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• Record video stream in rust

  19 novembre 2024, par El_Loco

  I have bought a stereo camera with global shutter and a frame rate of at most 120 fps. https://www.amazon.com/dp/B0D8T3ZSL4?ref_=pe_386300_442618370_TE_sc_as_ri_0#

  


  My next step is to write a program that can show and record a video with desired fps and resolution.

  


  use opencv::{&#xA;    core, highgui,&#xA;    prelude::*,&#xA;    videoio::{self, VideoCapture},&#xA;    Result,&#xA;};&#xA;&#xA;fn open_camera() -> Result<videocapture> {&#xA;    let capture = videoio::VideoCapture::new(2, videoio::CAP_ANY)?;&#xA;    return Ok(capture);&#xA;}&#xA;fn main() -> Result&lt;()> {&#xA;    let window = "video capture";&#xA;    highgui::named_window(window, highgui::WINDOW_AUTOSIZE)?;&#xA;    let mut cam = open_camera()?;&#xA;    let opened = videoio::VideoCapture::is_opened(&amp;cam)?;&#xA;    if !opened {&#xA;        panic!("Unable to open default camera!");&#xA;    }&#xA;    let width = 3200.0;&#xA;    let height = 1200.0;&#xA;    cam.set(videoio::CAP_PROP_FRAME_WIDTH, width)?;&#xA;    cam.set(videoio::CAP_PROP_FRAME_HEIGHT, height)?;&#xA;&#xA;    // Set the frame rate (FPS)&#xA;    let fps = 60.0;&#xA;        &#xA;    let fourcc = videoio::VideoWriter::fourcc(&#x27;M&#x27;, &#x27;J&#x27;, &#x27;P&#x27;, &#x27;G&#x27;)?;&#xA;    let mut writer = videoio::VideoWriter::new(&#xA;        "video_output.avi",&#xA;        fourcc,&#xA;        fps,&#xA;        core::Size::new(width as i32, height as i32),&#xA;        true,&#xA;    )?;&#xA;&#xA;    if !writer.is_opened()? {&#xA;        println!("Error: Could not open the video writer.");&#xA;    }&#xA;&#xA;    let mut frame = core::Mat::default();&#xA;    let mut ctr = 0;&#xA;    while cam.read(&amp;mut frame)? {&#xA;        if frame.empty() {&#xA;            break;&#xA;        }&#xA;        writer.write(&amp;frame)?;&#xA;        highgui::imshow(window, &amp;frame)?;&#xA;        &#xA;        let key = highgui::wait_key(1)?;&#xA;        if key > 0 {&#xA;            break;&#xA;        }&#xA;        ctr &#x2B;= 1;&#xA;        if ctr == 600 {&#xA;            break;&#xA;        }&#xA;    }&#xA;    cam.release()?;&#xA;    writer.release()?;&#xA;    Ok(())&#xA;}&#xA;</videocapture>

  


  When I run this code the frame rate is terrible. Like 1 fps or something. For debugging I tried to run in cheese. There I got 30 fps with full resolution 3200x1200. But I cannot change the fps to 60 fps what I can see.

  


  Then I tried to capture a video using ffmpeg :

  


  ffmpeg -f v4l2 -framerate 60 -video_size 3200x1200 -i /dev/video2 output.mp4

  


  With the following output :

  


  [video4linux2,v4l2 @ 0x5a72cbbd1400] The driver changed the time per frame from 1/60 to 1/2
Input #0, video4linux2,v4l2, from '/dev/video2':
  Duration: N/A, start: 2744.250608, bitrate: 122880 kb/s
  Stream #0:0: Video: rawvideo (YUY2 / 0x32595559), yuyv422, 3200x1200, 122880 kb/s, 2 fps, 2 tbr, 1000k tbn
File 'output.mp4' already exists. Overwrite? [y/N]


  


  The frame rate is lowered to 2 fps.

  


  Then I tried to run v4l2-ctl --list-formats-ext -d 2 with the following output :

  


  ioctl: VIDIOC_ENUM_FMT
        Type: Video Capture

        [0]: 'MJPG' (Motion-JPEG, compressed)
                Size: Discrete 3200x1200
                        Interval: Discrete 0.017s (60.000 fps)
                        Interval: Discrete 0.033s (30.000 fps)
                        Interval: Discrete 0.040s (25.000 fps)
                        Interval: Discrete 0.050s (20.000 fps)
                        Interval: Discrete 0.067s (15.000 fps)
                        Interval: Discrete 0.100s (10.000 fps)
                Size: Discrete 2560x720
                        Interval: Discrete 0.017s (60.000 fps)
                        Interval: Discrete 0.033s (30.000 fps)
                        Interval: Discrete 0.040s (25.000 fps)
                        Interval: Discrete 0.050s (20.000 fps)
                        Interval: Discrete 0.067s (15.000 fps)
                        Interval: Discrete 0.100s (10.000 fps)
                Size: Discrete 1600x600
                        Interval: Discrete 0.008s (120.000 fps)
                        Interval: Discrete 0.017s (60.000 fps)
                        Interval: Discrete 0.033s (30.000 fps)
                        Interval: Discrete 0.040s (25.000 fps)
                        Interval: Discrete 0.050s (20.000 fps)
                        Interval: Discrete 0.067s (15.000 fps)


  


  I then tried to open the camera using qv4land there it seemed to work. Does not seem like I can record a video though.

  


  I am using Rust to learn. I want to be able to programmatically be able to record a video somehow and then do computer vision. The easiest would be to do it in Rust. But other solutions are ok.

  


  Edit
I have found some more this morning :

  


  v4l2-ctl -d 2 --list-formats-ext
ioctl: VIDIOC_ENUM_FMT
    Type: Video Capture

    [0]: 'MJPG' (Motion-JPEG, compressed)
        Size: Discrete 3200x1200
            Interval: Discrete 0.017s (60.000 fps)
            Interval: Discrete 0.033s (30.000 fps)
            Interval: Discrete 0.040s (25.000 fps)
            Interval: Discrete 0.050s (20.000 fps)
            Interval: Discrete 0.067s (15.000 fps)
            Interval: Discrete 0.100s (10.000 fps)

    [1]: 'YUYV' (YUYV 4:2:2)
        Size: Discrete 3200x1200
            Interval: Discrete 0.500s (2.000 fps)
        Size: Discrete 2560x720
            Interval: Discrete 0.500s (2.000 fps)
        Size: Discrete 1600x600
            Interval: Discrete 0.100s (10.000 fps)


  


  I also found here that order of flags was important for ffmpeg. Running this I can actually record a video with 60 fps :

  


  ffmpeg -framerate 60 -f v4l2 -video_size 3200x1200 -input_format mjpeg  -i /dev/video2 output.avi

  


  A drawback is that the images does not look very sharp. You can clearly see the pixels. (I am new to video formats etc as well. Before it has just worked.)

  


  If I change from avito mkvit is slow again.

  


  In the link above I also saw a suggestion to first do :

  


  ffmpeg -framerate 60 -f v4l2 -video_size 3200x1200 -input_format mjpeg  -i /dev/video2 -c copy mjpeg.mkv

  


  and then :

  


  ffmpeg -i mjpeg.mkv -c:v libx264 -crf 23 -preset medium -pix_fmt yuv420p out.mkv

  


  which worked. But I am not sure those flags are ideal for the camera I have. I think it is a good start to make it run as expected using command line and ffmpeg. So I know what format to use and that it actually works as intended before doing it programmatically.

  


• Can I convert a django video upload from a form using ffmpeg before storing the video ?

  5 mai 2014, par GetItDone

  I’ve been stuck for weeks trying to use ffmpeg to convert user uploaded videos to flv. I use heroku to host my website, and store my static and media files on amazon S3 with s3boto. The initial video file will upload fine, however when I retrieve the video and run a celery task (in the same view where the initial video file is uploaded), the new file won’t store on S3. I’ve been trying to get this to work for over a month, with no luck, and really no good resources available for learning how to do this, so I figure maybe if I can get the ffmpeg task to run before storing the video I may be able to get it to work. Unfortunately I’m still not a very advanced at python (or django), so I don’t even know if/how this is possible. Anyone have any ideas ? I am willing to use any solution at this point no matter how ugly, as long as it successfully takes video uploads and converts to flv using ffmpeg, with the resulting file being stored on S3. It doesn’t seem that my situation is very common, because no matter where I look, I cannot find a solution that explains what I should be trying to do. Therefore I will be very appreciative of any guidance. Thanks. My relevant code follows :

  #models.py
  
  def content_file_name(instance, filename):
  
      ext = filename.split('.')[-1]
  
      new_file_name = "remove%s.%s" % (uuid.uuid4(), ext)
  
      return '/'.join(['videos', instance.teacher.username, new_file_name])
  
  
  
  class BroadcastUpload(models.Model):
  
      title = models.CharField(max_length=50, verbose_name=_('Title'))
  
      description = models.TextField(max_length=100, verbose_name=_('Description'))
  
      teacher = models.ForeignKey(User, null=True, blank=True, related_name='teacher')
  
      created_date = models.DateTimeField(auto_now_add=True)
  
      video_upload = models.FileField(upload_to=content_file_name)
  
      flvfilename = models.CharField(max_length=100, null=True, blank=True)
  
      videothumbnail = models.CharField(max_length=100, null=True, blank=True)
  
  
  
  #tasks.py
  
  @task(name='celeryfiles.tasks.convert_flv')
  
  def convert_flv(video_id):
  
      video = BroadcastUpload.objects.get(pk=video_id)
  
      print "ID: %s" % video.id
  
      id = video.id
  
      print "VIDEO NAME: %s" % video.video_upload.name
  
      teacher = video.teacher
  
      print "TEACHER: %s" % teacher
  
      filename = video.video_upload
  
      sourcefile = "%s%s" % (settings.MEDIA_URL, filename)
  
      vidfilename = "%s_%s.flv" % (teacher, video.id)
  
      targetfile = "%svideos/flv/%s" % (settings.MEDIA_URL, vidfilename)
  
      ffmpeg = "ffmpeg -i %s %s" % (sourcefile, vidfilename)
  
      try:
  
          ffmpegresult = subprocess.call(ffmpeg)
  
          #also tried separately with following line:
  
          #ffmpegresult = commands.getoutput(ffmpeg)
  
          print "---------------FFMPEG---------------"
  
          print "FFMPEGRESULT: %s" % ffmpegresult
  
      except Exception as e:
  
          ffmpegresult = None
  
          print("Failed to convert video file %s to %s" % (sourcefile, targetfile))
  
          print(traceback.format_exc())
  
      video.flvfilename = vidfilename
  
      video.save()
  
  
  
  @task(name='celeryfiles.tasks.ffmpeg_image')        
  
  def ffmpeg_image(video_id):
  
      video = BroadcastUpload.objects.get(pk=video_id)
  
      print "ID: %s" %video.id
  
      id = video.id
  
      print "VIDEO NAME: %s" % video.video_upload.name
  
      teacher = video.teacher
  
      print "TEACHER: %s" % teacher
  
      filename = video.video_upload
  
      sourcefile = "%s%s" % (settings.MEDIA_URL, filename)
  
      imagefilename = "%s_%s.png" % (teacher, video.id)
  
      thumbnailfilename = "%svideos/flv/%s" % (settings.MEDIA_URL, thumbnailfilename)
  
      grabimage = "ffmpeg -y -i %s -vframes 1 -ss 00:00:02 -an -vcodec png -f rawvideo -s 320x240 %s" % (sourcefile, thumbnailfilename)
  
      try:        
  
           videothumbnail = subprocess.call(grabimage)
  
           #also tried separately following line:
  
           #videothumbnail = commands.getoutput(grabimage)
  
           print "---------------IMAGE---------------"
  
           print "VIDEOTHUMBNAIL: %s" % videothumbnail
  
      except Exception as e:
  
           videothumbnail = None
  
           print("Failed to convert video file %s to %s" % (sourcefile, thumbnailfilename))
  
           print(traceback.format_exc())
  
      video.videothumbnail = imagefilename
  
      video.save()
  
  
  
  #views.py
  
  def upload_broadcast(request):
  
      if request.method == 'POST':
  
          form = BroadcastUploadForm(request.POST, request.FILES)
  
          if form.is_valid():
  
              upload=form.save()
  
              video_id = upload.id
  
              image_grab = ffmpeg_image.delay(video_id)
  
              video_conversion = convert_flv.delay(video_id)
  
              return HttpResponseRedirect('/current_classes/')
  
      else:
  
          form = BroadcastUploadForm(initial={'teacher': request.user,})
  
      return render_to_response('videos/create_video.html', {'form': form,}, context_instance=RequestContext(request))
  
  
  
  #settings.py
  
  DEFAULT_FILE_STORAGE = 'myapp.s3utils.MediaRootS3BotoStorage'
  
  DEFAULT_S3_PATH = "media"
  
  STATICFILES_STORAGE = 'myapp.s3utils.StaticRootS3BotoStorage'
  
  STATIC_S3_PATH = "static"
  
  AWS_STORAGE_BUCKET_NAME = 'my_bucket'
  
  CLOUDFRONT_DOMAIN = 'domain.cloudfront.net'
  
  AWS_ACCESS_KEY_ID = 'MY_KEY_ID'
  
  AWS_SECRET_ACCESS_KEY = 'MY_SECRET_KEY'
  
  MEDIA_ROOT = '/%s/' % DEFAULT_S3_PATH
  
  MEDIA_URL = 'http://%s/%s/' % (CLOUDFRONT_DOMAIN, DEFAULT_S3_PATH)
  
  ...
  
  
  
  #s3utils.py
  
  from storages.backends.s3boto import S3BotoStorage
  
  from django.utils.functional import SimpleLazyObject
  
  
  
  StaticRootS3BotoStorage = lambda: S3BotoStorage(location='static')
  
  MediaRootS3BotoStorage  = lambda: S3BotoStorage(location='media')

  I can add any other info if needed to help me solve my problem.

• Piwik is now Matomo – Announcement

  
  9 janvier 2018, par Matomo Core Team

  You may be surprised to read this announcement, but no stress, take a deep breath, nothing big is going to happen, it is just our name that is changing and here are the reasons why.

  

  Why are we changing from Piwik to Matomo ?

  “After an epic 10 year journey creating and perfecting the best open digital analytics solution, we felt it was a good time to refresh our brand to reflect how far we have come and to reaffirm our vision :
  To create, as a community, the leading international open source digital analytics platform, that gives every user full control of their data.”

  Matthieu Aubry, creator of Piwik

  As projects evolve, so do names. After 10 years of Piwik and the amazing achievement of building the top open source analytics software that gives every user full control of their data, we are now looking forward to the next chapter. Thus, Piwik, the community project, will now become Matomo. The only change is our name, everything else stays the same.

  This will allow users to take a fresh look at what we’ve become today and acknowledging all of the community’s hard work over the past 10 years. In addition, we also want our name to be unique, ensuring that it is not shared with any other company to remove any possible confusion or affiliations. Piwik is already used on over 1 million websites and with Matomo, we hope to reach our maximum potential.

  With the strong focus on privacy worldwide and the upcoming privacy regulations about to be legislated in Europe, it is clear that we were on the right mission from the very beginning. With the upcoming big release Matomo 4.0 planned for this year, new privacy protections will bring users the tools to be compliant with the GDPR privacy laws. And Matomo will grow in line with these regulations, with a very clear and focused vision.

  Changing our name is an exciting opportunity for us, and we hope you love the name Matomo as much as we do.

  Matomo FAQs

  So what is going to change for me ?

  Well, basically nothing, the name will change but the values stay the same : Matomo (Piwik) will continue to be free and always will be.

  Also the same people stay behind the project. We are motivated more than ever to take this project to the next level.

  Why not keep the name Piwik ?

  For a few reasons, one of which is to ensure that Matomo does not/will not share its name with any other businesses unlike Piwik. We also want to protect the Matomo brand and for it to remain the open source community project name forever.

  Where does the name Matomo come from ?

  We loved the name Piwik and were looking for something that sounded just as good ! Initially we wanted to have an acronym based on key terms, such as Free, Open Source and Privacy, but none really fit us perfectly.

  Until we found Matomo ! Easily pronounced in all languages. Short enough to remember. Concise. And best of all… Matomo means honesty in Japanese. Which aligns with one of our key values – transparency.

  We love the name Matomo and hope you do too.

  What is the vision of Matomo ?

  

  We have come a long way in those 10 years ! However, our mission statement remains the same :

  “To create, as a community, the leading international open source digital analytics platform, that gives every user full control of their data.”

  Matomo provides a range of amazing and innovative features, allowing you to get a 360 view of your visitors. These insights are invaluable to help understand behavior, keep track of goals, and increase conversion rates and revenue.

  Who will deliver Matomo professional services ?

  Any company who wishes to. The only exception is that no companies will be allowed to have the name Matomo.

  Our company providing professional services is and will remain InnoCraft.

  Where can I follow the Matomo project ?

  Our new website will be matomo.org (automatically redirected from Piwik.org)

  Follow our new Twitter : twitter.com/matomo_org

  Github : github.com/matomo-org

  Facebook : facebook.com/Matomo.org

  Linkedin : linkedin.com/company/matomo/

  If you are already following us on social media, you will be kept up to date with Matomo automatically as all social media accounts will be redirected.

  How should I pronounce Matomo ?

  If you’re wondering how to say ‘Matomo’, you can find out by clicking play :

  Where can I see a demo of Matomo ?

  On demo.matomo.org

  Where can I download Matomo first release ?

  On matomo.org/download

  (Matomo 3.3.0 will be released in the next few days)

  What is the new logo ?

  Check it out below.

  

  Matomo trademark Policy

  Matomo is an internationally registered trademark of Matthieu Aubry, Founder of Piwik (now Matomo).

  Information about how to use the name Matomo (and logo) can be found here : matomo.org/trademark/

  What are the next big steps ?

  We will keep it simple for our valued users. As it is just a name change, the only thing you will notice is that the Piwik brand will gradually be replaced on the websites you are used to seeing the name on. The first version of Matomo will be available in just a few days for download. The software version numbers stay the same : the next release after Piwik 3.2.1 will be Matomo 3.3.0.

  All our public HTTP APIs and Tracking SDKs will continue working normally. As you can imagine, there is a lot of work and complexity behind slowly updating all the SDKs and keeping backwards compatibility, so our renaming project will take a few weeks to complete.

  The Matomo trademark will later be transferred into the Matomo foundation, a non-profit that will be dedicated to promoting and ensuring access to Matomo and our related open source projects in perpetuity.

  ---

  Thank you

  Thank you for continuing to support our project, alongside our 20+ Matomo core team members and more than 500 contributors.

  Please help to spread the word about this announcement by sharing it with friends or or colleagues who may benefit from using Matomo Analytics !

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