A deep neural net to classify music by mood
Please install Miniconda3 to create a virtual environment for this project. This will make package conflicts unlikely.
To install Miniconda please go to https://conda.io/miniconda.html
If it warns you about adding Miniconda to your path, make sure you add it!
You can replicate the current Mood Anaconda environment by cloning this repo, then running
conda env create -f environment.yml
Make sure you have follow the Dependencies instructions above.
In the top level of this repo, simply do
jupyter notebook
.- Click on the
notebooks
dir - Open
livedemo.ipynb
And have fun!
Inside the mood_algorithm/spectrogram-mood-classifier
directory you will find a requirements.txt
file that lists all the necessary dependencies.
See the main()
function in /mood_algorithm/spectrogram-mood-classifier/predict.py
for example local and cloud predictions.
To predict on a bunch of songs using our current CloudML model, simply loop through all your songs, and pass their file names into the cloud_predict()
function.