Sur d’autres sites (7747)

• Server-side tracking vs client-side tracking : What you need to know

  3 juillet, par Joe

  Server-side tracking vs client-side tracking : What you need to know

  Today, consumers are more aware of their online privacy rights, leading to an extensive use of ad blockers and stricter cookie policies. Organisations are facing some noteworthy challenges with this trend, including :

  • Limited data collection, which makes it harder to understand user behaviour and deliver personalised ads that resonate with customers
  • Rising compliance costs as businesses adapt to new regulations, straining resources and budgets.
  • Growing customer scepticism in data practices, affecting brand reputation.
  • Maintaining transparency and fostering trust with customers through clear communication about data practices.

  Server-side tracking can help resolve these problems. This article will cover server-side tracking, how it works, implementation methods and its benefits.

  What is server-side tracking ? 

  Server-side tracking refers to a method where user data is collected directly by a server rather than through a user’s browser.

  The key advantage of server-side tracking is that data collection, processing, and storage occur directly on the website’s server.

  For example, when a visitor interacts with any website, the server captures that activity through the backend system, allowing for greater data control and security. 

  Client-side tracking vs. server-side tracking 

  There are two methods to collect user data : client-side and server-side. 

  Let’s understand their differences. 

  Client-side tracking : Convenience with caveats

  Client-side tracking embeds JavaScript tags, pixels or other scripts directly into a website’s code. When a user interacts with the site, these tags fire, collecting data from their browser. This information might include page views, button clicks, form submissions and other user actions. 

  The collected data is then sent directly to third-party analytics platforms like Google Analytics or Adobe Analytics, or internal teams can also analyse it.

  This method is relatively easy to implement. That’s because marketers can often deploy these tags without needing extensive developer support, enabling quick adjustments and A/B testing. 

  However, there are some challenges. 

  Ad blockers and browser privacy settings, such as Intelligent Tracking Prevention (ITP), restrict the ability of third-party tags to collect data. 

  This results in data gaps and inaccuracies skewing analytics reports and potentially leading to misguided business decisions. 

  Reliance on numerous JavaScript tags can also negatively impact website performance, slowing down page load times and affecting user experience. This is especially true on mobile devices where processing power and network speeds are often limited.

  

  Now, let’s see how server-side tracking changes this.

  Server-side tracking : Control and reliability

  Server-side tracking shifts the burden of data collection from the user’s browser to a server controlled by the business. 

  Instead of relying on JavaScript tags firing directly from the user’s device, user interactions are first sent to the business’s own server. Here, the data can be processed, enriched, and analysed. 

  This method provides numerous advantages, including enhanced control over data integrity, improved privacy, and more, which we discuss in the next section.

  Benefits of server-side tracking 

  Server-side tracking offers a compelling alternative to traditional client-side methods, providing numerous business advantages. Let’s take a look at them.

  Improved data accuracy

  This method reduces inaccuracies caused by ad blockers or cookie restrictions by bypassing browser limitations. As a result, the data collected is more reliable, leading to better analytics and marketing attribution.

  Data minimisation

  Data minimisation is a fundamental principle in data protection. It emphasises that organisations should collect only data that is strictly needed for a specific purpose. 

  In server-side tracking, this translates into collecting just the essential data points and discarding anything extra before the data is sent to analytics platforms. It helps organisations avoid accumulating excessive personal information, reducing the risk of data breaches and misuse.

  For example, consider a scenario where a user purchases a product on an e-commerce website. 

  With client-side tracking scripts, the system might inadvertently collect a range of data, including the user’s IP address, browser type, operating system and even details about other websites they have visited. 

  However, for conversions, the organisation only needs to know the purchase amount, product IDs, user IDS, and timestamps. 

  Server-side tracking filters unnecessary information. This reduces the privacy impact and simplifies data analysis and storage.

  Cross-device tracking capabilities

  Server-side tracking provides a unified view of customer behaviour regardless of the device they use, allowing for more personalised and targeted marketing campaigns. 

  In-depth event tracking

  Server-side tracking helps businesses track events that occur outside their websites, such as payment confirmations. Companies gain insights into the entire customer journey, from initial interaction to final purchase, optimising every touchpoint. 

  Enhanced privacy compliance

  With increasing regulations like GDPR and CCPA, businesses can better manage user consent and data handling practices through server-side solutions. 

  Server-side setups make honouring user consent easier. If a user opts out, server-side logic can exclude their data from all outgoing analytics calls in one central place. 

  

  Server-side methods reassure users and regulators that data is collected and secured with minimal risk. 

  In sectors like government and banking, this level of control is often a non-negotiable part of their duty of care. 

  Extended cookie lifetime

  Traditional website tracking faces growing obstacles as modern browsers prioritise user privacy. Initiatives like Safari’s ITP block third-party cookies and also constrain the use of first-party cookies. 

  Other browsers, such as Firefox and Brave, are implementing similar methods, while Chrome is beginning to phase out third-party cookies. Retargeting and cross-site analytics, which rely on these cookies, encounter significant challenges.

  Server-side tracking overcomes this by allowing businesses to collect data over a longer duration. 

  When a website’s server directly sets a cookie, that cookie often lasts longer than cookies created by JavaScript code running inside the browser. This lets websites get around some of the limits browsers put on tracking and allows them to remember a visitor when they return to the site later, which gives better customer insights. Plus, server-side tracking typically classifies cookies as first-party data, which is less susceptible to blocking by browsers and ad blockers.

  Server-side tracking : Responsibilities and considerations

  While server-side tracking delivers powerful capabilities, remember that it also brings increased responsibility. Companies must remain vigilant in upholding privacy regulations and user consent. It’s up to the organisation to make sure the server follows user consent, for example, not sending data if someone has opted out.

  Server-side setups introduce technical complexity, which can potentially lead to data errors that are more difficult to identify and resolve. Therefore, monitoring processes and quality assurance practices are essential for data integrity. 

  How does server-side tracking work ? 

  When a user interacts with a website (e.g., clicking a button), this action triggers an event. The event could be anything from a page view to a form submission.

  The backend system captures relevant details such as the event type, user ID and timestamp. This information helps in understanding user behaviour and creating meaningful analytics.

  The captured data is processed directly on the organisation’s server, allowing for immediate validation. For example, organisations can add additional context or filter out irrelevant information.

  Instead of sending data to third-party endpoints, the organisation stores everything in its own database or data warehouse. This ensures full control over data privacy and security.

  Organisations can perform their own analysis using tools like SQL or Python. To visualise data, custom dashboards and reports can be created using self-hosted analytics tools. This way, businesses can present complex data in a clear and actionable manner.

  How to implement server-side tracking ?

  Server-side tracking can work in four common ways, each offering a different blend of control, flexibility and complexity.

  1. Server-side tag management

  In this method, organisations use platforms like Google Tag Manager Server-Side to manage tracking tags on the server, often using containers to isolate and manage different tagging environments. 

  

  (Image Source) 

  This approach offers a balance between control and ease of use. It allows for the deployment and management of tags without modifying the application code, which is particularly useful for marketers who want to adjust tracking configurations quickly.

  2. Direct server-to-server tracking via APIs

  This method involves sharing information between two servers without affecting the user’s browser or device. 

  A unique identifier is generated and stored on a server when a user interacts with an ad or webpage. 

  If a user takes some action, like making a purchase, the unique identifier is sent from the advertiser’s server directly to the platform’s server (Google or Facebook) via an API. 

  It requires more development effort but is ideal for organisations needing fine-grained data control.

  3. Using analytics platforms with built-in server SDKs

  Another way is to employ analytics platforms like Matomo that provide SDKs for various programming languages to instrument the server-side code. 

  This eases integration with the platform’s analytics features and is a good choice for organisations primarily using a single analytics platform and want to use its server-side capabilities.

  4. Hybrid approaches

  Finally, organisations can also combine client- and server-side tracking to capture different data types and maximise accuracy. 

  This method involves client-side scripts for specific interactions (like UI events) and server-side tracking for more sensitive or critical data (like transactions). 

  While these are general approaches, dedicated analytics platforms can also be helpful. Matomo, for example, facilitates server-side tracking through two specific methods.

  Using server logs

  Matomo can import existing web server logs, such as Apache or Nginx, that capture each request. Every page view or resource load becomes a data point. 

  Matomo’s log processing script reads log files, importing millions of hits. This removes the need to add code to the site, making it suitable for basic page analytics (like the URL) without client-side scripts, particularly on security-sensitive sites.

  Using the Matomo tracking API (Server-side SDKs)

  This method integrates application code with calls to Matomo’s API. For example, when a user performs a specific action, the server sends a request to Matomo.php, the tracking endpoint, which includes details like the user ID and action. 

  Matomo offers SDKs in PHP, Java C#, and community SDKs to simplify these calls. These allow tracking of not just page views but custom events such as downloads and transactions from the backend, functioning similarly to Google’s Measurement Protocol but sending data to the Matomo instance. 

  Data privacy, regulations and Matomo

  As privacy concerns grow and regulations like GDPR and CCPA become more stringent, businesses must adopt data collection methods that respect user consent and data protection rights. 

  Server-side tracking allows organisations to collect first-party data directly from their servers, which is generally considered more compliant with privacy regulations.

  Matomo is a popular open-source web analytics platform that is committed to privacy. It gives organisations 100% data ownership and control, and no data is sent to third parties by default.

  

  (Image Source) 

  Matomo is a full-featured analytics platform with dashboards and segmentation comparable to Google Analytics. It can self-host and provides DoNotTrack settings and the ability to anonymise IP addresses.

  Governments and organisations requiring data sovereignty, such as the EU Commission and the Swiss government, choose Matomo for web analytics due to its strong compliance posture.

  Balancing data collection and user privacy

  Ad blockers and other restrictions prevent data from being accurate. Server-side tracking helps get data on the server and makes it more reliable while respecting user privacy. Matomo supports server-side tracking, and over one million websites use Matomo to optimise their data strategies. 

  Get started today by trying Matomo for free for 21 days, no credit card required.

• Using PyAV to encode mono audio to file, params match docs, but still causes Errno 22

  20 février 2023, par andrew8088

  While trying to use PyAV to encode live mono audio from a microphone to a compressed audio stream (using mp2 or flac as encoder), the program kept raising an exception ValueError: [Errno 22] Invalid argument.

  


  To remove the live microphone source as a cause of the problem, and to make the problematic code easier for others to run/test, I have removed the mic source and now just generate a pure tone as a sequence of input buffers.

  


  All attempts to figure out the missing or mismatched or incorrect argument have just resulted in seeing documentation and examples that are the same as my code.

  


  I would like to know from someone who has used PyAV successfully for mono audio what the correct method and parameters are for encoding mono frames into the mono stream.

  


  The package used is av 10.0.0 installed with
pip3 install av --no-binary av
so it uses my package-manager provided ffmpeg library, which is version 4.2.7.

  


  The problematic python code is :

  


  #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Recreating an error 22 when encoding sound with PyAV.

Created on Sun Feb 19 08:10:29 2023
@author: andrewm
"""
import typing
import sys
import math
import fractions

import av
from av import AudioFrame

""" Ensure some PyAudio constants are still defined without changing 
    the PyAudio recording callback function and without depending 
    on PyAudio simply for reproducing the PyAV bug [Errno 22] thrown in 
    File "av/filter/context.pyx", line 89, in av.filter.context.FilterContext.push
"""
class PA_Stub():
    paContinue = True
    paComplete= False

pyaudio = PA_Stub()


"""Generate pure tone at given frequency with amplitude 0...1.0 at 
   sampling frewuency fs and beginning at phase offset 'phase'.
   Returns the new phase after the sinusoid has cycled over the 
   sampling window length.
"""
def generate_tone(
        freq:int, phase:float, amp:float, fs, samp_fmt, buffer:bytearray
) -> float:
    assert samp_fmt == "s16", "Only s16 supported atm"
    samp_size_bytes = 2
    n_samples = int(len(buffer)/samp_size_bytes)
    window = [int(0) for i in range(n_samples)]
    theta = phase
    phase_inc = 2*math.pi * freq / fs
    for i in range(n_samples):
        v = amp * math.sin(theta)
        theta += phase_inc
        s = int((2**15-1)*v)
        window[i] = s
    for sample_i in range(len(window)):
        byte_i = sample_i * samp_size_bytes
        enc = window[sample_i].to_bytes(
                2, byteorder=sys.byteorder, signed=True
        )
        buffer[byte_i] = enc[0]
        buffer[byte_i+1] = enc[1]
    return theta


channels = 1
fs = 44100  # Record at 44100 samples per second
fft_size_samps = 256
chunk_samps = fft_size_samps * 10  # Record in chunks that are multiples of fft windows.

# print(f"fft_size_samps={fft_size_samps}\nchunk_samps={chunk_samps}")

seconds = 3.0
out_filename = "testoutput.wav"

# Store data in chunks for 3 seconds
sample_limit = int(fs * seconds)
sample_len = 0
frames = []  # Initialize array to store frames

ffmpeg_codec_name = 'mp2'  # flac, mp3, or libvorbis make same error.

sample_size_bytes = 2
buffer = bytearray(int(chunk_samps*sample_size_bytes))
chunkperiod = chunk_samps / fs
total_chunks = int(math.ceil(seconds / chunkperiod))
phase = 0.0

### uncomment if you want to see the synthetic data being used as a mic input.
# with open("test.raw","wb") as raw_out:
#     for ci in range(total_chunks):
#         phase = generate_tone(2600, phase, 0.8, fs, "s16", buffer)
#         raw_out.write(buffer)
# print("finished gen test")
# sys.exit(0)
# #---- 

# Using mp2 or mkv as the container format gets the same error.
with av.open(out_filename+'.mp2', "w", format="mp2") as output_con:
    output_con.metadata["title"] = "My title"
    output_con.metadata["key"] = "value"
    channel_layout = "mono"
    sample_fmt = "s16p"

    ostream = output_con.add_stream(ffmpeg_codec_name, fs, layout=channel_layout)
    assert ostream is not None, "No stream!"
    cctx = ostream.codec_context
    cctx.sample_rate = fs
    cctx.time_base = fractions.Fraction(numerator=1,denominator=fs)
    cctx.format = sample_fmt
    cctx.channels = channels
    cctx.layout = channel_layout
    print(cctx, f"layout#{cctx.channel_layout}")
    
    # Define PyAudio-style callback for recording plus PyAV transcoding.
    def rec_callback(in_data, frame_count, time_info, status):
        global sample_len
        global ostream
        frames.append(in_data)
        nsamples = int(len(in_data) / (channels*sample_size_bytes))
        
        frame = AudioFrame(format=sample_fmt, layout=channel_layout, samples=nsamples)
        frame.sample_rate = fs
        frame.time_base = fractions.Fraction(numerator=1,denominator=fs)
        frame.pts = sample_len
        frame.planes[0].update(in_data)
        print(frame, len(in_data))
        
        for out_packet in ostream.encode(frame):
            output_con.mux(out_packet)
        for out_packet in ostream.encode(None):
            output_con.mux(out_packet)
        
        sample_len += nsamples
        retflag = pyaudio.paContinue if sample_lencode>

  


  If you uncomment the RAW output part you will find the generated data can be imported as PCM s16 Mono 44100Hz into Audacity and plays the expected tone, so the generated audio data does not seem to be the problem.

  


  The normal program console output up until the exception is :

  


  mp2 at 0x7f8e38202cf0> layout#4
Beginning
 5120
. 5120


  


  The stack trace is :

  


  Traceback (most recent call last):&#xA;&#xA;  File "Dev/multichan_recording/av_encode.py", line 147, in <module>&#xA;    ret_data, ret_flag = rec_callback(buffer, ci, {}, 1)&#xA;&#xA;  File "Dev/multichan_recording/av_encode.py", line 121, in rec_callback&#xA;    for out_packet in ostream.encode(frame):&#xA;&#xA;  File "av/stream.pyx", line 153, in av.stream.Stream.encode&#xA;&#xA;  File "av/codec/context.pyx", line 484, in av.codec.context.CodecContext.encode&#xA;&#xA;  File "av/audio/codeccontext.pyx", line 42, in av.audio.codeccontext.AudioCodecContext._prepare_frames_for_encode&#xA;&#xA;  File "av/audio/resampler.pyx", line 101, in av.audio.resampler.AudioResampler.resample&#xA;&#xA;  File "av/filter/graph.pyx", line 211, in av.filter.graph.Graph.push&#xA;&#xA;  File "av/filter/context.pyx", line 89, in av.filter.context.FilterContext.push&#xA;&#xA;  File "av/error.pyx", line 336, in av.error.err_check&#xA;&#xA;ValueError: [Errno 22] Invalid argument&#xA;&#xA;</module>

  


  edit : It's interesting that the error happens on the 2nd AudioFrame, as apparently the first one was encoded okay, because they are given the same attribute values aside from the Presentation Time Stamp (pts), but leaving this out and letting PyAV/ffmpeg generate the PTS by itself does not fix the error, so an incorrect PTS does not seem the cause.

  


  After a brief glance in av/filter/context.pyx the exception must come from a bad return value from res = lib.av_buffersrc_write_frame(self.ptr, frame.ptr)
  
Trying to dig into av_buffersrc_write_frame from the ffmpeg source it is not clear what could be causing this error. The only obvious one is a mismatch between channel layouts, but my code is setting the layout the same in the Stream and the Frame. That problem had been found by an old question pyav - cannot save stream as mono and their answer (that one parameter required is undocumented) is the only reason the code now has the layout='mono' argument when making the stream.

  


  The program output shows layout #4 is being used, and from https://github.com/FFmpeg/FFmpeg/blob/release/4.2/libavutil/channel_layout.h you can see this is the value for symbol AV_CH_FRONT_CENTER which is the only channel in the MONO layout.

  


  The mismatch is surely some other object property or an undocumented parameter requirement.

  


  How do you encode mono audio to a compressed stream with PyAV ?

  


• VideoWriter Doesn't work using openCV, ubuntu, Qt

  25 janvier 2023, par underflow223

  My code :

  


  cv::VideoWriter(
  strFile.toStdString(),
  cv::VideoWriter::fourcc('m','p','4','v'),
  nfps,
  cv::Size(1920/nresize, 1080/nresize)
);


  


  Error message :

  


  [mpeg4_v4l2m2m @ 0x7f50a43c50] arm_release_ver of this libmali is 'g6p0-01eac0', rk_so_ver is '7'.
Could not find a valid device
[mpeg4_v4l2m2m @ 0x7f50a43c50] can't configure encoder


  


  If I use MJPG codec, it works fine thow.

  


  This is OPENCV configure info :

  


  -- General configuration for OpenCV 4.6.0 =====================================
--   Version control:               unknown
-- 
--   Extra modules:
--     Location (extra):            /home/firefly/Downloads/opencv_contrib-4.6.0/modules
--     Version control (extra):     unknown
-- 
--   Platform:
--     Timestamp:                   2023-01-19T02:11:26Z
--     Host:                        Linux 5.10.110 aarch64
--     CMake:                       3.16.3
--     CMake generator:             Unix Makefiles
--     CMake build tool:            /usr/bin/make
--     Configuration:               Release
-- 
--   CPU/HW features:
--     Baseline:                    NEON FP16
-- 
--   C/C++:
--     Built as dynamic libs?:      YES
--     C++ standard:                11
--     C++ Compiler:                /usr/bin/c++  (ver 9.4.0)
--     C++ flags (Release):         -fsigned-char -W -Wall -Wreturn-type -Wnon-virtual-dtor -Waddress -Wsequence-point -Wformat -Wformat-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections    -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG  -DNDEBUG
--     C++ flags (Debug):           -fsigned-char -W -Wall -Wreturn-type -Wnon-virtual-dtor -Waddress -Wsequence-point -Wformat -Wformat-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections    -fvisibility=hidden -fvisibility-inlines-hidden -g  -O0 -DDEBUG -D_DEBUG
--     C Compiler:                  /usr/bin/cc
--     C flags (Release):           -fsigned-char -W -Wall -Wreturn-type -Waddress -Wsequence-point -Wformat -Wformat-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections    -fvisibility=hidden -O3 -DNDEBUG  -DNDEBUG
--     C flags (Debug):             -fsigned-char -W -Wall -Wreturn-type -Waddress -Wsequence-point -Wformat -Wformat-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections    -fvisibility=hidden -g  -O0 -DDEBUG -D_DEBUG
--     Linker flags (Release):      -Wl,--gc-sections -Wl,--as-needed -Wl,--no-undefined  
--     Linker flags (Debug):        -Wl,--gc-sections -Wl,--as-needed -Wl,--no-undefined  
--     ccache:                      NO
--     Precompiled headers:         NO
--     Extra dependencies:          dl m pthread rt
--     3rdparty dependencies:
-- 
--   OpenCV modules:
--     To be built:                 aruco barcode bgsegm bioinspired calib3d ccalib core datasets dnn dnn_objdetect dnn_superres dpm face features2d flann freetype fuzzy gapi hfs highgui img_hash imgcodecs imgproc intensity_transform line_descriptor mcc ml objdetect optflow phase_unwrapping photo plot quality rapid reg rgbd saliency shape stereo stitching structured_light superres surface_matching text tracking ts video videoio videostab wechat_qrcode xfeatures2d ximgproc xobjdetect xphoto
--     Disabled:                    world
--     Disabled by dependency:      -
--     Unavailable:                 alphamat cudaarithm cudabgsegm cudacodec cudafeatures2d cudafilters cudaimgproc cudalegacy cudaobjdetect cudaoptflow cudastereo cudawarping cudev cvv hdf java julia matlab ovis python2 python3 sfm viz
--     Applications:                tests perf_tests apps
--     Documentation:               NO
--     Non-free algorithms:         NO
-- 
--   GUI:                           GTK3
--     GTK+:                        YES (ver 3.24.20)
--       GThread :                  YES (ver 2.64.6)
--       GtkGlExt:                  NO
--     VTK support:                 NO
-- 
--   Media I/O: 
--     ZLib:                        /usr/lib/aarch64-linux-gnu/libz.so (ver 1.2.11)
--     JPEG:                        /usr/lib/aarch64-linux-gnu/libjpeg.so (ver 80)
--     WEBP:                        build (ver encoder: 0x020f)
--     PNG:                         /usr/lib/aarch64-linux-gnu/libpng.so (ver 1.6.37)
--     TIFF:                        /usr/lib/aarch64-linux-gnu/libtiff.so (ver 42 / 4.1.0)
--     JPEG 2000:                   build (ver 2.4.0)
--     OpenEXR:                     build (ver 2.3.0)
--     HDR:                         YES
--     SUNRASTER:                   YES
--     PXM:                         YES
--     PFM:                         YES
-- 
--   Video I/O:
--     DC1394:                      YES (2.2.5)
--     FFMPEG:                      YES
--       avcodec:                   YES (58.54.100)
--       avformat:                  YES (58.29.100)
--       avutil:                    YES (56.31.100)
--       swscale:                   YES (5.5.100)
--       avresample:                YES (4.0.0)
--     GStreamer:                   YES (1.16.2)
--     v4l/v4l2:                    YES (linux/videodev2.h)
-- 
--   Parallel framework:            pthreads
-- 
--   Trace:                         YES (with Intel ITT)
-- 
--   Other third-party libraries:
--     Lapack:                      NO
--     Eigen:                       NO
--     Custom HAL:                  YES (carotene (ver 0.0.1))
--     Protobuf:                    build (3.19.1)
-- 
--   OpenCL:                        YES (no extra features)
--     Include path:                /home/firefly/Downloads/opencv-4.6.0/3rdparty/include/opencl/1.2
--     Link libraries:              Dynamic load
-- 
--   Python (for build):            /usr/bin/python2.7
-- 
--   Java:                          
--     ant:                         NO
--     JNI:                         NO
--     Java wrappers:               NO
--     Java tests:                  NO
-- 
============================================================================================


  


  ffmpeg info :

  


  ============================================================================================
ffmpeg
ffmpeg version 4.2.4-1ubuntu1.0firefly5 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 9 (Ubuntu 9.4.0-1ubuntu1~20.04.1)
  configuration: --prefix=/usr --extra-version=1ubuntu1.0firefly5 --toolchain=hardened --libdir=/usr/lib/aarch64-linux-gnu --incdir=/usr/include/aarch64-linux-gnu --arch=arm64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-libdrm --enable-librga --enable-rkmpp --enable-version3 --disable-libopenh264 --disable-vaapi --disable-vdpau --disable-decoder=h264_v4l2m2m --disable-decoder=vp8_v4l2m2m --disable-decoder=mpeg2_v4l2m2m --disable-decoder=mpeg4_v4l2m2m --enable-shared --disable-doc
  libavutil      56. 31.100 / 56. 31.100
  libavcodec     58. 54.100 / 58. 54.100
  libavformat    58. 29.100 / 58. 29.100
  libavdevice    58.  8.100 / 58.  8.100
  libavfilter     7. 57.100 /  7. 57.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  5.100 /  5.  5.100
  libswresample   3.  5.100 /  3.  5.100
  libpostproc    55.  5.100 / 55.  5.100
Hyper fast Audio and Video encoder
usage: ffmpeg [options] [[infile options] -i infile]... {[outfile options] outfile}...
====================================================================================