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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