def decorator(ref):
meta, homography_dict = func(ref)
if MetaProcessingParams.fixed_coordinate_system:
meta = fixu.fixed_to_original_coordinate_system(
meta, homography_dict,
int(os.environ.get('fixed_coordinate_resize_h')),
int(os.environ.get('fixed_coordinate_resize_w')),
int(os.environ.get('img_h')), int(os.environ.get('img_w')))
return meta, homography_dict
def processing_info(self):
for track_id, curr_track in self.initialised_tracks.items():
filter_set_init(self.filters[track_id], curr_track)
curr_track_elems = curr_track[2:]
filter_already_processed_states_pass(self.filters[track_id],
curr_track_elems)
for frame_no, frame_no_values in self.meta_left.items():
self.single_frame_processing(frame_no, frame_no_values)
self.new_meta.update(self.initialised_meta)
if self.homography_dict is not None:
self.new_meta = fixu.fixed_to_original_coordinate_system(
self.new_meta, self.homography_dict,
int(os.environ.get('fixed_coordinate_resize_h')),
int(os.environ.get('fixed_coordinate_resize_w')),
int(os.environ.get('img_h')), int(os.environ.get('img_w')))
return self.new_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] = []