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The pirate bay depuis la Belgique
1 April 2013, by
Updated: April 2013
Language: français
Type: Picture
Other articles (18)
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Ajouter notes et légendes aux images
7 February 2011, byPour pouvoir ajouter notes et légendes aux images, la première étape est d’installer le plugin "Légendes".
Une fois le plugin activé, vous pouvez le configurer dans l’espace de configuration afin de modifier les droits de création / modification et de suppression des notes. Par défaut seuls les administrateurs du site peuvent ajouter des notes aux images.
Modification lors de l’ajout d’un média
Lors de l’ajout d’un média de type "image" un nouveau bouton apparait au dessus de la prévisualisation (...) -
XMP PHP
13 May 2011, byDixit Wikipedia, XMP signifie :
Extensible Metadata Platform ou XMP est un format de métadonnées basé sur XML utilisé dans les applications PDF, de photographie et de graphisme. Il a été lancé par Adobe Systems en avril 2001 en étant intégré à la version 5.0 d’Adobe Acrobat.
Étant basé sur XML, il gère un ensemble de tags dynamiques pour l’utilisation dans le cadre du Web sémantique.
XMP permet d’enregistrer sous forme d’un document XML des informations relatives à un fichier : titre, auteur, historique (...) -
Les formats acceptés
28 January 2010, byLes commandes suivantes permettent d’avoir des informations sur les formats et codecs gérés par l’installation local de ffmpeg :
ffmpeg -codecs ffmpeg -formats
Les format videos acceptés en entrée
Cette liste est non exhaustive, elle met en exergue les principaux formats utilisés : h264 : H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10 m4v : raw MPEG-4 video format flv : Flash Video (FLV) / Sorenson Spark / Sorenson H.263 Theora wmv :
Les formats vidéos de sortie possibles
Dans un premier temps on (...)
On other websites (4651)
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NumPy array of a video changes from the original after writing into the same video
29 March 2021, by 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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FFmpeg get frame rate
22 September 2021, by 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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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 April 2023, by 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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