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    13 septembre 2013

    Jolie sélection multiple
    Le plugin Chosen permet d’améliorer l’ergonomie des champs de sélection multiple. Voir les deux images suivantes pour comparer.
    Il suffit pour cela d’activer le plugin Chosen (Configuration générale du site > Gestion des plugins), puis de configurer le plugin (Les squelettes > Chosen) en activant l’utilisation de Chosen dans le site public et en spécifiant les éléments de formulaires à améliorer, par exemple select[multiple] pour les listes à sélection multiple (...)

  • Le plugin : Gestion de la mutualisation

    2 mars 2010, par

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  • Gestion de la ferme

    2 mars 2010, par

    La ferme est gérée dans son ensemble par des "super admins".
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Sur d’autres sites (4544)

  • Could not read frame error when trying to decompress mp4 file with ffmpeg and Python's threading module

    23 janvier 2017, par mdornfe1

    I’m training constitutional neural networks with video data. So far the bottle neck of my application is decompressing the mp4 files before passing the images to the CNN for training. I had the idea to try to have multiple cpu threads decompress the images concurrently and having one thread pass images to the CNN for training. I made a class VideoStream which makes connection to the mp4 file using the ImageIO module which is built on top of ffmpeg. The structure of my program is a follows :

    1) Generate random ints which represent the frame numbers of the mp4 file that will be used in training. Store these ints in list frame_idxs.

    2) Pass this list of ints and an empty list called frame_queue to the worker function decompress_video_data.

    3) Each worker function makes a connection to the mp4 file using VideoStream.

    4) Each worker function then pops of elements of frame_idxs, decompresses that frame, and then stores that frame as numpy array in list frame_queue.

    Here is the code

    import numpy as np
    import os, threading, multiprocessing


    def decompress_video_data(frame_queue, frame_idxs, full_path):
       vs = VideoStream(full_path)
       while len(frame_idxs) >1 0:
           i = frame_idxs.pop()
           frame = vs[i]
           frame_queue.append(frame)

    video_folder = '/mnt/data_drive/frame_viewer_client'
    video_files = os.listdir(video_folder)
    video_file = video_files[0]
    full_path = os.path.join(video_folder, video_file)
    vs = VideoStream(full_path)

    num_samples = 1000
    batch_size = 1
    frame_queue = []
    decompress_threads = []
    frame_idxs = list(np.random.randint(0, len(vs),
       size = batch_size * num_samples))
    num_cores = multiprocessing.cpu_count()

    for n in range(num_cores - 1):
       decompress_thread = threading.Thread(target=decompress_video_data,
           args=(frame_queue, frame_idxs, full_path))
       decompress_threads.append(decompress_thread)
       decompress_thread.start()

    The program will sucessfuly decompress approximately 200 frames, and then ImageIO will throw an RuntimeError : Could not read frame. The full error is here. Does anyone know why this is happening ? Is it possible to do what I’m trying to do ? Does ffmpeg just not work with multi threading ?

  • Transcoding Mp4 video on Android with FFMPEG

    18 octobre 2012, par geeknizer

    I've compiled FFMPEG binary from Bambuser project (refer question) and have pushed binary and .so files to application directory.

    But when I try running FFMPEG with input file, it always complains file not found.

    1|root@android:/data/data/com.bambuser.broadcaster # ls                        
    cache           libavcodec.so   libavfilter.so  libswscale.so
    ffmpeg          libavcore.so    libavformat.so  tutorial.mp4
    lib             libavdevice.so  libavutil.so
    1|root@android:/data/data/com.bambuser.broadcaster # ./ffmpeg -i tutorial.mp4 out.mp4                                                              
    FFmpeg version UNKNOWN, Copyright (c) 2000-2010 the FFmpeg developers
     built on May  8 2012 10:11:37 with gcc 4.4.3
     configuration: --target-os=linux --cross-prefix=arm-linux-androideabi- --arch=arm --sysroot=/home/tarandeep/tools/android-ndk/platforms/android-3/arch-arm --soname-prefix=/data/data/com.bambuser.broadcaster/lib/ --enable-shared --disable-symver --enable-small --optimization-flags=-O2 --disable-everything --enable-encoder=mpeg2video --enable-encoder=nellymoser --prefix=../build/ffmpeg/armeabi-v7a --extra-cflags=&#39;-march=armv7-a -mfloat-abi=softfp&#39; --extra-ldflags=
     libavutil     50.34. 0 / 50.34. 0
     libavcore      0.16. 0 /  0.16. 0
     libavcodec    52.99. 1 / 52.99. 1
     libavformat   52.88. 0 / 52.88. 0
     libavdevice   52. 2. 2 / 52. 2. 2
     libavfilter    1.69. 0 /  1.69. 0
     libswscale     0.12. 0 /  0.12. 0
    tutorial.mp4: No such file or directory

    I've tried placing file in /sdcard and other locations, I always get same output

  • Analytics for ePortfolios, Mahara hui conference

    20 mars 2014, par Matthieu Aubry — Community, Meta

    I was privileged to present at the Mahara Hui conference in Wellington, New Zealand.

    Here are the slides of my presentation “Analytics for ePortfolios” :

    Summary : by using an analytics tool that integrates well with Mahara, such as Piwik, Mahara users can benefit from a multitude of insightful analytics reports.

    Learn more

    Mahara is a web application to build your electronic portfolio. You can create journals, upload files, embed social media resources from the web and collaborate with other users in groups. Mahara is a popular open source project built by a passionate community, and used in universities, schools and companies all over the world.

    Mahara Hui is the first kiwi conference on Mahara, the open source ePortfolio system, in New Zealand. This 2-day conference was held at Te Papa in Wellington from 19 to 20 March 2014 (schedule)

    Next steps

    I’m excited to join the Mahara team at the Mahara Hui Hackfest organised today at Catalyst IT offices. We will brainstorm how to integrate Piwik beautifully within Mahara, and how to ultimately provide students and employees useful analytics on all the content they create !