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Demon Seed
26 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
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Demon seed (wav version)
26 septembre 2011, par
Mis à jour : Avril 2013
Langue : English
Type : Audio
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The four of us are dying (wav version)
26 septembre 2011, par
Mis à jour : Avril 2013
Langue : English
Type : Audio
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Corona radiata (wav version)
26 septembre 2011, par
Mis à jour : Avril 2013
Langue : English
Type : Audio
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26 septembre 2011, par
Mis à jour : Avril 2013
Langue : English
Type : Audio
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26 septembre 2011, par
Mis à jour : Avril 2013
Langue : English
Type : Audio
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Sur d’autres sites (11790)
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ffmpeg - how to use pipe with amovie parameter ?
19 février 2018, par user1347009I am looking for a solution to overlay to mp3 files in which the longer one will be played in the background and the smaller one will continue to play like a loop with that.
My current code is working without pipe :ffmpeg -i 'longer.mp3' -filter_complex "amovie='small.mp3:loop=999'[s];[0][s]amix=duration=shortest" new.mp3This code works like a charm but what i want to achieve is this :
curl "any-url-to-api-to-audio-file" | ffmpeg -i 'longer.mp3' -filter_complex "amovie='pipe\:0:loop=999'[s];[0][s]amix=duration=shortest" new.mp3This code is not working and its giving me error as well,
ffmpeg version N-89955-g118e1b0b33 Copyright (c) 2000-2018 the FFmpeg
developers
built with gcc 4.4.7 (GCC) 20120313 (Red Hat 4.4.7-18)
configuration: --enable-openssl --enable-libmp3lame
libavutil 56. 7.100 / 56. 7.100
libavcodec 58. 9.100 / 58. 9.100
libavformat 58. 7.100 / 58. 7.100
libavdevice 58. 0.101 / 58. 0.101
libavfilter 7. 11.101 / 7. 11.101
libswscale 5. 0.101 / 5. 0.101
libswresample 3. 0.101 / 3. 0.101
Input #0, mp3, from 'morning_alarm.mp3':
Duration: 00:00:28.06, start: 0.025057, bitrate: 128 kb/s
Stream #0:0: Audio: mp3, 44100 Hz, stereo, s16p, 128 kb/s
Metadata:
encoder : LAME3.97
Side data:
replaygain: track gain - -9.200000, track peak - unknown, album gain - unknown, album peak - unknown,
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:--
0101 5088 101 5088 0 0 28080 0 --:--:-- --:--:-- --:--:-- 160k
Stream mapping:
Stream #0:0 (mp3) -> amix:input0
amix -> Stream #0:0 (libmp3lame)
Press [q] to stop, [?] for help
[Parsed_amovie_0 @ 0x26c76c0] Failed to avformat_open_input 'pipe:0'
[AVFilterGraph @ 0x26c3d80] Error initializing filter 'amovie' with args
'pipe\:0:loop=999'
Error reinitializing filters!
Failed to inject frame into filter network: Invalid data found when
processing input
Error while processing the decoded data for stream #0:0
Conversion failed!All i want to do is to overlay two audio files via command line in which 1st audio file will be longer and the second one will be smaller.
The smaller one will be repeated like a loop till the longer one play.Please tell me how can i do that ?
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What is PII ? Your introduction to personally identifiable information
Most websites you visit collect information about you via tools like Google Analytics and Matomo – sometimes collecting personally identifiable information (PII).
When it comes to PII, people are becoming more concerned about data privacy. Identifiable information can be used for illegal purposes like identity theft and fraud.
So how can you protect yourself as an innocent internet browser ? In the case of website owners – how do you protect users and your company from falling prey to privacy breaches ?
As one of the most trusted analytics companies, we feel our readers would benefit from being as informed as possible about data privacy issues and PII. Learn what it means, and what you can do to keep yours or others’ information safe.
Table of Contents
What does PII stand for ?
PII acronym
PII is an acronym for personally identifiable information.
PII definition
Personally identifiable information (PII) is a term used predominantly in the United States.
The appendix of OMB M-10-23 (Guidance for Agency Use of Third-Party Website and Applications) gives this definition for PII :
“The term ‘personally identifiable information’ refers to information which can be used to distinguish or trace an individual’s identity, such as their name, social security number, biometric records, etc. alone, or when combined with other personal or identifying information which is linked or linkable to a specific individual, such as date and place of birth, mother’s maiden name, etc.”
What can be considered personally identifiable information (PII) ? Some PII examples :
- Full name/usernames
- Home address/mailing address
- Email address
- Credit card numbers
- Date of birth
- Phone numbers
- Login details
- Precise locations
- Account numbers
- Passwords
- Security codes (including biometric records)
- Personal identification numbers
- Driver license number
- Get a more comprehensive list here
What’s non-PII ?
Anonymous information, or information that can’t be traced back to an individual, can be considered non-PII.
Who is affected by the exploitation of PII ?
Anyone can be affected by the exploitation of personal data, where you have identity theft, account fraud and account takeovers. When websites resort to illegally selling or sharing your data and compromising your privacy, the fear is falling victim to such fraudulent activity.
PII can also be an issue when employees have access to the database and the data is not encrypted. For example, anyone working in a bank can access your accounts ; anyone working at Facebook may be able to read your messages. This shows how privacy breaches can easily happen when employees have access to PII.
Website owner’s responsibility for data privacy (PII and analytics)
To respect your website visitor’s privacy, best practice is to avoid collecting PII whenever possible. If you work in an industry which requires people to disclose personal information (e.g. healthcare, security industries, public sector), then you must ensure this data is collected and handled securely.
The US National Institute of Standards and Technology states : “The likelihood of harm caused by a breach involving PII is greatly reduced if an organisation minimises the amount of PII it uses, collects, and stores. For example, an organisation should only request PII in a new form if the PII is absolutely necessary.”
How you’re held accountable remains up to the privacy laws of the country you’re doing business in. Make sure you are fully aware of the privacy and data protection laws that relate specifically to you.
To reduce the risk of privacy breaches, try collecting as little PII as you can ; purging it as soon as you can ; and making sure your IT security is updated and protected against security threats.
If you’re using data collection tools like web analytics, data may be tracked through features like User ID, custom variables, and custom dimensions. Sometimes they are also harder to identify when they are present, for example, in page URLs, page titles, or referrers URLs. So make sure you’re optimising your web analytics tools’ settings to ensure you’re asking your users for consent and respecting users’ privacy.
PII, GDPR and businesses in the US/EU
Because PII is broad, you may run into confusion when considering PII and GDPR (which applies in the EU). The General Data Protection Regulation (GDPR) provides more safeguards for user privacy.
GDPR grants people in the EU more rights concerning their “personal data” (more on PII vs personal data below). In the EU the GDPR restricts the collection and processing of personal data. The repercussions are severe penalties and fines for privacy infringements. Businesses are required to handle this personal data carefully. You can be fined up to 4% of their yearly revenue for data breaches or non-compliance.
Although there isn’t an overarching data protection law in the US, there are hundreds of laws on both the federal and state levels to protect the personal data of US residents. US Congress has also enacted industry-specific statutes related to data privacy, and the state of California passed the California Consumer Privacy Act.
To be on the safe side, if you are using analytics, follow matters relating to “personal data” in the GDPR. It’s all-encompassing when it comes to protecting user privacy. GDPR rules still apply whenever an EU citizen visits any non EU site (that processes personal data).
Personally identifiable information (PII) vs personal data
PII and “personal data” aren’t used interchangeably. All personal data can be PII, but not all PII can be defined as personal data.
The definition of “personal data” according to the GDPR :
This means “personal data” encompasses a greater number of identifiers which include the online sphere. Examples include : IP addresses and URL names. As well as seemingly “innocent” data like height, job position, company etc.
What’s considered personal data depends on the context. If a piece of information can be combined with others to establish someone’s identity then that can be considered personal data.
Under GDPR, when processing personal data, you need explicit consent. You need to ensure you’re compliant according to GDPR definitions of “personal data” not just what’s considered “PII”.
How Matomo deals with PII and personal data
Although Matomo Analytics is a web analytics software that tracks user activity on your website, we take privacy and PII very seriously – on both our Cloud and On-Premise offerings.
If you’re using Matomo and would like to know how you can be fully GDPR compliant and protect user privacy, read more :
- Learn how to not process any personally identifiable information – Anonymise IP addresses, user IDs, and order IDs
- Matomo protects user privacy by talking the talk and walking the walk
- Stay ahead of the GDPR with a privacy-respecting analytics platform
- 11 ways Matomo helps you protect your visitor’s privacy
Disclaimer
We are not lawyers and don’t claim to be. The information provided here is to help give an introduction to issues you may encounter when dealing with PII. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns.
Additional resources :
- https://www.consumeraffairs.com/finance/identity-theft-statistics.html#identity-theft-trends-in-2019
- https://ec.europa.eu/info/law/law-topic/data-protection_en
- https://iclg.com/practice-areas/data-protection-laws-and-regulations/usa
- https://www.csoonline.com/article/3215864/how-to-protect-personally-identifiable-information-pii-under-gdpr.html
- https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/key-definitions/what-is-personal-data/
-
Error installing package in anaconda : Attempted to make prefix record for unknown package type
25 janvier 2020, par ashwinidsI’m getting the error below for doing any operation install, update or uninstall
ERROR conda.core.link:_execute(700) : An error occurred while
uninstalling package ’::ffmpeg-3.2.4-2’. Rolling back
transaction : doneValueError(’Attempted to make prefix record for unknown package type :
ffmpeg-3.2.4-2’,)Details about the environment :
OS : ubuntu 18.04
python version : intelpython3Conda info
active environment : base
active env location : /home/p****/intelpython3
shell level : 1
user config file : /home/p****/.condarc
populated config files : /home/p****/.condarc
conda version : 4.7.12
conda-build version : not installed
python version : 3.6.8.final.0
virtual packages : __cuda=10.1
base environment : /home/p****/intelpython3 (writable)
channel URLs : https://conda.anaconda.org/intel/linux-64
https://conda.anaconda.org/intel/noarch
https://repo.anaconda.com/pkgs/main/linux-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/r/linux-64
https://repo.anaconda.com/pkgs/r/noarch
package cache : /home/p****/intelpython3/pkgs
/home/p****/.conda/pkgs
envs directories : /home/p****/intelpython3/envs
/home/p****/.conda/envs
platform : linux-64
user-agent : conda/4.7.12 requests/2.20.1 CPython/3.6.8 Linux/5.0.0-36-generic ubuntu/18.04.3 glibc/2.27
UID:GID : 1000:1000
netrc file : None
offline mode : FalseConda list
# packages in environment at /home/p****/intelpython3:
#
# Name Version Build Channel
_tflow_select 2.1.0 gpu anaconda
absl-py 0.8.0 py36_0 anaconda
affine 2.3.0 pypi_0 pypi
asn1crypto 0.24.0 py36_3 intel
astor 0.8.0 py36_0 anaconda
atomicwrites 1.3.0 pypi_0 pypi
attrs 19.3.0 pypi_0 pypi
audioread 2.1.6 py36_0 <unknown>
awscli 1.16.292 pypi_0 pypi
backcall 0.1.0 py36_2 <unknown>
backports 1.0 py36_9 <unknown>
bayesian-optimization 1.0.1 pypi_0 pypi
bleach 2.1.3 py36_2 <unknown>
boto3 1.10.19 pypi_0 pypi
botocore 1.13.28 pypi_0 pypi
bzip2 1.0.6 17 intel
c-ares 1.15.0 h7b6447c_1001 anaconda
causalgraphicalmodels 0.0.4 pypi_0 pypi
certifi 2018.1.18 py36_2 intel
cffi 1.11.5 py36_3 intel
chardet 3.0.4 py36_3 intel
click 7.0 pypi_0 pypi
click-plugins 1.1.1 pypi_0 pypi
cligj 0.5.0 pypi_0 pypi
colorama 0.4.1 pypi_0 pypi
conda 4.7.12 py36_0
conda-env 2.6.0 1
conda-package-handling 1.6.0 py36h7b6447c_0 anaconda
cryptography 2.3 py36_1 intel
cudatoolkit 10.1.243 h6bb024c_0
cudnn 7.6.0 cuda10.1_0 anaconda
cupti 10.1.168 0 anaconda
cvxopt 1.2.3 pypi_0 pypi
cycler 0.10.0 py36_7 intel
cython 0.29.6 py36h7b7c402_0 intel
daal 2019.4 intel_243 <unknown>
daal4py 2019.4 py36h7b7c402_0 intel
dbus 1.13.12 h746ee38_0
decorator 4.3.0 py36_3 <unknown>
descartes 1.1.0 pypi_0 pypi
docutils 0.15.2 pypi_0 pypi
dowhy 0.1.1 pypi_0 pypi
entrypoints 0.2.3 py36_2 <unknown>
expat 2.2.6 he6710b0_0
ffmpeg 3.2.4 2 <unknown>
fiona 1.8.11 pypi_0 pypi
fontconfig 2.12.6 h49f89f6_0
freetype 2.8 hab7d2ae_1
funcsigs 1.0.2 py36_7 intel
gast 0.3.2 py_0 anaconda
geopandas 0.6.2 pypi_0 pypi
get_terminal_size 1.0.0 py36_7 <unknown>
glib 2.63.1 h5a9c865_0
google-pasta 0.1.7 py_0 anaconda
grpcio 1.14.1 py36h9ba97e2_0 anaconda
gst-plugins-base 1.12.4 h33fb286_0
gstreamer 1.12.4 hb53b477_0
h5py 2.9.0 py36h7918eee_0 anaconda
hdf5 1.10.4 hb1b8bf9_0 anaconda
html5lib 1.0.1 py36_4 <unknown>
icc_rt 2019.4 intel_243 <unknown>
icu 58.2 h9c2bf20_1
idna 2.6 py36_3 intel
imageio 2.6.1 pypi_0 pypi
imgaug 0.2.6 pypi_0 pypi
impi_rt 2019.4 intel_243 <unknown>
importlib-metadata 0.23 pypi_0 pypi
intel-openmp 2019.4 intel_243 <unknown>
intelpython 2019.4 0 intel
ipp 2019.4 intel_243 <unknown>
ipykernel 4.6.1 py36_2 <unknown>
ipython 6.3.1 py36_3 <unknown>
ipython_genutils 0.2.0 py36_2 <unknown>
jedi 0.12.0 py36_2 <unknown>
jinja2 2.10.3 pypi_0 pypi
jmespath 0.9.4 pypi_0 pypi
joblib 0.13.2 pypi_0 pypi
jpeg 9b h024ee3a_2
json5 0.8.5 pypi_0 pypi
jsonschema 3.2.0 pypi_0 pypi
jupyter 1.0.0 py36_7 intel
jupyter_client 5.1.0 py36_5 <unknown>
jupyter_console 5.1.0 py36_2 <unknown>
jupyter_core 4.4.0 py36_6 <unknown>
jupyterlab 1.2.3 pypi_0 pypi
jupyterlab-server 1.0.6 pypi_0 pypi
keras 2.3.1 pypi_0 pypi
keras-applications 1.0.8 py_0 anaconda
keras-bert 0.80.0 pypi_0 pypi
keras-embed-sim 0.7.0 pypi_0 pypi
keras-layer-normalization 0.14.0 pypi_0 pypi
keras-multi-head 0.22.0 pypi_0 pypi
keras-pos-embd 0.11.0 pypi_0 pypi
keras-position-wise-feed-forward 0.6.0 pypi_0 pypi
keras-preprocessing 1.1.0 py_1 anaconda
keras-rectified-adam 0.17.0 pypi_0 pypi
keras-self-attention 0.41.0 pypi_0 pypi
keras-transformer 0.31.0 pypi_0 pypi
kiwisolver 1.0.1 py36_2 intel
libffi 3.2.1 11 intel
libgcc-ng 9.1.0 hdf63c60_0 anaconda
libgfortran-ng 7.3.0 hdf63c60_0 anaconda
libiconv 1.14 4 <unknown>
libpng 1.6.36 2 intel
libprotobuf 3.9.2 hd408876_0 anaconda
librosa 0.6.3 pypi_0 pypi
libsodium 1.0.16 3 <unknown>
libstdcxx-ng 9.1.0 hdf63c60_0 anaconda
libtiff 4.0.9 he85c1e1_1
libxcb 1.13 h1bed415_1
libxml2 2.9.8 hf84eae3_0
lightgbm 2.3.1 pypi_0 pypi
llvmlite 0.27.1 py36_0 intel
markdown 3.1.1 py36_0 anaconda
markupsafe 1.0 py36_3 <unknown>
matplotlib 2.1.0 py36hba5de38_0
mercantile 1.1.2 pypi_0 pypi
metaflow 2.0.0 pypi_0 pypi
mistune 0.8.3 py36_2 <unknown>
mkl 2019.4 intel_243 <unknown>
mkl-service 1.0.0 py36h7b7c402_11 intel
mkl_fft 1.0.11 py36h7b7c402_2 intel
mkl_random 1.0.2 py36h7b7c402_4 intel
more-itertools 7.2.0 pypi_0 pypi
mpi4py 3.0.0 py36_3 intel
mpmath 1.1.0 pypi_0 pypi
munch 2.5.0 pypi_0 pypi
nbconvert 5.2.1 py36_2 <unknown>
nbformat 4.4.0 py36_2 <unknown>
networkx 2.4 pypi_0 pypi
ninja 1.9.0 py36hfd86e86_0
noisyopt 0.2.2 pypi_0 pypi
notebook 5.2.2 py36_1 intel
numba 0.42.1 np116py36_2 intel
numexpr 2.6.8 py36_2 intel
numpy 1.16.2 py36h7b7c402_0 intel
numpy-base 1.16.2 py36_0 intel
oauthlib 3.1.0 pypi_0 pypi
olefile 0.46 py_0
openssl 1.0.2r 2 intel
packaging 19.2 pypi_0 pypi
pandas 0.24.1 py36_3 intel
pandocfilters 1.4.1 py36_2 <unknown>
parso 0.2.0 py36_2 <unknown>
path.py 11.0.1 py36_2 <unknown>
pcre 8.43 he6710b0_0
pexpect 4.2.1 py36_4 <unknown>
pickleshare 0.7.4 py36_3 <unknown>
pillow 6.2.1 pypi_0 pypi
pip 19.3.1 pypi_0 pypi
pluggy 0.13.1 pypi_0 pypi
prompt_toolkit 1.0.15 py36_2 <unknown>
protobuf 3.9.2 py36he6710b0_0 anaconda
ptyprocess 0.5.2 py36_2 <unknown>
pulp 2.0 pypi_0 pypi
py 1.8.0 pypi_0 pypi
pyasn1 0.4.8 pypi_0 pypi
pycosat 0.6.3 py36_3 intel
pycparser 2.18 py36_2 intel
pydot 1.4.1 pypi_0 pypi
pyeditline 2.0.0 py36_0 intel
pygments 2.2.0 py36_5 <unknown>
pygmy 0.2.0 pypi_0 pypi
pyopenssl 17.5.0 py36_2 intel
pyparsing 2.2.0 py36_2 intel
pyportfolioopt 0.4.3 pypi_0 pypi
pyproj 2.4.2.post1 pypi_0 pypi
pyqt 5.6.0 py36h22d08a2_6
pyrsistent 0.15.6 pypi_0 pypi
pysocks 1.6.7 py36_1 intel
pytesseract 0.3.0 pypi_0 pypi
pytest 4.6.6 pypi_0 pypi
python 3.6.8 7 intel
python-dateutil 2.6.0 py36_12 intel
python-graphviz 0.13 pypi_0 pypi
pytorch 1.3.1 py3.6_cuda10.1.243_cudnn7.6.3_0 pytorch
pytz 2018.4 py36_3 intel
pywavelets 1.1.1 pypi_0 pypi
pyyaml 4.1 py36_3 intel
pyzmq 16.0.2 py36_6 <unknown>
qt 5.6.2 hd25b39d_14
rasterio 1.1.1 pypi_0 pypi
regex 2019.11.1 pypi_0 pypi
requests 2.20.1 py36_1 intel
requests-oauthlib 1.3.0 pypi_0 pypi
resampy 0.2.1 pypi_0 pypi
rio-cogeo 1.1.6 pypi_0 pypi
rsa 3.4.2 pypi_0 pypi
ruamel_yaml 0.11.14 py36_4 intel
s3transfer 0.2.1 pypi_0 pypi
sacremoses 0.0.35 pypi_0 pypi
scikit-image 0.16.2 pypi_0 pypi
scikit-learn 0.20.3 py36h7b7c402_5 intel
scipy 1.3.3 pypi_0 pypi
seaborn 0.9.0 pypi_0 pypi
sentencepiece 0.1.83 pypi_0 pypi
setuptools 39.0.1 py36_0 intel
shapely 1.6.4.post2 pypi_0 pypi
simplegeneric 0.8.1 py36_7 <unknown>
sip 4.18.1 py36hf484d3e_2
six 1.11.0 py36_3 intel
smp 0.1.4 py36_0 intel
snuggs 1.4.7 pypi_0 pypi
sqlite 3.27.2 4 intel
supermercado 0.0.5 pypi_0 pypi
sympy 1.4 pypi_0 pypi
tbb 2019.6 intel_243 <unknown>
tbb4py 2019.6 py36_intel_0 <unknown>
tcl 8.6.4 24 intel
tensorboard 1.14.0 py36hf484d3e_0 anaconda
tensorflow 1.14.0 gpu_py36h3fb9ad6_0 anaconda
tensorflow-base 1.14.0 gpu_py36he45bfe2_0 anaconda
tensorflow-estimator 1.14.0 py_0 anaconda
tensorflow-gpu 1.14.0 h0d30ee6_0 anaconda
termcolor 1.1.0 py36_1 anaconda
terminado 0.8.1 py36_2 <unknown>
testpath 0.3.1 py36_2 <unknown>
tk 8.6.4 29 intel
torchvision 0.4.2 py36_cu101 pytorch
tornado 4.5.2 py36_5 <unknown>
tqdm 4.36.1 py_0 anaconda
traitlets 4.3.2 py36_3 <unknown>
transformers 2.1.1 pypi_0 pypi
tweepy 3.8.0 pypi_0 pypi
urllib3 1.22 pypi_0 pypi
wcwidth 0.1.7 py36_6 <unknown>
webencodings 0.5.1 py36_0 <unknown>
werkzeug 0.16.0 py_0 anaconda
wheel 0.31.0 py36_3 intel
widgetsnbextension 3.2.0 py36_1 <unknown>
wrapt 1.11.2 py36h7b6447c_0 anaconda
x264 20131218 0 <unknown>
xgboost 0.81 py36_0 intel
xz 5.2.3 2 intel
yaml 0.1.7 2 intel
zipp 0.6.0 pypi_0 pypi
zlib 1.2.11 5 intel
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