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BVH file parser for extracting skeleton structure and motion data.
Handles arbitrary BVH files from different sources (Mixamo, LAFAN1, Truebones, etc.)
and converts them into our unified SkeletonGraph + motion tensor format.
"""
import numpy as np
import re
from dataclasses import dataclass
from pathlib import Path
from typing import Optional
from .skeleton_graph import SkeletonGraph, normalize_joint_name
@dataclass
class BVHData:
"""Parsed BVH data."""
skeleton: SkeletonGraph
rotations: np.ndarray # [T, J, 3] Euler angles (degrees)
root_positions: np.ndarray # [T, 3]
fps: float
num_frames: int
rotation_order: str # e.g., 'ZYX'
local_translations: np.ndarray | None = None # [T, J, 3] per-frame local translations (if available)
def parse_bvh(filepath: str | Path) -> BVHData:
"""
Parse a BVH file into skeleton structure + motion data.
Returns:
BVHData with skeleton graph, rotations, root positions, and metadata.
"""
filepath = Path(filepath)
with open(filepath, 'r') as f:
content = f.read()
# Split into HIERARCHY and MOTION sections
parts = content.split('MOTION')
if len(parts) != 2:
raise ValueError(f"Invalid BVH format in {filepath}")
hierarchy_str = parts[0]
motion_str = parts[1]
# Parse hierarchy
joint_names, parent_indices, rest_offsets, channels_per_joint, rotation_order = (
_parse_hierarchy(hierarchy_str)
)
# Parse motion data
num_frames, frame_time, motion_data = _parse_motion(motion_str)
fps = 1.0 / frame_time if frame_time > 0 else 30.0
# Extract rotations and root positions from channel data
rest_offsets_arr = np.array(rest_offsets, dtype=np.float32)
rotations, root_positions, local_translations = _extract_motion_channels(
motion_data, channels_per_joint, len(joint_names), rest_offsets_arr
)
# Build skeleton graph
skeleton = SkeletonGraph(
joint_names=joint_names,
parent_indices=parent_indices,
rest_offsets=rest_offsets_arr,
)
return BVHData(
skeleton=skeleton,
rotations=rotations,
root_positions=root_positions,
fps=fps,
num_frames=num_frames,
rotation_order=rotation_order,
local_translations=local_translations,
)
def _parse_hierarchy(hierarchy_str: str):
"""Parse BVH HIERARCHY section."""
joint_names = []
parent_indices = []
rest_offsets = []
channels_per_joint = [] # list of (num_channels, has_position)
rotation_order = 'ZYX' # default
lines = hierarchy_str.strip().split('\n')
parent_stack = [-1] # stack of parent indices
current_joint_idx = -1
for line in lines:
line = line.strip()
if line.startswith('ROOT') or line.startswith('JOINT'):
name = line.split()[-1]
current_joint_idx = len(joint_names)
joint_names.append(name)
parent_indices.append(parent_stack[-1])
elif line.startswith('End Site'):
# End effector — we'll add it as a leaf joint
parent_idx = current_joint_idx
name = f"{joint_names[parent_idx]}_end"
current_joint_idx = len(joint_names)
joint_names.append(name)
parent_indices.append(parent_idx)
channels_per_joint.append((0, False))
elif line.startswith('OFFSET'):
vals = [float(x) for x in line.split()[1:4]]
rest_offsets.append(vals)
elif line.startswith('CHANNELS'):
parts = line.split()
num_ch = int(parts[1])
ch_names = parts[2:]
has_position = any('position' in c.lower() for c in ch_names)
channels_per_joint.append((num_ch, has_position))
# Detect rotation order from channel names
rot_channels = [c for c in ch_names if 'rotation' in c.lower()]
if rot_channels:
rotation_order = ''.join(
c[0].upper() for c in rot_channels
)
elif line == '{':
parent_stack.append(current_joint_idx)
elif line == '}':
parent_stack.pop()
if parent_stack:
current_joint_idx = parent_stack[-1]
return joint_names, parent_indices, rest_offsets, channels_per_joint, rotation_order
def _parse_motion(motion_str: str):
"""Parse BVH MOTION section."""
lines = motion_str.strip().split('\n')
num_frames = 0
frame_time = 1.0 / 30.0
data_start = 0
for i, line in enumerate(lines):
line = line.strip()
if line.startswith('Frames:'):
num_frames = int(line.split(':')[1].strip())
elif line.startswith('Frame Time:'):
frame_time = float(line.split(':')[1].strip())
elif line and not line.startswith('Frames') and not line.startswith('Frame'):
data_start = i
break
# Parse frame data
motion_data = []
for line in lines[data_start:]:
line = line.strip()
if line:
values = [float(x) for x in line.split()]
motion_data.append(values)
motion_data = np.array(motion_data, dtype=np.float32)
if len(motion_data) != num_frames and len(motion_data) > 0:
num_frames = len(motion_data)
return num_frames, frame_time, motion_data
def _extract_motion_channels(
motion_data: np.ndarray,
channels_per_joint: list[tuple[int, bool]],
num_joints: int,
rest_offsets: np.ndarray = None,
) -> tuple[np.ndarray, np.ndarray, np.ndarray | None]:
"""Extract per-joint rotations, root positions, and local translations.
Returns:
rotations: [T, J, 3] Euler angles
root_positions: [T, 3]
local_translations: [T, J, 3] or None — per-frame local translations
for joints that have position channels. None if only root has positions.
"""
T = len(motion_data)
rotations = np.zeros((T, num_joints, 3), dtype=np.float32)
root_positions = np.zeros((T, 3), dtype=np.float32)
# Track which non-root joints have position channels
has_per_joint_positions = False
joint_has_pos = [False] * num_joints
col = 0
joint_idx = 0
for num_ch, has_position in channels_per_joint:
if num_ch == 0:
joint_idx += 1
continue
if has_position and joint_idx == 0:
# Root joint: extract position (3) + rotation (3)
root_positions = motion_data[:, col:col + 3].copy()
rotations[:, 0, :] = motion_data[:, col + 3:col + 6]
joint_has_pos[0] = True
col += num_ch
elif has_position:
# Non-root with position channels
rotations[:, joint_idx, :] = motion_data[:, col + 3:col + 6]
joint_has_pos[joint_idx] = True
has_per_joint_positions = True
col += num_ch
else:
# Rotation only
rotations[:, joint_idx, :] = motion_data[:, col:col + 3]
col += num_ch
joint_idx += 1
# Build per-joint local translations if any non-root joint has position channels
local_translations = None
if has_per_joint_positions:
local_translations = np.zeros((T, num_joints, 3), dtype=np.float32)
# Fill with rest_offsets as default
if rest_offsets is not None:
for j in range(num_joints):
local_translations[:, j, :] = rest_offsets[j]
# Overwrite with per-frame position data where available
col = 0
joint_idx = 0
for num_ch, has_position in channels_per_joint:
if num_ch == 0:
joint_idx += 1
continue
if has_position and joint_idx > 0:
local_translations[:, joint_idx, :] = motion_data[:, col:col + 3]
col += num_ch
joint_idx += 1
return rotations, root_positions, local_translations
def resample_motion(
rotations: np.ndarray,
root_positions: np.ndarray,
source_fps: float,
target_fps: float = 20.0,
local_translations: np.ndarray = None,
) -> tuple[np.ndarray, np.ndarray] | tuple[np.ndarray, np.ndarray, np.ndarray]:
"""Resample motion to target FPS via linear interpolation."""
if abs(source_fps - target_fps) < 0.5:
if local_translations is not None:
return rotations, root_positions, local_translations
return rotations, root_positions
T_src = len(rotations)
duration = T_src / source_fps
T_tgt = int(duration * target_fps)
src_times = np.linspace(0, duration, T_src)
tgt_times = np.linspace(0, duration, T_tgt)
# Interpolate rotations [T, J, 3]
J = rotations.shape[1]
new_rots = np.zeros((T_tgt, J, 3), dtype=np.float32)
for j in range(J):
for d in range(3):
new_rots[:, j, d] = np.interp(tgt_times, src_times, rotations[:, j, d])
# Interpolate root positions [T, 3]
new_pos = np.zeros((T_tgt, 3), dtype=np.float32)
for d in range(3):
new_pos[:, d] = np.interp(tgt_times, src_times, root_positions[:, d])
# Interpolate local translations if present [T, J, 3]
if local_translations is not None:
new_trans = np.zeros((T_tgt, J, 3), dtype=np.float32)
for j in range(J):
for d in range(3):
new_trans[:, j, d] = np.interp(tgt_times, src_times, local_translations[:, j, d])
return new_rots, new_pos, new_trans
return new_rots, new_pos
def remove_end_sites(
joint_names: list[str],
parent_indices: list[int],
rest_offsets: np.ndarray,
rotations: np.ndarray,
) -> tuple[list[str], list[int], np.ndarray, np.ndarray]:
"""Remove End Site joints (they have no channels / zero rotations)."""
keep_mask = [not name.endswith('_end') for name in joint_names]
keep_indices = [i for i, k in enumerate(keep_mask) if k]
# Remap indices
old_to_new = {old: new for new, old in enumerate(keep_indices)}
old_to_new[-1] = -1
new_names = [joint_names[i] for i in keep_indices]
new_parents = [old_to_new.get(parent_indices[i], -1) for i in keep_indices]
new_offsets = rest_offsets[keep_indices]
new_rotations = rotations[:, keep_indices, :]
return new_names, new_parents, new_offsets, new_rotations
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