(self, motion_file, min_length=-1, im_eval=False)
| 61 | return |
| 62 | |
| 63 | def load_data(self, motion_file, min_length=-1, im_eval=False): |
| 64 | if osp.isfile(motion_file): |
| 65 | self.mode = MotionlibMode.file |
| 66 | self._motion_data_load = joblib.load(motion_file) |
| 67 | else: |
| 68 | self.mode = MotionlibMode.directory |
| 69 | self._motion_data_load = glob.glob(osp.join(motion_file, "*.pkl")) |
| 70 | data_list = self._motion_data_load |
| 71 | if self.mode == MotionlibMode.file: |
| 72 | if min_length != -1: |
| 73 | # filtering the data by the length of the motion |
| 74 | data_list = {k: v for k, v in list(self._motion_data_load.items()) if len(v["pose_quat_global"]) >= min_length} |
| 75 | elif im_eval: |
| 76 | # sorting the data by the length of the motion |
| 77 | data_list = { |
| 78 | item[0]: item[1] |
| 79 | for item in sorted( |
| 80 | self._motion_data_load.items(), |
| 81 | key=lambda entry: len(entry[1]["pose_quat_global"]), |
| 82 | reverse=True, |
| 83 | ) |
| 84 | } |
| 85 | else: |
| 86 | data_list = self._motion_data_load |
| 87 | self._motion_data_list = np.array(list(data_list.values())) |
| 88 | self._motion_data_keys = np.array(list(data_list.keys())) |
| 89 | else: |
| 90 | self._motion_data_list = np.array(self._motion_data_load) |
| 91 | self._motion_data_keys = np.array(self._motion_data_load) |
| 92 | |
| 93 | self._num_unique_motions = len(self._motion_data_list) |
| 94 | if self.mode == MotionlibMode.directory: |
| 95 | self._motion_data_load = joblib.load(self._motion_data_load[0]) # set self._motion_data_load to a sample of the data |
| 96 | logger.info(f"Loaded {self._num_unique_motions} motions") |
| 97 | |
| 98 | def setup_constants(self, fix_height=FixHeightMode.full_fix, multi_thread=True): |
| 99 | self.fix_height = fix_height |
no test coverage detected