def blind_test(self, feature_sets, normalize=None):
"""
This method should predict a value for all testobjects in the list feature_sets, and returns a list with the
predictions.
:param feature_sets: list of sub-lists, where the sub-lists are the images to classify.
:return:
"""
if self.gui_worker:
self.gui_worker.gui.status_message.emit("Started blind test...")
else:
print('----> Started blind test...')
classifications = []
if self.gui_worker:
self.gui_worker.gui.status_message.emit("Normalizing cases...")
else:
print('----> Normalizing cases...')
if normalize:
feature_sets = normalize(feature_sets)
else:
feature_sets = normalize_images(feature_sets)
if self.gui_worker:
self.gui_worker.gui.status_message.emit("Run blind tests...")
else:
print('----> Run blind tests...')
for test_case in feature_sets:
prediction = self.predictor(test_case)
classifications.append(prediction.tolist().index(max(prediction)))
return classifications
def play2048_test(self, feature_sets, normalize=None):
classifications = []
if normalize:
feature_sets = normalize(feature_sets)
else:
feature_sets = normalize_images(feature_sets)
for test_case in feature_sets:
prediction = self.predictor(test_case)
classifications.append(prediction.tolist())
return classifications
