convert-dataset

name	convert-dataset
description	Convert robot trajectory datasets between formats — currently agibot v1 → LeRobot v2.1 (parquet + HEVC/PNG-encoded MP4). Uses the `geniesim dataset convert agibot-to-lerobot` CLI verb, which wraps the `geniesim_benchmark.dataset.convert.agibot_to_lerobot` Python API. Trigger: When the user asks to "convert agibot to lerobot", "convert dataset", "transcode trajectory data", "build a LeRobot dataset", "把 agibot 数据转成 lerobot", or provides an agibot episode dir / batch dir and wants the LeRobot v2.1 layout (`data/chunk-*/*.parquet` + `videos/…/*.mp4` + `meta/`).
license	MPL-2.0
metadata	{"author":"genie-sim","version":"1.0"}
prerequisites	["geniesim_cli:fresh-machine-setup"]
inputs	[{"name":"agibot_dir","desc":"agibot episode dir (single) or parent dir containing multiple episode subdirs","required":true},{"name":"output_dir","desc":"Destination for the LeRobot dataset","required":true},{"name":"lerobot_ref_dir","desc":"Reference LeRobot dataset to fill missing fisheye / head_back extrinsic columns from","required":false},{"name":"fps","desc":"Video frame rate","required":false,"default":"30"}]
outputs	[{"desc":"LeRobot v2.1 dataset at output_dir (data/chunk-NNN/episode_*.parquet, videos/chunk-NNN/<key>/episode_*.mp4, meta/info.json + tasks.jsonl + episodes.jsonl + episodes_stats.jsonl)"}]

When to Use

• User has agibot v1 trajectory data and wants the LeRobot v2.1 layout (e.g. to feed an upstream LeRobot training pipeline, or compare against an existing LeRobot reference).
• User provides a parent dir of multiple episode subdirs — the converter auto-detects single vs batch from layout.

Do not use for:

• Just running a benchmark task → run-benchmark skill.
• Probing an inference server → check-inference skill.

Prerequisites

• geniesim_benchmark installed (tier-1 peer — comes with geniesim bootstrap).
• ffmpeg on PATH. Used for both RGB encoding (HEVC / libx265) and depth encoding (PNG / gray16le). The converter pre-flights ffmpeg; if missing it surfaces the install hint (sudo apt install ffmpeg on Debian/Ubuntu, brew install ffmpeg on macOS).
• h5py, numpy, pyarrow are declared deps of geniesim_benchmark; nothing to install separately.

Workflow

Single episode

geniesim dataset convert agibot-to-lerobot \
  --agibot-dir ./agibot/episode_000 \
  --output-dir ./lerobot_out

--agibot-dir is treated as a single episode iff it contains aligned_joints.h5 directly. The resulting dataset has total_episodes = 1.

Batch (auto-detect)

geniesim dataset convert agibot-to-lerobot \
  --agibot-dir ./agibot \
  --output-dir ./lerobot_out

When --agibot-dir does not contain aligned_joints.h5 directly, the converter scans for episode subdirectories (each must contain aligned_joints.h5). Episodes are indexed in sorted order of their directory name.

With a reference LeRobot dataset

geniesim dataset convert agibot-to-lerobot \
  --agibot-dir ./agibot \
  --output-dir ./lerobot_out \
  --lerobot-ref-dir /path/to/reference/lerobot_dataset

When the agibot episode is missing the fisheye / head_back extrinsics (common — those cameras aren't on every rig), the converter pulls the missing columns from <lerobot-ref-dir>/data/chunk-000/episode_000000.parquet. Omit to leave those columns empty.