#!/usr/bin/env python3 """Convert one BONES-SEED Unitree G1 CSV file to MT NPZ format.""" from __future__ import annotations import argparse from pathlib import Path import mujoco import numpy as np from scipy.spatial.transform import Rotation as R from converter_common import ( MT_BODY_NAMES, MT_JOINT_NAMES, ensure_output_parent, interpolate_linear, interpolate_quaternions, load_csv_motion, load_g1_model, output_frame_count, require_body_id, validate_fps, ) MIMIC_BODY_SOURCES = { "head_mimic": "torso_link", "left_hand_mimic": "left_wrist_roll_link", "right_hand_mimic": "right_wrist_roll_link", } def convert_csv_to_mt( csv_path: str | Path, output_path: str | Path, g1_xml: str | Path, source_fps: int = 120, target_fps: int = 50, verbose: bool = True, ) -> Path: """Convert a single CSV motion to MT format and return the output path.""" validate_fps(source_fps, target_fps) root_pos, root_rot_xyzw, dof_pos = load_csv_motion(csv_path) model = load_g1_model(str(Path(g1_xml).expanduser().resolve())) model_data = mujoco.MjData(model) physical_body_names = [ name for name in MT_BODY_NAMES if name not in MIMIC_BODY_SOURCES ] body_ids = { name: require_body_id(model, name) for name in physical_body_names } body_pos_w = np.zeros( (len(root_pos), len(MT_BODY_NAMES), 3), dtype=np.float32 ) for frame in range(len(root_pos)): model_data.qpos[:3] = root_pos[frame] model_data.qpos[3:7] = root_rot_xyzw[frame, [3, 0, 1, 2]] model_data.qpos[7:] = dof_pos[frame] mujoco.mj_forward(model, model_data) for body_name, body_id in body_ids.items(): output_index = MT_BODY_NAMES.index(body_name) body_pos_w[frame, output_index] = model_data.xpos[body_id] for mimic_name, source_name in MIMIC_BODY_SOURCES.items(): body_pos_w[:, MT_BODY_NAMES.index(mimic_name)] = body_pos_w[ :, MT_BODY_NAMES.index(source_name) ] root_rotation_inverse = R.from_quat(root_rot_xyzw).inv().as_matrix() local_body_pos = np.einsum( "tij,tbj->tbi", root_rotation_inverse, body_pos_w - root_pos[:, None, :], ).astype(np.float32) target_frames = output_frame_count( len(root_pos), source_fps, target_fps ) root_pos = interpolate_linear(root_pos, target_frames) root_rot_xyzw = interpolate_quaternions( root_rot_xyzw, target_frames ) dof_pos = interpolate_linear(dof_pos, target_frames) local_body_pos = interpolate_linear(local_body_pos, target_frames) output_path = ensure_output_parent(output_path) np.savez( output_path, root_pos=root_pos.astype(np.float32), root_rot=root_rot_xyzw.astype(np.float32), dof_pos=dof_pos.astype(np.float32), local_body_pos=local_body_pos.astype(np.float32), joint_names=np.asarray(MT_JOINT_NAMES), body_names=np.asarray(MT_BODY_NAMES), fps=np.asarray([target_fps], dtype=np.int64), ) if verbose: print( f"Saved MT: {output_path} " f"({len(root_pos)} frames @ {target_fps} fps)" ) return output_path def parse_args() -> argparse.Namespace: parser = argparse.ArgumentParser( description="Convert one BONES-SEED G1 CSV motion to MT NPZ" ) parser.add_argument("--input", required=True, help="Input G1 CSV file") parser.add_argument("--output", required=True, help="Output MT NPZ file") parser.add_argument( "--g1-xml", required=True, help="Compatible Unitree G1 MJCF XML" ) parser.add_argument("--source-fps", type=int, default=120) parser.add_argument("--target-fps", type=int, default=50) return parser.parse_args() def main() -> None: args = parse_args() convert_csv_to_mt( csv_path=args.input, output_path=args.output, g1_xml=args.g1_xml, source_fps=args.source_fps, target_fps=args.target_fps, ) if __name__ == "__main__": main()