Metadata-Version: 2.1
Name: torchopenl3
Version: 1.0.0
Summary: Deep audio and image embeddings, based on Look, Listen, and Learn approach Pytorch
Home-page: https://github.com/torchopenl3/torchopenl3/
Author: Humair Raj Khan and Gyanendra Das
Author-email: gyanendralucky9337@gmail.com
License: MIT
Description: # Torchopenl3
        TorchopenL3 is an open-source Python library Pytorch Support for computing deep audio embeddings.
        
        
        [![PyPI](https://img.shields.io/badge/python-3.6%2C%203.7-blue.svg)](https://pypi.python.org/pypi/openl3) [![Build Status](https://travis-ci.org/turian/torchopenl3.png?branch=main)](https://travis-ci.org/turian/torchopenl3) [![Maintenance](https://img.shields.io/badge/Maintained%3F-yes-green.svg)](https://github.com/turian/torchopenl3/pulse) [![Ask Me Anything !](https://img.shields.io/badge/Ask%20me-anything-1abc9c.svg)](https://GitHub.com/turian/torchopenl3) [![GitHub version](https://badge.fury.io/gh/turian%2Ftorchopenl3.svg)](https://github.com/turian/torchopenl3) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
        
        ## Contributors
        ![GitHub Contributors Image](https://contrib.rocks/image?repo=turian/torchopenl3)
        
        Please refer to the [Openl3 Library](https://github.com/marl/openl3) for keras version.
        
        The audio and image embedding models provided here are published as part of [1], and are based on the Look, Listen and Learn approach [2]. For details about the embedding models and how they were trained, please see:
        
        [Look, Listen and Learn More: Design Choices for Deep Audio Embeddings](http://www.justinsalamon.com/uploads/4/3/9/4/4394963/cramer_looklistenlearnmore_icassp_2019.pdf)<br/>
        Jason Cramer, Ho-Hsiang Wu, Justin Salamon, and Juan Pablo Bello.<br/>
        IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pages 3852â€“3856, Brighton, UK, May 2019.
        
        # Comparasion
        
        We run torchopenl3 over 100 audio files and compare with openl3 embeddings. Below is the MAE (Mean Absolute Error) Table
        
        
        | Content_type | Input_repr | Emd_size |           MAE          |
        |:------------:|:----------:|:--------:|:----------------------:|
        |      Env     |   Linear   |    512   | 1.1522600237867664e-06 |
        |      Env     |   Linear   |   6144   |  1.027089645617707e-06 |
        |      Env     |   Mel128   |    512   | 1.2094695046016568e-06 |
        |      Env     |   Mel128   |   6144   | 1.0968088741947213e-06 |
        |      Env     |   Mel256   |    512   | 1.1641358707947802e-06 |
        |      Env     |   Mel256   |   6144   | 1.0069775197507625e-06 |
        |     Music    |   Linear   |    512   |  1.173499645119591e-06 |
        |     Music    |   Linear   |   6144   |  1.048712784381678e-06 |
        |     Music    |   Mel128   |    512   | 1.1837427564387327e-06 |
        |     Music    |   Mel128   |   6144   | 1.0497348176841115e-06 |
        |     Music    |   Mel256   |    512   | 1.1619711483490392e-06 |
        |     Music    |   Mel256   |   6144   |  9.881532906774738e-07 |
        
        
        # Installation
        [![PyPI](https://img.shields.io/badge/python-3.6%2C%203.7-blue.svg)](https://pypi.python.org/pypi/openl3)  
        Install via pip 
        ```
        pip install git+https://github.com/turian/torchopenl3.git
        ```
        Install the package with all dev libraries (i.e. tensorflow openl3)
        ```
        git clone https://github.com/turian/torchopenl3.git
        pip3 install -e ".[dev]"
        ```
        
        Install Docker and work within the Docker environment.
        Unfortunately this Docker image is quite big (about 4 GB) because
        
        ```
        docker pull turian/torchopenl3
        # Or, build the docker yourself
        #docker build -t turian/torchopenl3 .
        ```
        
        # Using TorchpenL3
        [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1LHbM1WN_1LK61R6XEbUlrtmRb3fKlDov?usp=sharing) 
        
        To help you get started with TorchopenL3 please go through the colab file.
        
        # Acknowledge
        Special Thank you to [Joseph Turian](https://github.com/turain) for his help
        
        [1] [Look, Listen and Learn More: Design Choices for Deep Audio Embeddings](http://www.justinsalamon.com/uploads/4/3/9/4/4394963/cramer\_looklistenlearnmore\_icassp\_2019.pdf)<br/>
        Jason Cramer, Ho-Hsiang Wu, Justin Salamon, and Juan Pablo Bello.<br/>
        IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pages 3852â€“3856, Brighton, UK, May 2019.
        
        [2] [Look, Listen and Learn](http://openaccess.thecvf.com/content\_ICCV\_2017/papers/Arandjelovic\_Look\_Listen\_and\_ICCV\_2017\_paper.pdf)<br/>
        Relja ArandjeloviÄ‡ and Andrew Zisserman<br/>
        IEEE International Conference on Computer Vision (ICCV), Venice, Italy, Oct. 2017.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Multimedia :: Sound/Audio :: Analysis
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: dev
