corbanyax/pca-desk-starter

Personal desk/screen activity dataset captured and labelled with PCA — Personal Cognitive Assistant. Everything was captured locally and labelled on-device; only this exported, redacted dataset was uploaded.

Stat	Value
Episodes	2
Frames	16
FPS (nominal)	2.0
Format	LeRobot v3.0 (+ LLaVA / Ego4D / COCO exports)

What's inside

LeRobot v3 layout — meta/ (info, tasks, episodes), data/chunk-000/*.parquet (per-frame timesteps), media/ (frames). Each timestep carries a frozen-taxonomy tag: verb, nouns, tool, intent, modality, attention, narration.

Stream it

from huggingface_hub import snapshot_download
local = snapshot_download(repo_id="corbanyax/pca-desk-starter", repo_type="dataset")

# parquet timesteps — stream without loading everything
import pyarrow.dataset as ds
table = ds.dataset(f"{local}/data", format="parquet")
print(table.to_table().to_pandas().head())

Or with the 🤗 datasets streaming API:

from datasets import load_dataset
d = load_dataset("corbanyax/pca-desk-starter", split="train", streaming=True)
for row in d:
    print(row["narration"], row["verb"], row["nouns"])
    break

Reproduce / extend

pip install "pca[vision,dataset] @ git+https://github.com/atharvavdeo/pca"
pca-convert ./my_videos ./out --backend auto      # auto-picks model by your RAM
pca-convert ./my_videos ./out --push corbanyax/pca-desk-starter    # convert + upload

Privacy

Text was passed through PCA's PII redactor before upload (API keys, JWTs, emails, cards, phone/IP/IBAN, etc. masked). Review frames before publishing a public repo.

Card generated by pca.dataset.hub.