mava_exchange.reader.MediaPackageReader¶
- class mava_exchange.reader.MediaPackageReader(path: str | Path)¶
Read .mediapkg archive files.
Use as a context manager or call open()/close() manually.
Example:
with MediaPackageReader("corpus.mediapkg") as r: print(r.video_ids) print(r.track_names) df = r.read_track("v001", "emotions")
- __init__(path: str | Path)¶
Initialize reader.
- Parameters:
path (str or Path) – Path to .mediapkg file
Methods
__init__(path)Initialize reader.
close()Close the package file.
open()Open the package for reading.
read_track(video_id, track_name)Read a track's data into a DataFrame.
read_video(video_id)Read all tracks for a video.
track_def(track_name)Get track definition object.
tracks_for_video(video_id)List track names available for a video.
video_meta(video_id)Get video metadata.
Attributes
The parsed manifest.json dictionary.
List of all track names across all videos.
List of video IDs in the package.
- open() Self¶
Open the package for reading.
- close()¶
Close the package file.
- property manifest: dict¶
The parsed manifest.json dictionary.
- property video_ids: list[str]¶
List of video IDs in the package.
- property track_names: list[str]¶
List of all track names across all videos.
- video_meta(video_id: str) dict¶
Get video metadata.
Returns src, title, duration etc. (excludes file paths).
- track_def(track_name: str) ObservationSeries | AnnotationSeries | AnnotationListSeries¶
Get track definition object.
- Returns:
ObservationSeries, AnnotationSeries, or AnnotationListSeries
- Return type:
Track
- tracks_for_video(video_id: str) list[str]¶
List track names available for a video.
- read_track(video_id: str, track_name: str) DataFrame¶
Read a track’s data into a DataFrame.
- Parameters:
video_id (str) – Video identifier
track_name (str) – Track name
- Returns:
Track data with columns matching the track definition
- Return type:
pd.DataFrame
- read_video(video_id: str) dict[str, DataFrame]¶
Read all tracks for a video.
- Returns:
Mapping of track_name → DataFrame
- Return type:
dict[str, pd.DataFrame]