zdavidli / chirp

Real-time tweet reading with custom-trained voice models
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audio-processing ffmpeg flask machine-learning nlp one-shot-learning python signal-processing

2017-group-18

Group Members:

Building the project:

Note: Since the project is primarily in python and Flask, it does not need to be built!

Note: Minimum recommended server requirements: GTX 1060 or above with >8gb RAM

We recommend Python 3.6 and Anaconda due to Tensorflow requirements. To use the GPU features, you must also install the CUDA libraries that Tensorflow requries.

To install requirements

pip install -r requirements.txt

Install ffmpeg:

Windows 64 bit:

Open an administrator Command Prompt:

setx /M PATH "C:\path\to\git\repo\lib\ffmpegwin64\bin;%PATH%"

Be sure to replace the path with the correct path to the lib/ffmpegwin64 directory.

Ubuntu:

sudo add-apt-repository ppa:mc3man/trusty-media  
sudo apt-get update  
sudo apt-get install ffmpeg  
sudo apt-get install frei0r-plugins  

MacOS

Here are a couple of links to instructions:

http://www.renevolution.com/ffmpeg/2013/03/16/how-to-install-ffmpeg-on-mac-os-x.html http://www.idiotinside.com/2016/05/01/ffmpeg-mac-os-x/ http://macappstore.org/ffmpeg/

Restart your shell/command prompt/ssh after your install ffmpeg

To run:

cd src
python app.py

You will now be able to access the app at localhost:5000

You may also run on a different port with:

cd src
python app.py -p <port>

Note: On unix devices, use sudo to run on ports below 1024.

Testing

To run all tests...

On Unix systems, run

$ ./test.sh

On Windows systems, run

test.bat