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io/mapping.py
Load / save bone mapping JSON in the exact same format as KeeMap.
"""
from __future__ import annotations
import json
from dataclasses import dataclass, field
from typing import List, Optional
import numpy as np
from ..math3d import quat_identity, vec3
@dataclass
class BoneMappingItem:
name: str = ""
label: str = ""
description: str = ""
source_bone_name: str = ""
destination_bone_name: str = ""
keyframe_this_bone: bool = True
# Rotation correction (Euler, radians)
correction_factor: np.ndarray = field(default_factory=lambda: vec3())
# Quaternion correction
quat_correction_factor: np.ndarray = field(default_factory=quat_identity)
has_twist_bone: bool = False
twist_bone_name: str = ""
set_bone_position: bool = False
set_bone_rotation: bool = True
set_bone_scale: bool = False
# Rotation options
bone_rotation_application_axis: str = "XYZ" # X Y Z XY XZ YZ XYZ
bone_transpose_axis: str = "NONE" # NONE ZXY ZYX XZY YZX YXZ
# Position options
postion_type: str = "SINGLE_BONE_OFFSET" # SINGLE_BONE_OFFSET | POLE
position_correction_factor: np.ndarray = field(default_factory=lambda: vec3())
position_gain: float = 1.0
position_pole_distance: float = 0.3
# Scale options
scale_secondary_bone_name: str = ""
bone_scale_application_axis: str = "Y"
scale_gain: float = 1.0
scale_max: float = 1.0
scale_min: float = 0.5
@dataclass
class KeeMapSettings:
source_rig_name: str = ""
destination_rig_name: str = ""
bone_mapping_file: str = ""
bone_rotation_mode: str = "EULER" # EULER | QUATERNION
start_frame_to_apply: int = 0
number_of_frames_to_apply: int = 100
keyframe_every_n_frames: int = 1
keyframe_test: bool = False
# ---------------------------------------------------------------------------
# Load
# ---------------------------------------------------------------------------
def load_mapping(filepath: str):
"""
Returns (KeeMapSettings, List[BoneMappingItem]).
Reads the exact same JSON that KeeMap writes.
"""
with open(filepath, "r") as f:
data = json.load(f)
settings = KeeMapSettings(
source_rig_name=data.get("source_rig_name", ""),
destination_rig_name=data.get("destination_rig_name", ""),
bone_mapping_file=data.get("bone_mapping_file", ""),
bone_rotation_mode=data.get("bone_rotation_mode", "EULER"),
start_frame_to_apply=data.get("start_frame_to_apply", 0),
number_of_frames_to_apply=data.get("number_of_frames_to_apply", 100),
keyframe_every_n_frames=data.get("keyframe_every_n_frames", 1),
)
bones: List[BoneMappingItem] = []
for p in data.get("bones", []):
item = BoneMappingItem()
item.name = p.get("name", "")
item.label = p.get("label", "")
item.description = p.get("description", "")
item.source_bone_name = p.get("SourceBoneName", "")
item.destination_bone_name = p.get("DestinationBoneName", "")
item.keyframe_this_bone = p.get("keyframe_this_bone", True)
item.correction_factor = np.array([
p.get("CorrectionFactorX", 0.0),
p.get("CorrectionFactorY", 0.0),
p.get("CorrectionFactorZ", 0.0),
])
item.quat_correction_factor = np.array([
p.get("QuatCorrectionFactorw", 1.0),
p.get("QuatCorrectionFactorx", 0.0),
p.get("QuatCorrectionFactory", 0.0),
p.get("QuatCorrectionFactorz", 0.0),
])
item.has_twist_bone = p.get("has_twist_bone", False)
item.twist_bone_name = p.get("TwistBoneName", "")
item.set_bone_position = p.get("set_bone_position", False)
item.set_bone_rotation = p.get("set_bone_rotation", True)
item.set_bone_scale = p.get("set_bone_scale", False)
item.bone_rotation_application_axis = p.get("bone_rotation_application_axis", "XYZ")
item.bone_transpose_axis = p.get("bone_transpose_axis", "NONE")
item.postion_type = p.get("postion_type", "SINGLE_BONE_OFFSET")
item.position_correction_factor = np.array([
p.get("position_correction_factorX", 0.0),
p.get("position_correction_factorY", 0.0),
p.get("position_correction_factorZ", 0.0),
])
item.position_gain = p.get("position_gain", 1.0)
item.position_pole_distance = p.get("position_pole_distance", 0.3)
item.scale_secondary_bone_name = p.get("scale_secondary_bone_name", "")
item.bone_scale_application_axis = p.get("bone_scale_application_axis", "Y")
item.scale_gain = p.get("scale_gain", 1.0)
item.scale_max = p.get("scale_max", 1.0)
item.scale_min = p.get("scale_min", 0.5)
bones.append(item)
return settings, bones
# ---------------------------------------------------------------------------
# Save
# ---------------------------------------------------------------------------
def save_mapping(filepath: str, settings: KeeMapSettings, bones: List[BoneMappingItem]) -> None:
"""Write mapping JSON readable by KeeMap."""
root = {
"source_rig_name": settings.source_rig_name,
"destination_rig_name": settings.destination_rig_name,
"bone_mapping_file": settings.bone_mapping_file,
"bone_rotation_mode": settings.bone_rotation_mode,
"start_frame_to_apply": settings.start_frame_to_apply,
"number_of_frames_to_apply": settings.number_of_frames_to_apply,
"keyframe_every_n_frames": settings.keyframe_every_n_frames,
"bones": [],
}
for b in bones:
root["bones"].append({
"name": b.name,
"label": b.label,
"description": b.description,
"SourceBoneName": b.source_bone_name,
"DestinationBoneName": b.destination_bone_name,
"keyframe_this_bone": b.keyframe_this_bone,
"CorrectionFactorX": float(b.correction_factor[0]),
"CorrectionFactorY": float(b.correction_factor[1]),
"CorrectionFactorZ": float(b.correction_factor[2]),
"QuatCorrectionFactorw": float(b.quat_correction_factor[0]),
"QuatCorrectionFactorx": float(b.quat_correction_factor[1]),
"QuatCorrectionFactory": float(b.quat_correction_factor[2]),
"QuatCorrectionFactorz": float(b.quat_correction_factor[3]),
"has_twist_bone": b.has_twist_bone,
"TwistBoneName": b.twist_bone_name,
"set_bone_position": b.set_bone_position,
"set_bone_rotation": b.set_bone_rotation,
"set_bone_scale": b.set_bone_scale,
"bone_rotation_application_axis": b.bone_rotation_application_axis,
"bone_transpose_axis": b.bone_transpose_axis,
"postion_type": b.postion_type,
"position_correction_factorX": float(b.position_correction_factor[0]),
"position_correction_factorY": float(b.position_correction_factor[1]),
"position_correction_factorZ": float(b.position_correction_factor[2]),
"position_gain": b.position_gain,
"position_pole_distance": b.position_pole_distance,
"scale_secondary_bone_name": b.scale_secondary_bone_name,
"bone_scale_application_axis": b.bone_scale_application_axis,
"scale_gain": b.scale_gain,
"scale_max": b.scale_max,
"scale_min": b.scale_min,
})
with open(filepath, "w") as f:
json.dump(root, f, indent=2)
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