(self, clip_lmdb_dir, out_lmdb_dir, n_poses, subdivision_stride,
pose_resampling_fps, mean_pose, mean_dir_vec, disable_filtering=False)
| 15 | |
| 16 | class DataPreprocessor: |
| 17 | def __init__(self, clip_lmdb_dir, out_lmdb_dir, n_poses, subdivision_stride, |
| 18 | pose_resampling_fps, mean_pose, mean_dir_vec, disable_filtering=False): |
| 19 | self.n_poses = n_poses |
| 20 | self.subdivision_stride = subdivision_stride |
| 21 | self.skeleton_resampling_fps = pose_resampling_fps |
| 22 | self.mean_pose = mean_pose |
| 23 | self.mean_dir_vec = mean_dir_vec |
| 24 | self.disable_filtering = disable_filtering |
| 25 | |
| 26 | self.src_lmdb_env = lmdb.open(clip_lmdb_dir, readonly=True, lock=False) |
| 27 | with self.src_lmdb_env.begin() as txn: |
| 28 | self.n_videos = txn.stat()['entries'] |
| 29 | |
| 30 | self.spectrogram_sample_length = utils.data_utils.calc_spectrogram_length_from_motion_length(self.n_poses, self.skeleton_resampling_fps) |
| 31 | self.audio_sample_length = int(self.n_poses / self.skeleton_resampling_fps * 16000) |
| 32 | |
| 33 | # create db for samples |
| 34 | map_size = 1024 * 50 # in MB |
| 35 | map_size <<= 20 # in B |
| 36 | self.dst_lmdb_env = lmdb.open(out_lmdb_dir, map_size=map_size) |
| 37 | self.n_out_samples = 0 |
| 38 | |
| 39 | def run(self): |
| 40 | n_filtered_out = defaultdict(int) |
nothing calls this directly
no outgoing calls
no test coverage detected