o ϯi"@sddlmZddlmZddlmZmZddlmZde de dee effdd Z de de dee effd d Z de dee effd d Z dS))Dict) g_pathmgr)EncodedVideoInfoVideoFrameInfo)optional_threaded_foreachdata_directory_path multithreadedreturncsNitt}dtdtddffdd }fdd|D}t|||S) a Args: data_directory_path (str): Path or URI to EpicKitchenDataset data. Data at this path must be a folder of structure: { "{video_id}": [ "frame_{frame_number}.{file_extension}", "frame_{frame_number}.{file_extension}", "frame_{frame_number}.{file_extension}", ...] ...} multithreaded (bool): controls whether io operations are performed across multiple threads. Returns: Dictionary mapping video_id of available videos to the locations of their underlying frame files. video_id video_pathr Nc stt|}|D]}|dd}|dt|d }|d\}}|vr?t|||dt|t|t||d|<q |}|jt|ksLJ|j|ks_Jd|d|jd||j dt|ksjJ|j |ksvJd |t|j |j|j |j|j t||j d|<q dS N._)r locationframe_file_stemframe_string_lengthmin_frame_numbermax_frame_numberfile_extensionz Frames for z found in two paths: z and z:Frames with two different file extensions found for video )sortedrlssplitlenrintrrrrr rr) r r video_frame_file_namesframer frame_namestem path_frame_idvideo_frame_info video_framesX/home/ubuntu/.local/lib/python3.10/site-packages/pytorchvideo/data/epic_kitchen/utils.pyadd_video_frames#sL     zBbuild_frame_manifest_from_flat_directory..add_video_framescg|] }|d|fqS/r$).0r rr$r% Msz.rrstrr)rr video_idsr& video_pathsr$rr#r%(build_frame_manifest_from_flat_directory s * r2csNtt}idtdtddffdd }fdd|D}t|||S) au Args: data_directory_path (str): Path or URI to EpicKitchenDataset data. If this dataset is to load from the frame-based dataset: Data at this path must be a folder of structure: { "{participant_id}" : [ "{participant_id}_{participant_video_id}_{frame_number}.{file_extension}", ...], ...} multithreaded (bool): controls whether io operations are performed across multiple threads. Returns: Dictionary mapping video_id of available videos to the locations of their underlying frame files. participant_idparticipant_pathr Nc s<ttt|}|D]}|dd}|dt|d }|d\}}}||ks-J|d|} | vrOt| || dt|t|t||d| <q | } | jt|ks\J| j |ksoJd| d| j d|| j dt|kszJ| j |ksJd | t| j | j | j | j| jt|| j d| <q dSr )rrrr.rrrrrrrrr rr) r3r4participant_framesframe_file_namerrpath_participant_id path_video_idr r r!r"r$r%add_participant_video_framesqsP      zPbuild_frame_manifest_from_nested_directory..add_participant_video_framescr'r(r$)r*r3r+r$r%r,sz>build_frame_manifest_from_nested_directory..r-)rrparticipant_idsr9particpant_pathsr$r1r%*build_frame_manifest_from_nested_directoryVs  0r<cCs^i}t|D]%}|d|}t|D]}|dd}|d|}t||||<qq|S)aY Creates a dictionary from video_id to EncodedVideoInfo for encoded videos in the given directory. Args: data_directory_path (str): The folder to ls to find encoded video files. Returns: Dict[str, EncodedVideoInfo] mapping video_id to EncodedVideoInfo for each file in 'data_directory_path' r)N)rrr)rencoded_video_infosr3participant_folder_pathvideo_file_namer video_full_pathr$r$r%,build_encoded_manifest_from_nested_directorys rBN)typingriopath.common.file_ior(pytorchvideo.data.dataset_manifest_utilsrrpytorchvideo.data.utilsrr.boolr2r<rBr$r$r$r%s.     L  W