def generate_features_pool(self):
""" generate train and test files for classification """
from analysis import Analysis
from dir_processing import DirProcessing
from file_op import FileOp
landmarks_urls_list, features = Analysis.get_topic_proportions_for_every_image()
subsets_dict = self.divide_persons_into_subsets()
for i in range(0, len(landmarks_urls_list)):
landmarks_url = landmarks_urls_list[i]
label_url = DirProcessing.get_label_url_from_landmarks_url(landmarks_url)
loc = DirProcessing.get_location_from_sequence(landmarks_url, 3)
if label_url and loc != "MIDDLE":
person_id, perform_id, index_id = DirProcessing.get_id_from_label_url(label_url)
subset_id = subsets_dict[person_id]
feature = features[i, :]
if loc == "START":
label = 0
else:
label = FileOp.read_label_file(label_url)
self.features_pool[subset_id].append(feature)
self.labels_pool[subset_id].append(label)
self.urls_pool[subset_id].append(landmarks_url)
print "Features pools have been generated. "
