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"info": {
"author": "Aditya Khandkar",
"author_email": "khandkar.adi@gmail.com",
"bugtrack_url": null,
"classifiers": [
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Intended Audience :: End Users/Desktop",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 2.7",
"Programming Language :: Python :: 3.2",
"Programming Language :: Python :: 3.3",
"Programming Language :: Python :: 3.4",
"Programming Language :: Python :: 3.5",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: Implementation :: CPython",
"Topic :: Multimedia :: Sound/Audio :: Analysis",
"Topic :: Multimedia :: Sound/Audio :: Speech",
"Topic :: Software Development :: Libraries :: Python Modules"
],
"description": "Piwho\n=====\n\nPiwho is python wrapper around `MARF `__\nspeaker recognition framework for the Raspberry pi and other SBCs. With\nthe Piwho you can implement speaker recognition in your projects.\n\n.. image:: https://travis-ci.org/Adirockzz95/Piwho.svg?branch=v1.3.0\n :target: https://travis-ci.org/Adirockzz95/Piwho\n\n|\n\n**Blink example**\n\n.. code:: python\n\n\n import RPi.GPIO as GPIO\n import time\n from piwho import recognition, vad\n\n def blink(pin):\n GPIO.setmode(GPIO.BOARD)\n GPIO.setup(pin, GPIO.OUT) \n\n for i in range(0,10):\n GPIO.output(pin,GPIO.HIGH)\n time.sleep(1)\n GPIO.output(pin,GPIO.LOW)\n time.sleep(1)\n \n if __name__ == \"__main__\":\n recog = recognition.SpeakerRecognizer('./')\n vad.record()\n name = recog.identify_speaker()\n if name[0] == 'Abhishek':\n blink(11)\n\nTested on\n---------\n\n- Ubuntu 15.10\n- Pi 1 model B (raspbian wheezy, jessie)\n- Pi 2 model B (raspbian wheezy, jessie, stretch)\n- CHIP\n\nInstallation\n------------\n\nUpdate the Pi\n\n.. code:: bash\n\n $ sudo apt-get update\n $ sudo apt-get upgrade\n\nYou need to have JDK (min version: 1.7) installed on your Pi.\n\n.. code:: bash\n\n # verify jdk is installed\n $ java -version\n\nPyaudio is required to run audio recording script. (Optional)\n\n.. code:: bash\n\n # Install portaudio\n $ sudo apt-get install portaudio19-dev\n # Install python dev package\n $ sudo apt-get install python2.7-dev\n # Install pyaudio\n $ pip install pyaudio \n\nPiwho is on PyPI\n\n.. code:: bash\n\n $ pip install piwho\n\nor clone the project from github\n\n.. code:: bash\n\n $ git clone https://www.github.com/Adirockzz95/Piwho.git\n $ cd Piwho\n $ python setup.py install\n\nTests\n-----\n\nTests are implemented using unittest framework:\n\n.. code:: bash\n\n $ pip install -r requirements.txt\n $ python -m unittest discover -v ./tests\n\nDocumentation\n-------------\n\n- `Training the model `__\\ \n- `Recognition `__\\ \n- `Gender detection `__\\ \n- `integrating with Jasper `__\n\nTips / Caveats\n--------------\n\n- Recognition/Training time depends on the length of an audio file.\n- If possible overclock your Pi- use Turbo mode.\n- Give maxmium RAM to CPU.\n- Read `MARF\n manual `__\n to know how the it works.\n- Recognition speed is directly proportional to the CPU power.\n\nMisc\n----\n\nHere are resources/similar projects I came across while working on this\nproject.\n\n- `recognito `__ : Works\n very well on Pi, but data storage is not implemented.\n- `voiceid `__\n- `ALIZE `__\n- `Shout `__\n- `MARF\n manual `__\n- `LIUM\n site `__\n\n\nLICENSE\n-------\n`MIT <./LICENSE>`__",
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