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  • L’agrémenter visuellement

    10 avril 2011

    MediaSPIP est basé sur un système de thèmes et de squelettes. Les squelettes définissent le placement des informations dans la page, définissant un usage spécifique de la plateforme, et les thèmes l’habillage graphique général.
    Chacun peut proposer un nouveau thème graphique ou un squelette et le mettre à disposition de la communauté.

  • Publier sur MédiaSpip

    13 juin 2013

    Puis-je poster des contenus à partir d’une tablette Ipad ?
    Oui, si votre Médiaspip installé est à la version 0.2 ou supérieure. Contacter au besoin l’administrateur de votre MédiaSpip pour le savoir

  • Ajouter des informations spécifiques aux utilisateurs et autres modifications de comportement liées aux auteurs

    12 avril 2011, par

    La manière la plus simple d’ajouter des informations aux auteurs est d’installer le plugin Inscription3. Il permet également de modifier certains comportements liés aux utilisateurs (référez-vous à sa documentation pour plus d’informations).
    Il est également possible d’ajouter des champs aux auteurs en installant les plugins champs extras 2 et Interface pour champs extras.

Sur d’autres sites (6940)

  • Leading Google Analytics alternative, Matomo, parodies Christopher Nolan blockbuster ahead of the UA sunset

    4 juillet 2023, par Erin — Press Releases

    Wellington, New Zealand, 4 July 2023 : In the world of online data, Google Analytics has long reigned supreme. Its dominance has been unquestioned, leaving website owners with little choice but to rely on the tech giant for their data insights. However, a new dawn in web analytics is upon us, and Matomo, the leading alternative to Google Analytics, is seizing a unique opportunity to position itself as the go-to provider. In a bold move, Matomo has launched a parody trailer, “Googleheimer,” humorously taking a satirical swipe at Google in the style of the upcoming Oppenheimer biopic by Christopher Nolan.

    Capitalising on a time-bound decision

    With an important decision looming for marketers and web specialists who need to switch analytics providers by July 1st, Matomo has found the perfect window to capture their attention.

    The urgency of the situation, combined with the high intent to switch providers, sets the stage for Matomo to establish itself as the leading alternative analytics platform of choice.

    Matomo’s parody trailer addresses the frustrations of GA4 head-on by highlighting the issues and the uncertainties caused by the sunset of Universal Analytics in humorous satire with lines such as :

    “But we’re keeping everyone’s data, right ? Right ?? …RIGHT ?!”

    Riding on the coat tails of this summer’s anticipated blockbuster from Christopher Nolan, Matomo openly points at the downsides of GA4, and reflects many frustrated marketers pain points in an entertaining way. Beneath the comedic and satirical tone lies the message that users have choices, and no longer need to surrender to the behemoth incumbent.

    Matomo was founded to challenge the status quo and provide a solution for those who believe in privacy and in ethical analytics, and who prefer that their customer data not be concentrated in the hands of just a few corporations.

    Watch the full trailer here. 


    About Matomo

    Matomo is a world-leading open-source privacy-friendly ethical web analytics platform, trusted by over 1.4 million websites in 190 countries and translated into over 50 languages. Matomo helps businesses and organisations track and optimise their online presence allowing users to easily collect, analyse, and act on their website and marketing data to gain a deeper understanding of their visitors and drive conversions and revenue. Matomo’s vision is to create, as a community, the leading open digital analytics platform that gives every user complete control of their data.

    Visit matomo.org for more information.




    More on Google Analytics changes



    A new dawn in web analytics is upon us, and Matomo – the leading alternative to Google Analytics – is here for it. After 20 years, Google is blowing up Universal Analytics (or GA3) – and taking your data with it. Inspired by Christopher Nolan’s upcoming biopic about physicist J. Robert Oppenheimer and the making of his atomic bomb (also known as “The Manhattan Project”), this parody trailer openly points to Google and draws the comparison in humorous satire. GA4 comes with a new set of metrics, setups and reports that change how you analyse your data.

  • How to obtain time markers for video splitting using python/OpenCV

    10 novembre 2018, par Bleddyn Raw-Rees

    I’m working on my MSc project which is researching automated deletion of low value content in digital file stores. I’m specifically looking at the sort of long shots that often occur in natural history filming whereby a static camera is left rolling in order to capture the rare snow leopard or whatever. These shots may only have some 60s of useful content with perhaps several hours of worthless content either side.

    As a first step I have a simple motion detection program from Adrian Rosebrock’s tutorial [http://www.pyimagesearch.com/2015/05/25/basic-motion-detection-and-tracking-with-python-and-opencv/#comment-393376]. Next I intend to use FFMPEG to split the video.

    What I would like help with is how to get in and out points based on the first and last points that motion is detected in the video.

    Here is the code should you wish to see it...

    # import the necessary packages
    import argparse
    import datetime
    import imutils
    import time
    import cv2

    # construct the argument parser and parse the arguments
    ap = argparse.ArgumentParser()
    ap.add_argument("-v", "--video", help="path to the video file")
    ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")
    args = vars(ap.parse_args())

    # if the video argument is None, then we are reading from webcam
    if args.get("video", None) is None:
    camera = cv2.VideoCapture(0)
    time.sleep(0.25)

    # otherwise, we are reading from a video file
    else:
       camera = cv2.VideoCapture(args["video"])

    # initialize the first frame in the video stream
    firstFrame = None

    # loop over the frames of the video
    while True:
       # grab the current frame and initialize the occupied/unoccupied
       # text
       (grabbed, frame) = camera.read()
       text = "Unoccupied"

       # if the frame could not be grabbed, then we have reached the end
       # of the video
       if not grabbed:
           break

       # resize the frame, convert it to grayscale, and blur it
       frame = imutils.resize(frame, width=500)
       gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
       gray = cv2.GaussianBlur(gray, (21, 21), 0)

       # if the first frame is None, initialize it
       if firstFrame is None:
           firstFrame = gray
           continue

       # compute the absolute difference between the current frame and
       # first frame
       frameDelta = cv2.absdiff(firstFrame, gray)
       thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]

       # dilate the thresholded image to fill in holes, then find contours
       # on thresholded image
       thresh = cv2.dilate(thresh, None, iterations=2)
       (_, cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

       # loop over the contours
       for c in cnts:
           # if the contour is too small, ignore it
           if cv2.contourArea(c) < args["min_area"]:
               continue

           # compute the bounding box for the contour, draw it on the frame,
           # and update the text
           (x, y, w, h) = cv2.boundingRect(c)
           cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
           text = "Occupied"

       # draw the text and timestamp on the frame
       cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
           cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
       cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
           (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)

       # show the frame and record if the user presses a key
       cv2.imshow("Security Feed", frame)
       cv2.imshow("Thresh", thresh)
       cv2.imshow("Frame Delta", frameDelta)
       key = cv2.waitKey(1) & 0xFF

       # if the `q` key is pressed, break from the lop
       if key == ord("q"):
           break

    # cleanup the camera and close any open windows
    camera.release()
    cv2.destroyAllWindows()
  • ffmpeg arguments for youtube upload [duplicate]

    9 mars, par Hoopes

    I'm currently having an issue in my ios app where youtube sharing of a video created by ffmpeg seems broken. I am starting with an audio file, and an image that I will use as the static background of the video.

    


    ffmpeg -y 
-i "/path/to/audio.m4a" 
-r 24 
-i "/path/to/background.png" 
-codec:a aac_at 
-codec:v h264_videotoolbox 
-brand mp42 
-vf "scale=1080:1080" 
-vf "scale=out_color_matrix=bt709" 
-color_primaries bt709 
-color_trc bt709 
-colorspace bt709 
-movflags +faststart 
"output.mp4"


    


    Note that since i'm on an ios device, i am using h264_videotoolbox, which uses the apple hardware to help encode it.

    


    When I use the regular ios share screen, and share to something like slack, the video seems to work fine. However, when I try to share to youtube via the same share screen, it looks like it can't detect the duration of the video :

    


    Youtube detecting zero duration

    


    Another thing to note is that when i download the file, and upload it to youtube via regular web browser, it seems to be fine - which somewhat points to it not being ffmpeg related, but it shares fine to other apps.

    


    I'm using ffmpeg version 5.1.2