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Rennes Emotion Map 2010-11
19 octobre 2011, par
Mis à jour : Juillet 2013
Langue : français
Type : Texte
Autres articles (68)
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MediaSPIP 0.1 Beta version
25 avril 2011, parMediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
The zip file provided here only contains the sources of MediaSPIP in its standalone version.
To get a working installation, you must manually install all-software dependencies on the server.
If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...) -
MediaSPIP version 0.1 Beta
16 avril 2011, parMediaSPIP 0.1 beta est la première version de MediaSPIP décrétée comme "utilisable".
Le fichier zip ici présent contient uniquement les sources de MediaSPIP en version standalone.
Pour avoir une installation fonctionnelle, il est nécessaire d’installer manuellement l’ensemble des dépendances logicielles sur le serveur.
Si vous souhaitez utiliser cette archive pour une installation en mode ferme, il vous faudra également procéder à d’autres modifications (...) -
Amélioration de la version de base
13 septembre 2013Jolie 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 (...)
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How to Check Website Traffic As Accurately As Possible
18 août 2023, par Erin — Analytics Tips -
doc/platform : drop reference to ffmpeg.zeranoe.com
28 mars 2023, par Stefano Sabatinidoc/platform : drop reference to ffmpeg.zeranoe.com
It was closed in September 2020.
Fix issue :
http://trac.ffmpeg.org/ticket/9734 -
Unable to open audio file on Heroku using Librosa
15 mars 2020, par Rohan BojjaI have a feature extraction REST API written in Python using the Librosa library (Extracting audio features), it receives an audio file through HTTP POST and responds with a list of features(such as MFCC,etc).
Since librosa depends on SoundFile (libsndfile1 / libsndfile-dev), it doesn’t support all the formats, I’m converting the audio file using ffmpeg-python wrapper (https://kkroening.github.io/ffmpeg-python/) .
It works just fine on my Windows 10 machine with Conda, but when I deploy it on Heroku, the librosa.load() functions returns an unknown format error, no matter what format I convert it to. I have tried FLAC, AIFF and WAV.
My first guess is that the converted format isn’t supported by libsndfile1, but it works on my local server (plus, their documentation says AIFF and WAV are supported), so I’m a little lost.
I have attached all the relevant snippets of code below, I can provide anything extra if necessary. Any help is highly appreciated. Thanks.
UPDATE1 :
I am using pipes instead of writing and reading from disk, worth a mention as the question could be misleading otherwise.
The log :
File "/app/app.py", line 31, in upload
x , sr = librosa.load(audioFile,mono=True,duration=5)
File "/app/.heroku/python/lib/python3.6/site-packages/librosa/core/audio.py", line 164, in load
six.reraise(*sys.exc_info())
File "/app/.heroku/python/lib/python3.6/site-packages/six.py", line 703, in reraise
raise value
File "/app/.heroku/python/lib/python3.6/site-packages/librosa/core/audio.py", line 129, in load
with sf.SoundFile(path) as sf_desc:
File "/app/.heroku/python/lib/python3.6/site-packages/soundfile.py", line 629, in __init__
self._file = self._open(file, mode_int, closefd)
File "/app/.heroku/python/lib/python3.6/site-packages/soundfile.py", line 1184, in _open
"Error opening {0!r}: ".format(self.name))
File "/app/.heroku/python/lib/python3.6/site-packages/soundfile.py", line 1357, in _error_check
raise RuntimeError(prefix + _ffi.string(err_str).decode('utf-8', 'replace'))
RuntimeError: Error opening <_io.BytesIO object at 0x7f46ad28beb8>: File contains data in an unknown format.
10.69.244.94 - - [15/Mar/2020:12:37:28 +0000] "POST /receiveWav HTTP/1.1" 500 290 "-" "curl/7.55.1"Flask/Librosa code deployed on Heroku (app.py) :
from flask import Flask, jsonify, request
import scipy.optimize
import os,pickle
import numpy as np
from sklearn.preprocessing import StandardScaler
import librosa
import logging
import soundfile as sf
from pydub import AudioSegment
import subprocess as sp
import ffmpeg
from io import BytesIO
logging.basicConfig(level=logging.DEBUG)
app = Flask(__name__)
@app.route('/receiveWav',methods = ['POST'])
def upload():
if(request.method == 'POST'):
f = request.files['file']
app.logger.info(f'AUDIO FORMAT\n\n\n\n\n\n\n\n\n\n: {f}')
proc = (
ffmpeg.input('pipe:')
.output('pipe:', format='aiff')
.run_async(pipe_stdin=True,pipe_stdout=True, pipe_stderr=True)
)
audioFile,err = proc.communicate(input=f.read())
audioFile = BytesIO(audioFile)
scaler = pickle.load(open("scaler.ok","rb"))
x , sr = librosa.load(audioFile,mono=True,duration=5)
y=x
#Extract the features
chroma_stft = librosa.feature.chroma_stft(y=y, sr=sr)
spec_cent = librosa.feature.spectral_centroid(y=y, sr=sr)
spec_bw = librosa.feature.spectral_bandwidth(y=y, sr=sr)
rolloff = librosa.feature.spectral_rolloff(y=y, sr=sr)
zcr = librosa.feature.zero_crossing_rate(y)
rmse = librosa.feature.rms(y=y)
mfcc = librosa.feature.mfcc(y=y, sr=sr)
features = f'{np.mean(chroma_stft)} {np.mean(rmse)} {np.mean(spec_cent)} {np.mean(spec_bw)} {np.mean(rolloff)} {np.mean(zcr)}'
for e in mfcc:
features += f' {np.mean(e)}'
input_data2 = np.array([float(i) for i in features.split(" ")]).reshape(1,-1)
input_data2 = scaler.transform(input_data2)
return jsonify(input_data2.tolist())
# driver function
if __name__ == '__main__':
app.run(debug = True)Aptfile :
libsndfile1
libsndfile-dev
libav-tools
libavcodec-extra-53
libavcodec-extra-53
ffmpegrequirements.txt :
aniso8601==8.0.0
audioread==2.1.8
certifi==2019.11.28
cffi==1.14.0
Click==7.0
decorator==4.4.2
ffmpeg-python==0.2.0
Flask==1.1.1
Flask-RESTful==0.3.8
future==0.18.2
gunicorn==20.0.4
itsdangerous==1.1.0
Jinja2==2.11.1
joblib==0.14.1
librosa==0.7.2
llvmlite==0.31.0
MarkupSafe==1.1.1
marshmallow==3.2.2
numba==0.48.0
numpy==1.18.1
pycparser==2.20
pydub==0.23.1
pytz==2019.3
resampy==0.2.2
scikit-learn==0.22.2.post1
scipy==1.4.1
six==1.14.0
SoundFile==0.10.3.post1
Werkzeug==1.0.0
wincertstore==0.2