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The Great Big Beautiful Tomorrow
28 octobre 2011, par
Mis à jour : Octobre 2011
Langue : English
Type : Texte
Autres articles (24)
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Supporting all media types
13 avril 2011, parUnlike most software and media-sharing platforms, MediaSPIP aims to manage as many different media types as possible. The following are just a few examples from an ever-expanding list of supported formats : images : png, gif, jpg, bmp and more audio : MP3, Ogg, Wav and more video : AVI, MP4, OGV, mpg, mov, wmv and more text, code and other data : OpenOffice, Microsoft Office (Word, PowerPoint, Excel), web (html, CSS), LaTeX, Google Earth and (...)
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ANNEXE : Les plugins utilisés spécifiquement pour la ferme
5 mars 2010, parLe site central/maître de la ferme a besoin d’utiliser plusieurs plugins supplémentaires vis à vis des canaux pour son bon fonctionnement. le plugin Gestion de la mutualisation ; le plugin inscription3 pour gérer les inscriptions et les demandes de création d’instance de mutualisation dès l’inscription des utilisateurs ; le plugin verifier qui fournit une API de vérification des champs (utilisé par inscription3) ; le plugin champs extras v2 nécessité par inscription3 (...)
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Encoding and processing into web-friendly formats
13 avril 2011, parMediaSPIP automatically converts uploaded files to internet-compatible formats.
Video files are encoded in MP4, Ogv and WebM (supported by HTML5) and MP4 (supported by Flash).
Audio files are encoded in MP3 and Ogg (supported by HTML5) and MP3 (supported by Flash).
Where possible, text is analyzed in order to retrieve the data needed for search engine detection, and then exported as a series of image files.
All uploaded files are stored online in their original format, so you can (...)
Sur d’autres sites (3781)
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dashenc : allow assigning all streams of a media type to an AdaptationSet
29 janvier 2017, par Peter Großedashenc : allow assigning all streams of a media type to an AdaptationSet
Using the characters "v" or "a" instead of stream index numbers for assigning
streams in the adaption_set option, all streams matching that given type will
be added to the AdaptationSet.Signed-off-by : Peter Große <pegro@friiks.de>
Signed-off-by : Martin Storsjö <martin@martin.st> -
Could not read frame error when trying to decompress mp4 file with ffmpeg and Python's threading module
23 janvier 2017, par mdornfe1I’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 ?
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OCPA, FDBR and TDPSA – What you need to know about the US’s new privacy laws
22 juillet 2024, par Daniel Crough