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Stereo master soundtrack
17 octobre 2011, par
Mis à jour : Octobre 2011
Langue : English
Type : Audio
Sur d’autres sites (24)
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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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