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animationengine.py
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# MB-Lab
# MB-Lab fork website : https://github.com/animate1978/MB-Lab
# ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 3
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# ##### END GPL LICENSE BLOCK #####
import logging
import os
import json
import time
from functools import lru_cache
import mathutils
import bpy
from . import algorithms
from .utils import get_active_armature
logger = logging.getLogger(__name__)
class RetargetEngine:
def __init__(self):
self.has_data = False
self.femaleposes_exist = False
self.maleposes_exist = False
self.data_path = algorithms.get_data_path()
self.maleposes_path = os.path.join(self.data_path, self.data_path, "poses", "male_poses")
self.femaleposes_path = os.path.join(self.data_path, self.data_path, "poses", "female_poses")
if os.path.isdir(self.maleposes_path):
self.maleposes_exist = True
if os.path.isdir(self.femaleposes_path):
self.femaleposes_exist = True
self.body_name = ""
self.armature_name = ""
self.skeleton_mapped = {}
self.lib_filepath = algorithms.get_blendlibrary_path()
self.knowledge_path = os.path.join(self.data_path, "retarget_knowledge.json")
if os.path.isfile(self.lib_filepath) and os.path.isfile(self.knowledge_path):
self.knowledge_database = algorithms.load_json_data(self.knowledge_path, "Skeleton knowledge data")
self.local_rotation_bones = self.knowledge_database["local_rotation_bones"]
self.last_selected_bone_name = None
self.stored_animations = {}
self.correction_is_sync = True
self.is_animated_bone = ""
self.rot_type = ""
self.has_data = True
else:
logger.critical("Retarget database not found. Please check your Blender addons directory.")
@staticmethod
def get_selected_posebone():
if bpy.context.selected_pose_bones:
if bpy.context.selected_pose_bones:
return bpy.context.selected_pose_bones[0]
return None
def is_editable_bone(self):
armat = get_active_armature()
if armat:
if armat.animation_data:
if armat.animation_data.action:
if self.rot_type in ["EULER", "QUATERNION"]:
self.is_animated_bone = "VALID_BONE"
else:
self.is_animated_bone = "The bone has not anim. data"
else:
self.is_animated_bone = "{0} has not action data".format(armat.name)
else:
self.is_animated_bone = "{0} has not animation data".format(armat.name)
else:
self.is_animated_bone = "No armature selected"
@staticmethod
def get_action(target_armature):
if target_armature and target_armature.animation_data:
return target_armature.animation_data.action
return None
def check_correction_sync(self):
scn = bpy.context.scene
selected_bone = self.get_selected_posebone()
if selected_bone:
if self.last_selected_bone_name != selected_bone.name:
self.get_bone_rot_type()
offsets = self.get_offset_values()
if scn.mblab_rot_offset_0 != offsets[0]:
self.correction_is_sync = False
if scn.mblab_rot_offset_1 != offsets[1]:
self.correction_is_sync = False
if scn.mblab_rot_offset_2 != offsets[2]:
self.correction_is_sync = False
self.is_editable_bone()
self.last_selected_bone_name = selected_bone.name
def get_offset_values(self):
offsets = [0, 0, 0]
for i in (0, 1, 2):
if self.rot_type == "QUATERNION":
channel = i+1
else:
channel = i
armat_name, animation_curve, animation_data_id = self.get_curve_data(channel)
if armat_name in self.stored_animations.keys():
if animation_data_id in self.stored_animations[armat_name].keys():
animation_data = self.stored_animations[armat_name][animation_data_id]
if animation_curve:
if animation_curve.keyframe_points:
offsets[i] = animation_curve.keyframe_points[0].co[1] - animation_data[0]
return offsets
def identify_curve_rot(self, bone):
r_type = "NO_CURVES"
armat = get_active_armature()
if armat:
action = self.get_action(armat)
if action and bone:
d_path1 = f'pose.bones["{bone.name}"].rotation_quaternion'
d_path2 = f'pose.bones["{bone.name}"].rotation_axis_angle'
d_path3 = f'pose.bones["{bone.name}"].rotation_euler'
animation_curve1 = action.fcurves.find(d_path1, 0)
animation_curve2 = action.fcurves.find(d_path2, 0)
animation_curve3 = action.fcurves.find(d_path3, 0)
if animation_curve1:
r_type = "QUATERNION"
if animation_curve2:
r_type = "AXIS_ANGLE"
if animation_curve3:
r_type = "EULER"
return r_type
def get_bone_rot_type(self):
selected_bone = self.get_selected_posebone()
self.rot_type = self.identify_curve_rot(selected_bone)
def get_bone_curve_id(self, selected_bone):
if self.rot_type == "QUATERNION":
return f'pose.bones["{selected_bone.name}"].rotation_quaternion'
if self.rot_type == "EULER":
return f'pose.bones["{selected_bone.name}"].rotation_euler'
return None
def get_curve_data(self, channel):
armat = get_active_armature()
d_path = None
if armat:
action = self.get_action(armat)
if action:
selected_bone = self.get_selected_posebone()
if selected_bone:
d_path = self.get_bone_curve_id(selected_bone)
if d_path:
animation_curve = action.fcurves.find(d_path, channel)
animation_data_id = f'{d_path}{str(channel)}'
if animation_curve:
return (armat.name, animation_curve, animation_data_id)
return (None, None, None)
def reset_bones_correction(self):
self.stored_animations = {}
def correct_bone_angle(self, channel, value):
scn = bpy.context.scene
if self.rot_type == "QUATERNION":
channel += 1
armat_name, animation_curve, animation_data_id = self.get_curve_data(channel)
if armat_name and animation_curve and animation_data_id:
if armat_name not in self.stored_animations.keys():
self.stored_animations[armat_name] = {}
if animation_data_id not in self.stored_animations[armat_name].keys():
animation_data = []
for kpoint in animation_curve.keyframe_points:
animation_data.append(kpoint.co[1])
self.stored_animations[armat_name][animation_data_id] = animation_data
else:
animation_data = self.stored_animations[armat_name][animation_data_id]
for i, _ in enumerate(animation_data):
animation_curve.keyframe_points[i].co[1] = animation_data[i] + value
animation_curve.update()
scn.frame_set(scn.frame_current)
def align_bones_z_axis(self, target_armature, source_armature):
armature_z_axis = {}
if target_armature:
if source_armature:
logger.info("Aligning Z axis of %s with Z axis of %s",
target_armature.name, source_armature.name)
algorithms.select_and_change_mode(source_armature, 'EDIT')
for x_bone in target_armature.data.bones:
b_name = x_bone.name
source_bone_name = self.get_mapped_name(b_name)
if source_bone_name is not None:
armature_z_axis[b_name] = source_armature.data.edit_bones[source_bone_name].z_axis.copy()
else:
logger.debug("Bone %s non mapped", b_name)
algorithms.select_and_change_mode(source_armature, 'POSE')
algorithms.select_and_change_mode(target_armature, 'EDIT')
for armat_bone in target_armature.data.edit_bones:
if armat_bone.name in armature_z_axis:
z_axis = armature_z_axis[armat_bone.name]
armat_bone.align_roll(z_axis)
algorithms.select_and_change_mode(target_armature, 'POSE')
def reset_skeleton_mapped(self):
self.skeleton_mapped = {}
def init_skeleton_map(self, source_armat):
self.reset_skeleton_mapped()
self.already_mapped_bones = []
self.spine_bones_names = None
self.rarm_bones_names = None
self.larm_bones_names = None
self.rleg_bones_names = None
self.lleg_bones_names = None
self.head_bones_names = None
self.pelvis_bones_names = None
self.rtoe1_bones_names = None
self.rtoe2_bones_names = None
self.rtoe3_bones_names = None
self.rtoe4_bones_names = None
self.rtoe5_bones_names = None
self.ltoe1_bones_names = None
self.ltoe2_bones_names = None
self.ltoe3_bones_names = None
self.ltoe4_bones_names = None
self.ltoe5_bones_names = None
self.rfinger0_bones_names = None
self.rfinger1_bones_names = None
self.rfinger2_bones_names = None
self.rfinger3_bones_names = None
self.rfinger4_bones_names = None
self.lfinger0_bones_names = None
self.lfinger1_bones_names = None
self.lfinger2_bones_names = None
self.lfinger3_bones_names = None
self.lfinger4_bones_names = None
self.map_main_bones(source_armat)
@staticmethod
def name_combinations(bone_identifiers, side):
combinations = []
if side == 'RIGHT':
side_id = ("r", "right")
junctions = (".", "_", "-", "")
elif side == 'LEFT':
side_id = ("l", "left")
junctions = (".", "_", "-", "")
else:
side_id = [""]
junctions = [""]
for b_id in bone_identifiers:
for s_id in side_id:
for junct in junctions:
combinations.append(f'{b_id}{junct}{s_id}')
combinations.append(f'{s_id}{junct}{b_id}')
return combinations
def get_bone_by_exact_id(self, bones_to_scan, bone_identifiers, side):
if bones_to_scan:
name_combinations = self.name_combinations(bone_identifiers, side)
for b_name in bones_to_scan:
if b_name.lower() in name_combinations:
return b_name
return None
def get_bone_by_childr(self, armat, bones_to_scan, childr_identifiers):
if childr_identifiers:
for bone_name in bones_to_scan:
x_bone = self.get_bone(armat, bone_name)
if not x_bone:
return None
for ch_bone in x_bone.children:
for ch_id in childr_identifiers:
c1 = algorithms.is_string_in_string(ch_id, ch_bone.name)
c2 = ch_bone.name in bones_to_scan
c3 = algorithms.is_too_much_similar(x_bone.name, ch_bone.name)
if c1 and c2 and not c3:
return x_bone.name
return None
@staticmethod
def get_bones_by_index(bones_chain, index_data):
index = None
if bones_chain:
if len(index_data) == 1:
if index_data[0] == "LAST":
index = len(bones_chain)-1
else:
index = index_data[0]
if len(index_data) == 3:
if len(bones_chain) == index_data[0]:
index = index_data[1]
else:
index = index_data[2]
if index == "None":
index = None
if index is not None:
try:
return bones_chain[index]
except IndexError:
logger.warning("The chain %s of mocap file has less bones than the chain in the lab", bones_chain)
return None
# def get_bones_by_parent(self, armat, bones_to_scan, parent_IDs):
# found_bones = set()
# for bone_name in bones_to_scan:
# parent_name = self.bone_parent_name(armat, bone_name)
# for pr_id in parent_IDs:
# if algorithms.is_string_in_string(pr_id, parent_name):
# found_bones.add(bone_name)
# return found_bones
@staticmethod
def get_bone_chains(armat, bone_names):
found_chains = []
for bone_name in bone_names:
bn = armat.data.bones[bone_name]
chain = [bone_name] + [b.name for b in bn.parent_recursive]
found_chains.append(chain)
return found_chains
@staticmethod
def get_all_bone_names(armat):
bone_names = []
for bn in armat.data.bones:
bone_names.append(bn.name)
return bone_names
@staticmethod
@lru_cache(maxsize=2)
def generate_bones_ids(side):
bone_ids = ("forearm", "elbow", "lowerarm", "hand", "wrist", "finger", "thumb", "index",
"ring", "pink", "thigh", "upperleg", "upper_leg", "leg", "knee", "shin", "calf",
"lowerleg", "lower_leg", "toe", "ball", "foot")
bn_pos = "r" if side == "RIGHT" else "l"
combo_bones_start = []
combo_bones_end = []
for b_id in bone_ids:
combo_bones_start.append(f'{bn_pos}{b_id}')
combo_bones_end.append(f'{b_id}{bn_pos}')
return combo_bones_start, combo_bones_end
def is_in_side(self, bone_names, side):
score_level = 0.0
if side == "RIGHT":
id_side2 = "right"
id_side3 = ("r.", "r_")
id_side4 = ("_r", ".r")
if side == "LEFT":
id_side2 = "left"
id_side3 = ("l.", "l_")
id_side4 = ("_l", ".l")
combo_bones_start, combo_bones_end = self.generate_bones_ids(side)
for bone_name in bone_names:
bone_name = bone_name.lower()
if len(bone_name) > 3:
c1 = bone_name[:2] in id_side3
c2 = bone_name[-2:] in id_side4
c3 = id_side2 in bone_name
c4 = algorithms.is_in_list(bone_names, combo_bones_start, "START")
c5 = algorithms.is_in_list(bone_names, combo_bones_end, "END")
if c1 or c2 or c3 or c4 or c5:
score_level += 1
if bone_names:
return score_level/len(bone_names)
return 0
@staticmethod
def order_with_list(bones_set, bones_list):
ordered_bones = []
for bone in bones_list:
if bone in bones_set:
ordered_bones.append(bone)
return ordered_bones
def chains_intersection(self, chains):
chain_sets = []
chain_inters = None
result_chain = []
for chain in chains:
chain_sets.append(set(chain))
for i, chain in enumerate(chain_sets):
chain_inters = chain if chain_inters is None else chain_inters.intersection(chain)
result_chain = self.order_with_list(chain_inters, chains[i])
return result_chain
@staticmethod
def filter_chains_by_max_length(chains):
longer_chains = []
max_length = 0
for chain in chains:
max_length = max(max_length, len(chain))
for chain in chains:
if len(chain) == max_length:
longer_chains.append(chain)
return longer_chains
def chains_difference(self, chain_list, subchain_list):
subchain_set = set(subchain_list)
chain_set = set(chain_list)
d_chain = chain_set.difference(subchain_set)
return self.order_with_list(d_chain, chain_list)
def filter_chains_by_side(self, chains):
left_chains = []
right_chains = []
center_chains = []
for chain in chains:
score_left = self.is_in_side(chain, "LEFT")
score_right = self.is_in_side(chain, "RIGHT")
if score_left > 0:
left_chains.append(chain)
elif score_right > 0:
right_chains.append(chain)
else:
center_chains.append(chain)
if not center_chains:
score_threshold = 0
for chain in chains:
score_left = self.is_in_side(chain, "LEFT")
score_right = self.is_in_side(chain, "RIGHT")
score_center = 1.0-score_left-score_right
if score_center > score_threshold:
score_threshold = score_center
center_chain = chain
center_chains.append(center_chain)
return left_chains, center_chains, right_chains
@staticmethod
def filter_chains_by_tail(chains, chain_ids):
target_chains_lists = []
if chains:
for chain in chains:
chain_tail = chain[0]
if algorithms.is_in_list(chain_ids, [chain_tail]):
target_chains_lists.append(chain)
return target_chains_lists
@staticmethod
def clear_chain_by_dot_product(chain, armature):
algorithms.select_and_change_mode(armature, 'EDIT')
if len(chain) > 2:
edit_bones = algorithms.get_edit_bones(armature)
bone_name = chain[0]
if bone_name in edit_bones:
e_bone = edit_bones[bone_name]
if e_bone.parent:
v1 = e_bone.vector.normalized()
v2 = e_bone.parent.vector.normalized()
if v1.dot(v2) < 0.5:
logger.info("Retarget: Bone %s removed BY DOT", bone_name)
chain.remove(bone_name)
algorithms.select_and_change_mode(armature, 'POSE') # TODO: store the status and restore it
return chain
@staticmethod
def clear_chain_by_length(chain, armature):
algorithms.select_and_change_mode(armature, 'EDIT')
for bone_name in chain:
edit_bones = algorithms.get_edit_bones(armature)
if bone_name in edit_bones:
e_bone = edit_bones[bone_name]
if e_bone.parent:
if e_bone.length < e_bone.parent.length/8:
logger.info("Retarget: Bone %s removed BY LENGTH", bone_name)
chain.remove(bone_name)
algorithms.select_and_change_mode(armature, 'POSE') # TODO: store the status and restore it
return chain
def filter_chains_by_dotprod(self, armature):
self.spine_bones_names = self.clear_chain_by_dot_product(self.spine_bones_names, armature)
self.head_bones_names = self.clear_chain_by_dot_product(self.head_bones_names, armature)
self.rarm_bones_names = self.clear_chain_by_dot_product(self.rarm_bones_names, armature)
self.larm_bones_names = self.clear_chain_by_dot_product(self.larm_bones_names, armature)
self.pelvis_bones_names = self.clear_chain_by_dot_product(self.pelvis_bones_names, armature)
self.ltoe_and_leg_names = self.clear_chain_by_dot_product(self.ltoe_and_leg_names, armature)
self.rtoe_and_leg_names = self.clear_chain_by_dot_product(self.rtoe_and_leg_names, armature)
self.rfinger0_bones_names = self.clear_chain_by_dot_product(self.rfinger0_bones_names, armature)
self.rfinger1_bones_names = self.clear_chain_by_dot_product(self.rfinger1_bones_names, armature)
self.rfinger2_bones_names = self.clear_chain_by_dot_product(self.rfinger2_bones_names, armature)
self.rfinger3_bones_names = self.clear_chain_by_dot_product(self.rfinger3_bones_names, armature)
self.rfinger4_bones_names = self.clear_chain_by_dot_product(self.rfinger4_bones_names, armature)
self.lfinger0_bones_names = self.clear_chain_by_dot_product(self.lfinger0_bones_names, armature)
self.lfinger1_bones_names = self.clear_chain_by_dot_product(self.lfinger1_bones_names, armature)
self.lfinger2_bones_names = self.clear_chain_by_dot_product(self.lfinger2_bones_names, armature)
self.lfinger3_bones_names = self.clear_chain_by_dot_product(self.lfinger3_bones_names, armature)
self.lfinger4_bones_names = self.clear_chain_by_dot_product(self.lfinger4_bones_names, armature)
def filter_chains_by_length(self, armature):
self.head_bones_names = self.clear_chain_by_length(self.head_bones_names, armature)
self.rarm_bones_names = self.clear_chain_by_length(self.rarm_bones_names, armature)
self.larm_bones_names = self.clear_chain_by_length(self.larm_bones_names, armature)
self.rleg_bones_names = self.clear_chain_by_length(self.rleg_bones_names, armature)
self.lleg_bones_names = self.clear_chain_by_length(self.lleg_bones_names, armature)
self.ltoe_and_leg_names = self.clear_chain_by_length(self.ltoe_and_leg_names, armature)
self.rtoe_and_leg_names = self.clear_chain_by_length(self.rtoe_and_leg_names, armature)
self.rfinger0_bones_names = self.clear_chain_by_length(self.rfinger0_bones_names, armature)
self.rfinger1_bones_names = self.clear_chain_by_length(self.rfinger1_bones_names, armature)
self.rfinger2_bones_names = self.clear_chain_by_length(self.rfinger2_bones_names, armature)
self.rfinger3_bones_names = self.clear_chain_by_length(self.rfinger3_bones_names, armature)
self.rfinger4_bones_names = self.clear_chain_by_length(self.rfinger4_bones_names, armature)
self.lfinger0_bones_names = self.clear_chain_by_length(self.lfinger0_bones_names, armature)
self.lfinger1_bones_names = self.clear_chain_by_length(self.lfinger1_bones_names, armature)
self.lfinger2_bones_names = self.clear_chain_by_length(self.lfinger2_bones_names, armature)
self.lfinger3_bones_names = self.clear_chain_by_length(self.lfinger3_bones_names, armature)
self.lfinger4_bones_names = self.clear_chain_by_length(self.lfinger4_bones_names, armature)
@staticmethod
def filter_chains_by_id(chains, chain_ids):
target_chains_lists = []
for chain in chains:
if algorithms.is_in_list(chain_ids, chain):
target_chains_lists.append(chain)
return target_chains_lists
@staticmethod
def filter_chains_by_order(chains, n_ord):
named_fingers = ("thu", "ind", "mid", "ring", "pink")
identifiers = []
for chain in chains:
if chain:
identifiers.append(chain[0])
identifiers.sort()
result_chain = []
chain_order = None
chain_id = None
if algorithms.is_in_list(named_fingers, identifiers):
chain_order = "NAMED"
else:
chain_order = "NUMBERED"
if chain_order == "NAMED":
chain_id = named_fingers[n_ord]
if chain_order == "NUMBERED":
if len(identifiers) > n_ord:
chain_id = identifiers[n_ord]
if chain_id:
chain_id = chain_id.lower()
for chain in chains:
chain_tail = chain[0]
chain_tail = chain_tail.lower()
if chain_id in chain_tail:
result_chain = chain
return result_chain
return result_chain
def identify_bone_chains(self, chains):
left_chains, center_chains, right_chains = self.filter_chains_by_side(chains)
# ARM_CHAIN_IDS
arm_chain_ids = ("arm", "elbow", "hand", "wrist", "finger", "thumb", "index",
"ring", "pink", "mid")
arms_tail_chains = self.filter_chains_by_id(chains, arm_chain_ids)
arms_tail_chains = self.filter_chains_by_max_length(arms_tail_chains)
spine_chain = self.chains_intersection(arms_tail_chains)
right_arm_tail_chains = self.filter_chains_by_tail(right_chains, arm_chain_ids)
right_arm_tail_chains = self.filter_chains_by_max_length(right_arm_tail_chains)
r_arm_spine_chain = self.chains_intersection(right_arm_tail_chains)
right_arm_chain = self.chains_difference(r_arm_spine_chain, spine_chain)
left_arm_tail_chains = self.filter_chains_by_tail(left_chains, arm_chain_ids)
left_arm_tail_chains = self.filter_chains_by_max_length(left_arm_tail_chains)
l_arm_spine_chain = self.chains_intersection(left_arm_tail_chains)
left_arm_chain = self.chains_difference(l_arm_spine_chain, spine_chain)
# HEAD_CHAIN_IDS
head_chain_ids = ("head", "neck", "skull", "face", "spine")
head_tail_chains = self.filter_chains_by_id(center_chains, head_chain_ids)
head_tail_chains = self.filter_chains_by_max_length(head_tail_chains)
head_and_spine_chains = self.chains_intersection(head_tail_chains)
head_chain = self.chains_difference(head_and_spine_chains, spine_chain)
# FINGER_CHAIN_IDS
finger_chain_ids = ("finger", "thumb", "index", "ring", "pink", "mid")
# RIGHT
right_fingers_tail_chains = self.filter_chains_by_tail(right_chains, finger_chain_ids)
r_finger_arm_spine_chain = self.chains_intersection(right_fingers_tail_chains)
right_fingers_chain = [self.chains_difference(fingr, r_finger_arm_spine_chain)
for fingr in right_fingers_tail_chains]
# LEFT
left_fingers_tail_chains = self.filter_chains_by_tail(left_chains, finger_chain_ids)
l_finger_arm_spine_chain = self.chains_intersection(left_fingers_tail_chains)
left_fingers_chain = [self.chains_difference(fingr, l_finger_arm_spine_chain)
for fingr in left_fingers_tail_chains]
# FOOT_CHAIN_IDS
foot_chain_ids = ("foot", "ankle", "toe", "ball")
right_foot_tail_chains = self.filter_chains_by_tail(right_chains, foot_chain_ids)
right_foot_tail_chains.sort()
self.rtoe_and_leg_names = right_foot_tail_chains[0]
right_foot_tail_chains = self.filter_chains_by_max_length(right_foot_tail_chains)
r_leg_and_spine_chain = self.chains_intersection(right_foot_tail_chains)
right_leg_chain = self.chains_difference(r_leg_and_spine_chain, spine_chain)
right_toes_chain = [self.chains_difference(toe, r_leg_and_spine_chain) for toe in right_foot_tail_chains]
right_toes_chain = self.filter_chains_by_max_length(right_toes_chain)
left_foot_tail_chains = self.filter_chains_by_tail(left_chains, foot_chain_ids)
left_foot_tail_chains.sort()
self.ltoe_and_leg_names = left_foot_tail_chains[0]
left_foot_tail_chains = self.filter_chains_by_max_length(left_foot_tail_chains)
l_leg_and_spine_chain = self.chains_intersection(left_foot_tail_chains)
left_leg_chain = self.chains_difference(l_leg_and_spine_chain, spine_chain)
left_toes_chain = [self.chains_difference(toe, l_leg_and_spine_chain) for toe in left_foot_tail_chains]
left_toes_chain = self.filter_chains_by_max_length(left_toes_chain)
feet_tail_chains = self.filter_chains_by_tail(chains, foot_chain_ids)
# TODO not used
# leg_chain_IDs = ["thigh", "upperleg", "upper_leg", "leg", "knee", "shin",
# "calf", "lowerleg", "lower_leg", "foot", "ankle", "toe", "ball"]
pelvis_chain = self.chains_intersection(feet_tail_chains)
self.spine_bones_names = spine_chain
self.head_bones_names = head_chain
self.rarm_bones_names = right_arm_chain
self.larm_bones_names = left_arm_chain
self.rleg_bones_names = right_leg_chain
self.lleg_bones_names = left_leg_chain
self.pelvis_bones_names = pelvis_chain
self.rfinger0_bones_names = self.filter_chains_by_order(right_fingers_chain, 0)
self.rfinger1_bones_names = self.filter_chains_by_order(right_fingers_chain, 1)
self.rfinger2_bones_names = self.filter_chains_by_order(right_fingers_chain, 2)
self.rfinger3_bones_names = self.filter_chains_by_order(right_fingers_chain, 3)
self.rfinger4_bones_names = self.filter_chains_by_order(right_fingers_chain, 4)
self.lfinger0_bones_names = self.filter_chains_by_order(left_fingers_chain, 0)
self.lfinger1_bones_names = self.filter_chains_by_order(left_fingers_chain, 1)
self.lfinger2_bones_names = self.filter_chains_by_order(left_fingers_chain, 2)
self.lfinger3_bones_names = self.filter_chains_by_order(left_fingers_chain, 3)
self.lfinger4_bones_names = self.filter_chains_by_order(left_fingers_chain, 4)
@staticmethod
def get_ending_bones(armat):
found_bones = set()
for bn in armat.data.bones:
if not bn.children:
found_bones.add(bn.name)
return found_bones
@staticmethod
def string_similarity(main_string, identifiers, side):
m_string = main_string.lower()
sub_string_found = False
substrings = []
if side == 'LEFT':
substrings = ["l-", "-l", "_l", "l_", ".l", "l.", "left"]
if side == 'RIGHT':
substrings = ["r-", "-r", "_r", "r_", ".r", "r.", "right"]
for id_string in identifiers:
if id_string in m_string:
sub_string_found = True
if sub_string_found:
strings_to_subtract = identifiers + substrings
for s_string in strings_to_subtract:
s_string = s_string.lower()
if s_string in m_string:
m_string = m_string.replace(s_string, "")
return len(m_string)
return 1000
def get_bone_by_similar_id(self, bones_to_scan, bone_identifiers, side):
diff_length = 100
result = None
if bones_to_scan:
for bone_name in bones_to_scan:
score = self.string_similarity(bone_name, bone_identifiers, side)
if score < diff_length:
diff_length = score
result = bone_name
return result
def find_bone(self, armat, bone_type, search_method):
if not self.knowledge_database:
return None
bone_knowledge = self.knowledge_database[bone_type]
main_ids = bone_knowledge["main_IDs"]
children_ids = bone_knowledge["children_IDs"]
# parent_IDs = bone_knowledge["parent_IDs"]
side = bone_knowledge["side"]
chain_id = bone_knowledge["chain_ID"]
position_in_chain = bone_knowledge["position_in_chain"]
bones_chain = None
if chain_id == "spine_bones_names":
bones_chain = self.spine_bones_names
elif chain_id == "rarm_bones_names":
bones_chain = self.rarm_bones_names
elif chain_id == "larm_bones_names":
bones_chain = self.larm_bones_names
elif chain_id == "rleg_bones_names":
bones_chain = self.rleg_bones_names
elif chain_id == "lleg_bones_names":
bones_chain = self.lleg_bones_names
elif chain_id == "head_bones_names":
bones_chain = self.head_bones_names
elif chain_id == "pelvis_bones_names":
bones_chain = self.pelvis_bones_names
elif chain_id == "rtoe_and_leg_names":
bones_chain = self.rtoe_and_leg_names
elif chain_id == "ltoe_and_leg_names":
bones_chain = self.ltoe_and_leg_names
elif chain_id == "rfinger0_bones_names":
bones_chain = self.rfinger0_bones_names
elif chain_id == "rfinger1_bones_names":
bones_chain = self.rfinger1_bones_names
elif chain_id == "rfinger2_bones_names":
bones_chain = self.rfinger2_bones_names
elif chain_id == "rfinger3_bones_names":
bones_chain = self.rfinger3_bones_names
elif chain_id == "rfinger4_bones_names":
bones_chain = self.rfinger4_bones_names
elif chain_id == "lfinger0_bones_names":
bones_chain = self.lfinger0_bones_names
elif chain_id == "lfinger1_bones_names":
bones_chain = self.lfinger1_bones_names
elif chain_id == "lfinger2_bones_names":
bones_chain = self.lfinger2_bones_names
elif chain_id == "lfinger3_bones_names":
bones_chain = self.lfinger3_bones_names
elif chain_id == "lfinger4_bones_names":
bones_chain = self.lfinger4_bones_names
elif chain_id == "all_chains":
bones_chain = self.get_all_bone_names(armat)
if bones_chain:
all_methods = ["by_exact_name", "by_chain_index", "by_similar_name", "by_children"]
search_sequence = [search_method] # The first method is the one in knowledge
for methd in all_methods:
if methd not in search_sequence:
search_sequence.append(methd)
for s_method in search_sequence:
if s_method == "by_exact_name":
result = self.get_bone_by_exact_id(bones_chain, main_ids, side)
if result:
logger.info("Retarget: Bone %s found BY EXACT NAME", bone_type)
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
logger.info("Retarget: %s added to mapped bones", result)
return result
if s_method == "by_similar_name":
result = self.get_bone_by_similar_id(bones_chain, main_ids, side)
if result:
logger.info("Retarget: Bone %s found BY SIMILAR NAME", bone_type)
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
logger.info("Retarget: %s added to mapped bones", result)
return result
if s_method == "by_children":
result = self.get_bone_by_childr(armat, bones_chain, children_ids)
if result:
logger.info("Retarget: Bone %s found BY CHILDREN", bone_type)
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
logger.info("Retarget: %s added to mapped bones", result)
return result
if s_method == "by_chain_index":
result = self.get_bones_by_index(bones_chain, position_in_chain)
if result:
logger.info("Retarget: Bone %s found BY CHAIN INDEX", bone_type)
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
logger.info("Retarget: %s added to mapped bones", result)
return result
logger.warning("All retarget methods failed for %s.", bone_type)
#logger.warning(No candidates found in: {0}, or the candidate found is already mapped to another bone".format(bones_chain))
return None
def bone_parent_name(self, armat, b_name):
x_bone = self.get_bone(armat, b_name)
if x_bone:
if x_bone.parent:
return x_bone.parent.name
return None
def get_bone(self, armat, b_name, b_type="TARGET"):
if armat:
if b_type == "TARGET":
if b_name:
if b_name in armat.pose.bones:
return armat.pose.bones[b_name]
if b_type == "SOURCE":
b_name = self.get_mapped_name(b_name)
if b_name:
if b_name in armat.pose.bones:
return armat.pose.bones[b_name]
return None
@staticmethod
def get_target_editbone(armat, b_name,):
if bpy.context.object.mode == "EDIT":
if b_name:
ebone = algorithms.get_edit_bone(armat, b_name)
if ebone:
return ebone
logger.warning("%s not found in edit mode of target armature %s", b_name, armat)
return None
else:
logger.warning("Warning: Can't get the edit bone of %s because the mode is %s",
bpy.context.scene.objects.active, bpy.context.object.mode)
return None
def get_source_editbone(self, armat, b_name):
if bpy.context.object.mode == "EDIT":
b_name = self.get_mapped_name(b_name)
if b_name:
ebone = algorithms.get_edit_bone(armat, b_name)
if ebone:
return ebone
logger.warning("%s not found in edit mode of source armature %s", b_name, armat)
return None
else:
logger.warning("Warning: Can't get the edit bone of %s because the mode is %s",
bpy.context.scene.objects.active, bpy.context.object.mode)
return None
def get_mapped_name(self, b_name):
return self.skeleton_mapped.get(b_name)
def map_bone(self, armat, b_name, b_type, s_method):
mapped_name = self.find_bone(armat, b_type, s_method)
if mapped_name is not None:
self.skeleton_mapped[b_name] = mapped_name
def map_by_direct_parent(self, armat, childr_name, map_name):
childr_bone_name = self.get_mapped_name(childr_name)
if childr_bone_name:
parent_bone_name = self.bone_parent_name(armat, childr_bone_name)
if parent_bone_name:
if parent_bone_name not in self.already_mapped_bones:
self.skeleton_mapped[map_name] = parent_bone_name
self.already_mapped_bones.append(parent_bone_name)
return True
logger.warning("Error in mapping %s as direct parent of %s", map_name, childr_name)
return False
def map_main_bones(self, armat):
ending_bones = self.get_ending_bones(armat)
chains = self.get_bone_chains(armat, ending_bones)
self.identify_bone_chains(chains)
self.filter_chains_by_length(armat)
self.filter_chains_by_dotprod(armat)
for bone in (
("clavicle_L", "LCLAVICLE", "by_exact_name"),
("clavicle_R", "RCLAVICLE", "by_exact_name"),
("head", "HEAD", "by_exact_name"),
("lowerarm_R", "RFOREARM", "by_exact_name"),
("lowerarm_L", "LFOREARM", "by_exact_name"),
("upperarm_R", "RUPPERARM", "by_children"),
("upperarm_L", "LUPPERARM", "by_children"),
("hand_R", "RHAND", "by_exact_name"),
("hand_L", "LHAND", "by_exact_name"),
("breast_R", "RBREAST", "by_exact_name"),
("breast_L", "LBREAST", "by_exact_name"),
("calf_R", "RCALF", "by_exact_name"),
("calf_L", "LCALF", "by_exact_name"),
("foot_R", "RFOOT", "by_exact_name"),
("foot_L", "LFOOT", "by_exact_name"),
("toes_R", "RTOE", "by_exact_name"),
("toes_L", "LTOE", "by_exact_name"),
("pelvis", "PELVIS", "by_exact_name"),
("spine03", "CHEST", "by_chain_index"),
):
self.map_bone(armat, *bone)
if not self.map_by_direct_parent(armat, "head", "neck"):
self.map_bone(armat, "neck", "NECK", "by_similar_name") # TODO: integrate in find function
self.map_by_direct_parent(armat, "spine03", "spine02")
self.map_by_direct_parent(armat, "spine02", "spine01")
self.map_by_direct_parent(armat, "calf_R", "thigh_R")
self.map_by_direct_parent(armat, "calf_L", "thigh_L")
for bone in (
("thumb03_R", "RTHUMB03", "by_chain_index"),
("thumb02_R", "RTHUMB02", "by_chain_index"),
("thumb01_R", "RTHUMB01", "by_chain_index"),
("index03_R", "RINDEX03", "by_chain_index"),
("index02_R", "RINDEX02", "by_chain_index"),
("index01_R", "RINDEX01", "by_chain_index"),
("index00_R", "RINDEX00", "by_exact_name"),
("middle03_R", "RMIDDLE03", "by_chain_index"),
("middle02_R", "RMIDDLE02", "by_chain_index"),
("middle01_R", "RMIDDLE01", "by_chain_index"),
("middle00_R", "RMIDDLE00", "by_exact_name"),
("ring03_R", "RRING03", "by_chain_index"),
("ring02_R", "RRING02", "by_chain_index"),
("ring01_R", "RRING01", "by_chain_index"),
("ring00_R", "RRING00", "by_exact_name"),
("pinky03_R", "RPINKY03", "by_chain_index"),
("pinky02_R", "RPINKY02", "by_chain_index"),
("pinky01_R", "RPINKY01", "by_chain_index"),
("pinky00_R", "RPINKY00", "by_exact_name"),
("thumb03_L", "LTHUMB03", "by_chain_index"),
("thumb02_L", "LTHUMB02", "by_chain_index"),
("thumb01_L", "LTHUMB01", "by_chain_index"),
("index03_L", "LINDEX03", "by_chain_index"),
("index02_L", "LINDEX02", "by_chain_index"),
("index01_L", "LINDEX01", "by_chain_index"),
("index00_L", "LINDEX00", "by_exact_name"),
("middle03_L", "LMIDDLE03", "by_chain_index"),
("middle02_L", "LMIDDLE02", "by_chain_index"),
("middle01_L", "LMIDDLE01", "by_chain_index"),
("middle00_L", "LMIDDLE00", "by_exact_name"),
("ring03_L", "LRING03", "by_chain_index"),
("ring02_L", "LRING02", "by_chain_index"),
("ring01_L", "LRING01", "by_chain_index"),
("ring00_L", "LRING00", "by_exact_name"),
("pinky03_L", "LPINKY03", "by_chain_index"),
("pinky02_L", "LPINKY02", "by_chain_index"),
("pinky01_L", "LPINKY01", "by_chain_index"),
("pinky00_L", "LPINKY00", "by_exact_name"),