Metadata-Version: 2.1
Name: birdvoxclassify
Version: 0.3.0
Summary: Species identification from bird flight call recordings
Home-page: https://github.com/BirdVox/birdvoxclassify
Author: Aurora Cramer, Vincent Lostanlen, Justin Salamon, Andrew Farnsworth, and Juan Pablo Bello
Author-email: jtcramer@nyu.edu
License: MIT
Project-URL: Source, https://github.com/BirdVox/birdvoxclassify
Project-URL: Tracker, https://github.com/BirdVox/birdvoxclassify/issues
Description: # BirdVoxClassify: species classification of bird flight calls
        
        An open-source Python library and command-line tool for classifying bird species from flight calls in audio recordings.
        
        [![PyPI](https://img.shields.io/badge/python-3.5%2C%203.6-blue.svg)]()
        [![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://choosealicense.com/licenses/mit/)
        [![Coverage Status](https://coveralls.io/repos/github/BirdVox/birdvoxclassify/badge.svg)](https://coveralls.io/github/BirdVox/birdvoxclassify)
        [![Build Status](https://travis-ci.org/BirdVox/birdvoxclassify.svg?branch=master)](https://travis-ci.org/BirdVox/birdvoxclassify)
        [![Documentation Status](https://readthedocs.org/projects/birdvoxclassify/badge/?version=latest)](http://birdvoxclassify.readthedocs.io/en/latest/?badge=latest)
        
        BirdVoxClassify is a pre-trained deep learning system for classifying bird species from flight calls in short audio recordings.
        It relies on per-channel energy normalization (PCEN) for improved robustness to background noise.
        It is made available both as a Python library and as a command-line tool for Windows, OS X, and Linux.
        
        The code used to train these models can be found at [this repository](https://github.com/BirdVox/cramer2020icassp).
        
        # Installation instructions
        
        Dependencies
        ------------
        
        #### Python Versions
        Currently, we support Python 3.6, 3.7, and 3.8.
        
        #### libsndfile (Linux only)
        BirdVoxClassify depends on the PySoundFile module to load audio files, which itself depends on the non-Python library libsndfile.
        On Windows and Mac OS X, these will be installed automatically via the ``pip`` package manager and you can therefore skip this step.
        However, on Linux, `libsndfile` must be installed manually via your platform's package manager.
        For Debian-based distributions (such as Ubuntu), this can be done by simply running
        
            apt-get install libsndfile
        
        For more detailed information, please consult the
        [installation instructions of pysoundfile](https://pysoundfile.readthedocs.io/en/0.9.0/#installation>).
        
        #### Note about TensorFlow:
        We have dropped support for Tensorflow 1.x, and have moved to Tensorflow 2.x.
        
        
        Installing BirdVoxClassify
        ------------------------
        The simplest way to install BirdVoxClassify is by using ``pip``, which will also install the additional required dependencies
        if needed.
        
        To install the latest version of BirdVoxClassify from source:
        
        1. Clone or pull the latest version:
        
                git clone git@github.com:BirdVox/birdvoxclassify.git
        
        2. Install using pip to handle Python dependencies:
        
                cd birdvoxclassify
                pip install -e .
                
                
        ## Contact
        
        Aurora Cramer, New York University (`@auroracramer` on GitHub).
        For more information on the BirdVox project, please visit our website: [https://wp.nyu.edu/birdvox](https://wp.nyu.edu/birdvox)
        
        See the [BirdVox Google Group](https://groups.google.com/g/birdvox) for questions and relevant discussion regarding BirdVox research and tools.
        
        Please cite the following paper when using BirdVoxClassify in your work:
        
        **[Chirping up the Right Tree: Incorporating Biological Taxonomies into Deep Bioacoustic Classifiers](https://www.justinsalamon.com/uploads/4/3/9/4/4394963/cramer_taxonet_icassp_2020.pdf)**<br/>
        Jason Cramer, Vincent Lostanlen, Andrew Farnsworth, Justin Salamon, and Juan Pablo Bello<br/>
        In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.
                
        
Keywords: bioacoustics,audio signal processing,machine learning
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Multimedia :: Sound/Audio :: Analysis
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
Provides-Extra: docs
Provides-Extra: tests
