def score(
self,
bundle,
bundle_size=32,
verbose=True,
):
loader = Loader(bundle)
return self.model().evaluate_generator(
loader.gen_data_test(bundle_size),
steps=1,
verbose=verbose,
)
def score(
self,
bundle,
bundle_size=32,
verbose=True,
scale_factor=4,
):
loader = Loader(bundle, scale_factor, Image.BICUBIC)
return self.model().evaluate_generator(
loader.gen_data_test(bundle_size),
steps=1,
verbose=verbose,
)
def train(
self,
bundle,
bundle_size=32,
steps_per_epoch=128,
epochs=8,
verbose=True,
):
loader = Loader(bundle)
history = self.model().fit_generator(
loader.gen_data_train(bundle_size),
steps_per_epoch=steps_per_epoch,
epochs=epochs,
verbose=verbose,
validation_data=loader.gen_data_test(bundle_size),
validation_steps=steps_per_epoch,
)
path_history = path.join(self._path_history, self.name() + '.hi')
with open(path_history, 'wb') as file_hi:
dump(history.history, file_hi)