"""Ensemble plan manually split by type moode/theme."""
from dbispipeline.evaluators import FixedSplitEvaluator
from dbispipeline.evaluators import ModelCallbackWrapper
import dbispipeline.result_handlers
from sklearn.pipeline import Pipeline
from mediaeval2020 import common
from mediaeval2020.dataloaders.melspectrograms import MelSpectPickleLoader
from mediaeval2020.dataloaders.melspectrograms import labels_to_indices
from mediaeval2020.models.crnn import CRNNModel
from mediaeval2020.models.ensemble import Ensemble
dataloader = MelSpectPickleLoader('data/mediaeval2020/melspect_1366.pickle')
label_splits = [
labels_to_indices(
dataloader=dataloader,
label_list=[ # theme
'action',
'adventure',
'advertising',
'background',
'ballad',
'children',
'christmas',
'commercial',
'corporate',
'documentary',
'drama',
'dream',
'film',
"""Ensemble plan manually split by type moode/theme."""
from dbispipeline.evaluators import FixedSplitEvaluator
from dbispipeline.evaluators import ModelCallbackWrapper
import dbispipeline.result_handlers
from sklearn.pipeline import Pipeline
from mediaeval2020 import common
from mediaeval2020.dataloaders.melspectrograms import MelSpectPickleLoader
from mediaeval2020.dataloaders.melspectrograms import labels_to_indices
from mediaeval2020.models.crnn import CRNNModel
from mediaeval2020.models.ensemble import Ensemble
dataloader = MelSpectPickleLoader(
'data/mediaeval2020/melspect_augmented_1366_sampled.pickle')
label_splits = [
labels_to_indices(
dataloader=dataloader,
label_list=[
'sexy',
'travel',
'hopeful',
'soundscape',
'groovy',
'fast',
'action',
'cool',
'space',
'movie',
'game',
'drama',
