Python packages for audio onset detection Evaluation
In the "src" dir the tool is organised into python packages as followed:-
- Eval : statistical tools for evaluating onsets prediction vs ground-truth
- Predict : global package to generate pool and onsets text files
- OnsetNovelty : package grouping multiple onset novelty functions
- Slice : package grouping multiple multidimensional "peak-picking" algorithms
- Utils : common routines and functions for dealing with files and the environment.
conf.py at the top level holds environment specific things - customise this for your setup.
Specify folders in conf.py
for already computed onset textfiles : run Eval/__init__.py
for computing : specify desired methods in OnsetNovelty's and Slice's __init__.py then run Predict's init.py
you can use last computation using pool cache (basicaly set fromFile=true in config.py)
- Install PyDev
- http://pydev.org/manual_101_install.html
- You may need to install Oracle Java (http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html)
- Then set Java -> Installed JREs -> to Java SE 8
- Restart and in Preferences you should now have PyDev appearing
- Set Interpreters > Python Interpreter to "/usr/local/bin/python" or whatever
- Go to Eclipse Marketplace
- Install EGit
- Pull down code
- Go to File -> Import
- Select "Projects from Git"
- Clone URI "https://github.com/GiantSteps/EvalOnsets"
- Import existing project to your workspace destination
Make sure to set the "src" directory as the PYTHONPATH to detect the packages.
- essentia
- signal
- sklearn
- scypi
- matplotlib
- modal (https://github.com/johnglover/modal)
*opencv