https://github.com/csteinmetz1/pyloudnorm-eval
Evaluation of a number of loudness meter implementations
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.9%) to scientific vocabulary
Repository
Evaluation of a number of loudness meter implementations
Basic Info
- Host: GitHub
- Owner: csteinmetz1
- License: apache-2.0
- Language: Python
- Default Branch: main
- Size: 48.3 MB
Statistics
- Stars: 11
- Watchers: 2
- Forks: 1
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Setup
Install essentia (macOS)
You will need homebrew.
brew tap MTG/essentia
brew install essentia --HEAD
For other platforms, please refer to the essentia docs.
Install loudness.py
The original repo is located here: https://github.com/BrechtDeMan/loudness.py.git.
However, there are a few issues that make it difficult to run via our testbench.
Therefore, we will install via our branch, which has a few changes, but doesn't change the algorithm implementation.
git clone https://github.com/csteinmetz1/loudness.py.git
mv loudness.py loudness_py
Note you need to rename the resulting directory so it can be imported.
Install loudness-scanner
git clone git://github.com/jiixyj/loudness-scanner.git
cd loudness-scanner
git submodule init
git submodule update
mkdir build
cd build
cmake ..
make
In order to use essentia make sure you create an environment in the following manner. Make sure to go back to the top level directory first.
cd ../.. # go back up
python3 -m venv env/ --system-site-packages
source env/bin/activate
pip install -r requirements.txt
Data
Run
Now run the evaluation, which will measure the loudness of all files in the data/ directory and store the results in a text file.
This should take around 60 seconds.
python eval.py > results.txt
Optionally, you can run the fine-detail frequency test,
python eval.py -f
of the speed test to produce timings on your platform.
python eval.py -s
Citation
If you use pyloudnorm or this evaluation in your work please consider citing us.
@inproceedings{steinmetz2021pyloudnorm, title={pyloudnorm: {A} simple yet flexible loudness meter in Python}, author={Steinmetz, Christian J. and Reiss, Joshua D.}, booktitle={150th AES Convention} year={2021}}
Owner
- Name: Christian J. Steinmetz
- Login: csteinmetz1
- Kind: user
- Location: London, UK
- Company: @aim-qmul
- Website: christiansteinmetz.com
- Twitter: csteinmetz1
- Repositories: 79
- Profile: https://github.com/csteinmetz1
Machine learning for Hi-Fi audio. PhD Researcher at C4DM.
GitHub Events
Total
- Watch event: 3
Last Year
- Watch event: 3
Issues and Pull Requests
Last synced: over 1 year ago
All Time
- Total issues: 2
- Total pull requests: 0
- Average time to close issues: 1 day
- Average time to close pull requests: N/A
- Total issue authors: 1
- Total pull request authors: 0
- Average comments per issue: 1.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- dbogdanov (2)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- Pillow >=8.2.0
- PySoundFile ==0.9.0.post1
- cffi ==1.14.4
- cycler ==0.10.0
- future ==0.18.2
- kiwisolver ==1.3.1
- matplotlib ==3.3.3
- numpy ==1.21.2
- pycparser ==2.20
- pyloudnorm ==0.1.0
- pyparsing ==2.4.7
- python-dateutil ==2.8.1
- scipy ==1.6.0
- six ==1.15.0