def load_and_clean_csv(csv_path):
curr_meta = pdu.read_multiindex_pd(csv_path)
curr_meta = curr_meta[~curr_meta['id'].isin(MetaProcessingParams.
false_indexes)]
new_indexes = pdu.get_update_indexes_rule(curr_meta)
curr_meta = curr_meta.replace({'id': new_indexes})
curr_meta.to_csv(csv_path)
return curr_meta
def final_merge_single(self, overlapped_windows):
""" Final merge, optional"""
self.update_config_for_final()
name = 'final'
meta_object = MetaPartition(None, overlapped_windows, self.homography,
name)
file_dir = FileProcessing(meta_object, name)
file_dir.create_dir()
meta_object.add_observer(file_dir)
processed_meta = DataframeProcessing(meta_object)
meta_object.add_observer(processed_meta)
tracker_obj = TrackerMerger(processed_meta, meta_object, file_dir)
window_processing(tracker_obj, final_merge=True)
final_json = util.choose_best_csv_final_last(os.environ.get('RES_DIR'))
final_json_meta = pdu.read_multiindex_pd(final_json)
return final_json_meta
def load_info(self):
files = os.listdir(self.files_dir)
for file in files:
file_path = os.path.join(args.files_dir, file)
if file.endswith('json'):
curr_file_info = load_and_process(file_path)
curr_file_info = sort_meta_by_key(curr_file_info)
elif file.endswith('.csv'):
meta_pandas = read_multiindex_pd(file_path)
meta_dict = from_dataframe_to_dict(meta_pandas)
curr_file_info = fixed_to_original_coordinate_system(
meta_dict, self.homography_dict,
int(os.environ.get('fixed_coordinate_resize_h')),
int(os.environ.get('fixed_coordinate_resize_w')),
self.height, self.width)
else:
raise ValueError('Check you input file formats!')
self.files_info[file] = curr_file_info
self.ids_counters[file] = []