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MLEnd Datasets

Project description

MLEnd Datasets

Links: Homepage | Documentation | Github | PyPi - project | _ Installation: pip install mlend



Installation

Requirement: numpy, matplotlib, scipy.stats, spkit

with pip

pip install mlend

update with pip

pip install mlend --upgrade

Download data : Spoken Numerals

import mlend
from mlend import download_spoken_numerals, spoken_numerals_load


datadir = download_spoken_numerals(save_to = '../Data/MLEnd', subset = {},verbose=1,overwrite=False)

Create Training and Testing Sets

TrainSet, TestSet, MAPs = spoken_numerals_load(datadir_main = datadir, train_test_split = 'Benchmark_B', verbose=1,encode_labels=True)

Download data : London Sounds

import mlend
from mlend import download_london_sounds, london_sounds_load


datadir = download_london_sounds(save_to = '../Data/MLEnd', subset = {},verbose=1,overwrite=False)

Download data : Hums and Whistles

import mlend
from mlend import download_hums_whistles, hums_whistles_load


datadir = download_hums_whistles(save_to = '../Data/MLEnd', subset = {},verbose=1,overwrite=False)

Download data : Yummy

import mlend
from mlend import download_yummy, yummy_load

subset = {}

datadir = download_yummy(save_to = '../MLEnd', subset = subset,verbose=1,overwrite=False)

Contacts:

  • Jesús Requena Carrión

  • Queen Mary University of London

  • Nikesh Bajaj

  • Queen Mary University of London

  • n.bajaj[AT]qmul.ac.uk, n.bajaj[AT]imperial[dot]ac[dot]uk


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