compare engagement and conversion rates on mobile, desktop and tablets. You can also get insights into their usage patterns and potential issues with certain mobile elements.

  

  This is one aspect of technographic segmentation, where you segment based on users’ hardware or software. You can also create segments based on browser software or even specific versions.

  Loyal or high-value customers

  The best way to get more loyal or high-value customers is to explore their journey in more detail. These types of segments can help you better understand your ideal customers and how they act on your site.

  You can then use this insight to alter your campaigns or how you communicate with your target audience.

  For example, you might notice that high-value customers tend to come from a certain source. You can then focus your marketing efforts on this source to reach more of your ideal customers.

  Visitor or customer source

  You need to track the results if you’re investing in marketing (like an influencer campaign or a sponsored post) outside platforms with their own analytics.

  

  Before you can create a reliable segment, you need to make sure that you use campaign tracking parameters to reliably track the source. You can use our free campaign tracking URL builder for that.

  Demographic segments — location (country, state) and more

  Web analytics tools, such as Matomo, use visitors’ IP addresses to pinpoint their location more accurately by cross-referencing with a database of known and estimated IP locations. In addition, these tools can detect a visitor’s location through the language settings in their browser. 

  This can help create segments based on location or language. By exploring these trends, you can identify patterns in behaviour, tailor your content to specific audiences, and adapt your overall strategy to better meet the preferences and needs of your diverse visitor base.

  How new privacy laws affect segmentation options

  Over the past few years, new legislation regarding privacy and customer data has been passed globally. The most notable privacy laws are the GDPR in the EU, the CCPA in California and the VCDPA in Virginia.

  

  For most companies, it can save a lot of work and future headaches to choose a GDPR-compliant web analytics solution not only streamlines operations, saving considerable effort and preventing future headaches, but also ensures peace of mind by guaranteeing the collection of compliant and accurate data. This approach allows companies to maintain compliance with privacy regulations while remaining firmly committed to a data-driven strategy.

  Create your very own custom segments in Matomo (while ensuring compliance and data accuracy)

  Crafting precise marketing messages and optimising ROI is crucial, but it becomes challenging without the right tools, especially when it comes to maintaining accurate data.

  That’s where Matomo comes in. Our privacy-friendly web analytics platform is GDPR-compliant and ensures accurate data, empowering you to effortlessly create and analyse precise custom segments.

  If you want to improve your marketing campaigns while remaining GDPR-compliant, start your 21-day free trial of Matomo. No credit card required.