Acoustic Scene Classification
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Acoustic Scene Auditory (ASC) using Convolutional Neural Network (CNN) is a project being part of the Machine Learning Nanodegreen program given by Udacity. For a description of the proposal, you can refer to its web version.
Dataset
The dataset can be downloaded on the Zenodo server.
Features
TODO
Credits
Project created by Matthieu Berjon and based on the work of Simone Battaglino, Ludovick Lepauloux and Nicholas Evans.
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
History
0.3.1 (2017-08-22)
Added
Issue #8: config file feature
Issue #11: Samplerate setting up through CLI
Issue #10: Spectrogram calculation
Issue #24: Add a ‘config’ subcommand to the CLI
Issue #25: Read a value from the config file
Issue #21: Script to verify the samplerate sanity of the database
Issue #30: Function to transform milliseconds to samples
Changed
Deprecated
Nothing.
Removed
Nothing.
Fixed
Security
Update of the Coveralls library from 1.1 to 1.2.0
0.2.3 (2017-08-07)
Added
Changed
Python 3.3 testing removed
Deprecated
Nothing
Removed
Nothing
Fixed
Security
Nothing
0.2.2 (2017-07-31)
Added
nothing
Changed
Updated of the ChangeLog (HISTORY.rst)
Deprecated
nothing
Removed
nothing
Fixed
nothing
Security
nothing
0.2.1 (2017-07-31)
Added
nothing
Changed
nothing
Deprecated
nothing
Removed
nothing
Fixed
unzip_data() url list issue
download of temporary files in the right directory
Security
nothing
0.2.0 (2017-07-31)
Added
Adding of a documentation (with docstrings)
CLI command to download and unzip data automatically
creation of a python package
configuration of Tox
download() method in data class
Changed
Use of RST instead of markdown for all the documentation
development packages are now in requirements_dev.txt
Deprecated
nothing
Removed
nothing
Fixed
source files satisfy PEP8
bug fix on getdata cli
Security
Update of all packages to their latest versions
0.1.0 (2017-07-25)
First release as a package.
1 maintainer
Release files for asc 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| asc-0.3.1.tar.gz | 30.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| asc-0.3.1-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 42.5 kB
Release files / asc-0.3.1.tar.gz
| Download URL | asc-0.3.1.tar.gz |
|---|---|
| Size | 30.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / asc-0.3.1-py2.py3-none-any.whl
| Download URL | asc-0.3.1-py2.py3-none-any.whl |
|---|---|
| Size | 11.8 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
