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i4h-workflow-dataset-mimic

i4h-workflow-dataset-mimic

github.com/nvidiaData & databases3.8k67 installsUpdated today
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About i4h-workflow-dataset-mimic

A workflow skill for expanding recorded demonstrations by cloning successful HDF5 episodes and perturbing their actions. It guides dataset inspection and verification of generated variants and preserved episode contracts.

Key features

  1. 01Resolve source checkout and HDF5
  2. 02Inspect successful episodes and segments
  3. 03Generate action-jitter variants
  4. 04Verify counts and preserved data

Use cases

  1. 01Create more demonstration episodes from successful recordings
  2. 02Check segment preservation after action perturbation

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/nvidia/skills --skill i4h-workflow-dataset-mimic

After installing, type/i4h-workflow-dataset-mimicin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

BENCHMARK.md
skill-card.md
skill.oms.sig
evals/
evals.json

Details

From the project README

Mimic Workflow Demonstrations

Purpose

Clone successful source episodes and perturb recorded actions.

Instructions

  1. Run the checkout resolver and select the source HDF5.
  2. Inspect successful episodes and segments.
  3. Run mimic to generate the requested additional action-jitter variants.
  4. Compare exact counts and preserved contracts.

Resolve and inspect

export I4H_WORKFLOWS_REPO_URL="${I4H_WORKFLOWS_REPO_URL:-https://github.com/isaac-for-healthcare/i4h-workflows}"
I4H_REPO_DIR_NAME="${I4H_WORKFLOWS_REPO_URL%/}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME##*/}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME##*:}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME%.git}"
[ -n "$I4H_REPO_DIR_NAME" ] || { echo "Cannot derive a checkout name from I4H_WORKFLOWS_REPO_URL" >&2; exit 2; }
ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"
if [ ! -d "$ROOT/workflows/i4h_workflows" ]; then
  ROOT="${I4H_WORKFLOWS:-$HOME/$I4H_REPO_DIR_NAME}"
  [ -d "$ROOT/workflows/i4h_workflows" ] || git clone "$I4H_WORKFLOWS_REPO_URL" "$ROOT"
fi
export I4H_WORKFLOWS="$ROOT"
cd "$ROOT"
HDF5_PATH=/absolute/path/to/source.hdf5
uv run --project tools/dataset i4h-dataset inspect "$HDF5_PATH" --segments

Treat the resolver above as part of the skill contract: a hosted copy may run outside the base repository, so never assume the current checkout contains workflows/i4h_workflows. I4H_WORKFLOWS_REPO_URL selects the clone source. When I4H_WORKFLOWS is unset, derive the fallback directory from that URL; set I4H_WORKFLOWS only to reuse or choose a specific destination. Never replace an existing checkout.

Use the explicit/current-chain recording. Require at least one successful source episode. If the user asks for node-scoped jitter, require that node in segment metadata.

Expand

RUN_DIR="$(pwd)/runs/<workflow>/$(date +%Y%m%d_%H%M%S)"
mkdir -p "$RUN_DIR"
uv run --project tools/mimic i4h-mimic \
  "$HDF5_PATH" "$RUN_DIR/expanded.hdf5" \
  --episodes <additional-count> \
  --noise 0.01 \
  --seed <seed> \
  --include-source \
  --successful-only

--episodes is the number of generated variants, not the final total. Add --node <node-id> only when requested. Preserve the default deterministic seed unless the user supplies another.

Verify and compose

uv run --project tools/dataset i4h-dataset inspect "$RUN_DIR/expanded.hdf5" --segments

Confirm source count, generated count, dimensions, success flags, and segment preservation. Reject zero generated episodes.

If the same prompt requests visualization, continue with i4h-workflow-dataset-convert, then i4h-lerobot-viz; raw HDF5 is not a LeRobot visualizer input.

Troubleshooting

On failure, inspect the first episode shape or segment error. If a requested node is absent, report available node ids.

Prerequisites

Require a readable HDF5 file with at least one successful episode and valid segments for node-scoped jitter.

Limitations

The current tool does not independently add state noise, rerun physics, or synthesize camera frames.

Examples

  • Mimic 3 more episodes and visualize my dataset. → generate three variants, convert the expanded HDF5, then launch LeRobot visualization.

Completion gate

Report input/output paths, source and generated counts, final total, action-noise value, seed, optional node, limitations, and conversion/visualizer result when requested.

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