Curate Video

Video Data Loading

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Load video data for curation using NeMo Curator.

How it Works

NeMo Curator loads videos with a composite stage that discovers files and extracts metadata:

VideoReader is a composite stage that is broken down into a

  1. Partitioning (list files) stage
  • Local paths use FilePartitioningStage to list files
  • Remote URLs (for example, s3://, gcs://)
    • use ClientPartitioningStage backed by fsspec.
    • Optional input_list_json_path allows explicit file lists under a root prefix.
  1. Reader stage (VideoReaderStage)
  • This stage downloads the bytes (local or via FSPath) for each listed file
  • Calls video.populate_metadata() to extract resolution, fps, duration, encoding format, and other fields.

You can set

  • video_limit to limit the number of files to be processed; use None for unlimited.
  • verbose=True to log detailed per-video information.

Local and Cloud

Use VideoReader to load videos from local paths or remote URLs.

Example

1from nemo_curator.pipeline import Pipeline
2from nemo_curator.stages.video.io.video_reader import VideoReader
3
4pipe = Pipeline(name="video_read", description="Read videos and extract metadata")
5pipe.add_stage(VideoReader(input_video_path="s3://my-bucket/videos/", video_limit=None, verbose=True))
6pipe.run()

Explicit File List (JSON)

For remote datasets, ClientPartitioningStage can use an explicit file list JSON. Each entry must be an absolute path under the specified root.

JSON Format

1[
2 "s3://my-bucket/datasets/videos/video1.mp4",
3 "s3://my-bucket/datasets/videos/video2.mkv",
4 "s3://my-bucket/datasets/more_videos/video3.webm"
5]

If any entry is outside the root, the stage raises an error.

Example

1from nemo_curator.pipeline import Pipeline
2from nemo_curator.stages.client_partitioning import ClientPartitioningStage
3from nemo_curator.stages.video.io.video_reader import VideoReaderStage
4
5ROOT = "s3://my-bucket/datasets/"
6JSON_LIST = "s3://my-bucket/lists/videos.json"
7
8pipe = Pipeline(name="video_read_json_list", description="Read specific videos via JSON list")
9pipe.add_stage(
10 ClientPartitioningStage(
11 file_paths=ROOT,
12 input_list_json_path=JSON_LIST,
13 files_per_partition=1,
14 file_extensions=[".mp4", ".mov", ".avi", ".mkv", ".webm"],
15 )
16)
17pipe.add_stage(VideoReaderStage(verbose=True))
18pipe.run()

Supported File Types

The loader filters these video extensions by default:

  • .mp4
  • .mov
  • .avi
  • .mkv
  • .webm

Metadata on Load

After a successful read, the loader populates the following metadata fields for each video:

  • size (bytes)
  • width, height
  • framerate
  • num_frames
  • duration (seconds)
  • video_codec, pixel_format, audio_codec
  • bit_rate_k

With verbose=True, the loader logs size, resolution, fps, duration, weight, and bit rate for each processed video.