📦 yt8m-h264

yt8m-h264 is a lightweight derivative of the YouTube-8M dataset that exposes H.264 NAL units (SPS, PPS, IDR) for efficient bytestream-level modeling and compression-aware video research.

This dataset stores pre-processed H.264 bytestream chunks directly in Arrow artifacts, allowing fast loading with:

from datasets import load_dataset
ds = load_dataset("leee99/yt8m-h264")

No decoding, FFMPEG, or custom scripts are required at load time.

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✅ What’s inside?

• Extracted from YouTube-8M video segments

• Each sample contains:

  • sps: Sequence of SPS NAL units (as raw bytes)
  • pps: Sequence of PPS NAL units (as raw bytes)
  • idr: Sequence of IDR slice NAL units (as raw bytes)

• Stored directly in Arrow (binary) columns

A single example looks like:

{
    "sample_id": "00001234",
    "sps": [b"\x00\x00\x00...\x67"],          # list of byte payloads
    "pps": [b"\x00\x00\x00...\x68"],
    "idr": [b"\x65\x88\x99..."],              # IDR slices as raw byte arrays
}

These bytes correspond to Annex-B NAL units (0x00 00 00 01 <nal-header> <payload>), suitable for:

• bytestream modeling
• compressed-domain video understanding
• tokenization (Byte-level / Bit-level)
• entropy analysis
• H.264 syntax learning

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✅ Loading the dataset

from datasets import load_dataset
ds = load_dataset("leee99/yt8m-h264")

print(ds)
print(ds["test"][0])

Outputs:

DatasetDict({
    test: Dataset({
        features: ['sample_id', 'sps', 'pps', 'idr'],
        num_rows: <N>
    })
})