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Exemple de boutons d’action pour une collection collaborative
27 février 2013, par
Mis à jour : Mars 2013
Langue : français
Type : Image
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Exemple de boutons d’action pour une collection personnelle
27 février 2013, par
Mis à jour : Février 2013
Langue : English
Type : Image
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Collections - Formulaire de création rapide
19 février 2013, par
Mis à jour : Février 2013
Langue : français
Type : Image
Autres articles (47)
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Keeping control of your media in your hands
13 avril 2011, parThe vocabulary used on this site and around MediaSPIP in general, aims to avoid reference to Web 2.0 and the companies that profit from media-sharing.
While using MediaSPIP, you are invited to avoid using words like "Brand", "Cloud" and "Market".
MediaSPIP is designed to facilitate the sharing of creative media online, while allowing authors to retain complete control of their work.
MediaSPIP aims to be accessible to as many people as possible and development is based on expanding the (...) -
Personnaliser les catégories
21 juin 2013, parFormulaire de création d’une catégorie
Pour ceux qui connaissent bien SPIP, une catégorie peut être assimilée à une rubrique.
Dans le cas d’un document de type catégorie, les champs proposés par défaut sont : Texte
On peut modifier ce formulaire dans la partie :
Administration > Configuration des masques de formulaire.
Dans le cas d’un document de type média, les champs non affichés par défaut sont : Descriptif rapide
Par ailleurs, c’est dans cette partie configuration qu’on peut indiquer le (...) -
Publier sur MédiaSpip
13 juin 2013Puis-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
Sur d’autres sites (6415)
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Can I use the file buffer or stream as input for fluent-ffmpeg ? I am trying to avoid saving the video locally to get its path before removing
22 avril 2023, par Moath ThawahrehI am receiving the file via an api, I was trying to process the file.buffer as input for FFmpeg but it did not work, I had to save the video locally first and then process the path and remove the saved video later on.
I don't want to believe that there is no other way to solve this and I have been looking for solutions and workarounds but it was all about ffmpeg input as a path.


I would love to find a solution using fluent-ffmpeg because it has some other great features, but I won't mind any suggestions for compressing the video using any different approaches if it's more efficient


Again my code below works fine but I have to save the video and then remove it I am hoping for a more efficient solution :


fs.writeFileSync('temp.mp4', file.buffer);

 // Resize the temporary file using ffmpeg
 ffmpeg('temp.mp4') // here I tried pass file.buffer as readable stream,it receives paths only 
 .format('mp4')
 .size('50%')
 .save('resized.mp4')
 .on('end', async () => {
 // Upload the resized file to Firebase
 const resizedFileStream = bucket.file(`video/${uniqueId}`).createWriteStream();
 fs.createReadStream('resized.mp4').pipe(resizedFileStream);

 await new Promise<void>((resolve, reject) => {
 resizedFileStream
 .on('finish', () => {
 // Remove the local files after they have been uploaded
 fs.unlinkSync('temp.mp4');
 fs.unlinkSync('resized.mp4');
 resolve();
 })
 .on('error', reject);
 });

 // Get the URL of the uploaded resized version
 const resizedFile = bucket.file(`video/${uniqueId}`);
 const url = await resizedFile.getSignedUrl({
 action: 'read',
 expires: '03-17-2025', // Change this to a reasonable expiration date
 });

 console.log('Resized file uploaded successfully.');
 })
 .on('error', (err) => {
 console.log('An error occurred: ' + err.message);
 });
</void>

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FFmpeg get frame rate
22 septembre 2021, par zhin dinsI have several images and I am reproducing them in 78.7ms, I am creating like the 80s video effect. But, I am unable to find the correct ms, and this images with the original videos are unsync.


I dumped the video to images using this command => ffmpeg -i *.mp4 the80effect/img-%d.jpg And now, I have 48622 frames. The video FPS is 24


So, 48622/24 = 2025 +- I cannot use 2025ms since those images will load very slow. And the and the approximate value is 78.7ms per frame/image


How can I find the correct value ? The video duration in seconds is 2026. I have tried all math to find this but I'm failing. How many images (one frame) per msCould you help me ? Thank you.


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NumPy array of a video changes from the original after writing into the same video
29 mars 2021, par RashiqI have a video (
test.mkv) that I have converted into a 4D NumPy array - (frame, height, width, color_channel). I have even managed to convert that array back into the same video (test_2.mkv) without altering anything. However, after reading this new,test_2.mkv, back into a new NumPy array, the array of the first video is different from the second video's array i.e. their hashes don't match and thenumpy.array_equal()function returns false. I have tried using both python-ffmpeg and scikit-video but cannot get the arrays to match.

Python-ffmpeg attempt :


import ffmpeg
import numpy as np
import hashlib

file_name = 'test.mkv'

# Get video dimensions and framerate
probe = ffmpeg.probe(file_name)
video_stream = next((stream for stream in probe['streams'] if stream['codec_type'] == 'video'), None)
width = int(video_stream['width'])
height = int(video_stream['height'])
frame_rate = video_stream['avg_frame_rate']

# Read video into buffer
out, error = (
 ffmpeg
 .input(file_name, threads=120)
 .output("pipe:", format='rawvideo', pix_fmt='rgb24')
 .run(capture_stdout=True)
)

# Convert video buffer to array
video = (
 np
 .frombuffer(out, np.uint8)
 .reshape([-1, height, width, 3])
)

# Convert array to buffer
video_buffer = (
 np.ndarray
 .flatten(video)
 .tobytes()
)

# Write buffer back into a video
process = (
 ffmpeg
 .input('pipe:', format='rawvideo', s='{}x{}'.format(width, height))
 .output("test_2.mkv", r=frame_rate)
 .overwrite_output()
 .run_async(pipe_stdin=True)
)
process.communicate(input=video_buffer)

# Read the newly written video
out_2, error = (
 ffmpeg
 .input("test_2.mkv", threads=40)
 .output("pipe:", format='rawvideo', pix_fmt='rgb24')
 .run(capture_stdout=True)
)

# Convert new video into array
video_2 = (
 np
 .frombuffer(out_2, np.uint8)
 .reshape([-1, height, width, 3])
)

# Video dimesions change
print(f'{video.shape} vs {video_2.shape}') # (844, 1080, 608, 3) vs (2025, 1080, 608, 3)
print(f'{np.array_equal(video, video_2)}') # False

# Hashes don't match
print(hashlib.sha256(bytes(video_2)).digest()) # b'\x88\x00\xc8\x0ed\x84!\x01\x9e\x08 \xd0U\x9a(\x02\x0b-\xeeA\xecU\xf7\xad0xa\x9e\\\xbck\xc3'
print(hashlib.sha256(bytes(video)).digest()) # b'\x9d\xc1\x07xh\x1b\x04I\xed\x906\xe57\xba\xf3\xf1k\x08\xfa\xf1\xfaM\x9a\xcf\xa9\t8\xf0\xc9\t\xa9\xb7'


Scikit-video attempt :


import skvideo.io as sk
import numpy as np

video_data = sk.vread('test.mkv')

sk.vwrite('test_2_ski.mkv', video_data)

video_data_2 = sk.vread('test_2_ski.mkv')

# Dimensions match but...
print(video_data.shape) # (844, 1080, 608, 3)
print(video_data_2.shape) # (844, 1080, 608, 3)

# ...array elements don't
print(np.array_equal(video_data, video_data_2)) # False

# Hashes don't match either
print(hashlib.sha256(bytes(video_2)).digest()) # b'\x8b?]\x8epD:\xd9B\x14\xc7\xba\xect\x15G\xfaRP\xde\xad&EC\x15\xc3\x07\n{a[\x80'
print(hashlib.sha256(bytes(video)).digest()) # b'\x9d\xc1\x07xh\x1b\x04I\xed\x906\xe57\xba\xf3\xf1k\x08\xfa\xf1\xfaM\x9a\xcf\xa9\t8\xf0\xc9\t\xa9\xb7'


I don't understand where I'm going wrong and both the respective documentations do not highlight how to do this particular task. Any help is appreciated. Thank you.


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