l-k-r/retargeted_motions

Retargeted Motion Dataset

This repository contains cleaned and retargeted motion data from multiple datasets, organized by robot and source dataset.

Structure

The dataset is organized as follows:

data/
  <robot_name>/
    <dataset_name>/
      tag_config.json        # Maps tags (e.g., "push") to lists of motion names
      <motion_name>/
        original_motion.mp4  # Visualization of the original source motion
        <sample_name>/       # e.g., sample1
          motion.csv         # Motion data in CSV format
          motion.npz         # Motion data in NPZ format (joint positions, velocities, etc.)
          object_motion.npz  # Object motion data (position, rotation, linear/angular velocity)
          metadata.json      # Metadata (e.g., object path, retargeting method)
          retargeted_motion.mp4 # Visualization of the retargeted motion

Setup

It is recommended to use a Conda environment to manage dependencies.

1. Create and activate a new environment:

   conda create -n retarget_dataset python=3.10
   conda activate retarget_dataset
   

2. Install required packages:

   pip install numpy matplotlib flask scipy
   

To access the 3D object files referenced in metadata.json, you need to clone the drcl assets repository. The object_path in metadata.json is relative to the root of the drcl assets directory.

Usage

1. View Single Motion Plot

Visualize the joint values, root position, and object motion for a specific recording.

python scripts/plot.py --robot <robot> --dataset <dataset> --motion_name <motion_name> [--sample <sample_name>]

Example:

python scripts/plot.py --robot unitree_g1 --dataset omomo --motion_name sub1_largetable_053 --sample sample1

2. Dataset Summary

Scan a dataset directory to verify file consistency and list all available motions with their frame counts and metadata.

python scripts/write_summary.py --robot <robot> --dataset <dataset>

3. Contact Detection

Estimate robot–object contact from object_motion.npz, visualize the result, and optionally save a binary contact signal back into the file.

python scripts/calculate_contact.py --robot <robot> --dataset <dataset> \
  --motion_name <motion_name> [--sample <sample_name>] [--save]

• --robot: robot name (e.g. unitree_g1).
• --dataset: dataset name (e.g. omomo).
• --motion_name: motion directory name under the dataset (e.g. sub3_largebox_000).
• --sample: sample directory name (default: sample1).
• --save: if set, writes the computed contact list into the corresponding object_motion.npz under key contact.

All tunable parameters controlling smoothing, thresholds, and grounding logic are defined as global variables at the top of scripts/calculate_contact.py.

4. Web Visualizer

Launch a local web server to browse and visualize motions by tag (e.g., "push", "pick") across datasets.

python scripts/web_visualizer.py