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animationengine.py
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animationengine.py
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#ManuelbastioniLAB - Copyright (C) 2015-2018 Manuel Bastioni
#Official site: www.manuelbastioni.com
#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, see <http://www.gnu.org/licenses/>.
import bpy, os, json, time
import mathutils
from . import algorithms
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:
algorithms.print_log_report("CRITICAL","Retarget database not found. Please check your Blender addons directory.")
return None
def get_selected_posebone(self):
if bpy.context.selected_pose_bones:
if len(bpy.context.selected_pose_bones) > 0:
return bpy.context.selected_pose_bones[0]
return None
def is_editable_bone(self):
armat = algorithms.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"
def get_action(self,target_armature):
if target_armature:
if 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]
scn = bpy.context.scene
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 len(animation_curve.keyframe_points) > 0:
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 = algorithms.get_active_armature()
if armat:
action = self.get_action(armat)
if action:
if bone:
d_path1 = 'pose.bones["{0}"].rotation_quaternion'.format(bone.name)
d_path2 = 'pose.bones["{0}"].rotation_axis_angle'.format(bone.name)
d_path3 = 'pose.bones["{0}"].rotation_euler'.format(bone.name)
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 'pose.bones["{0}"].rotation_quaternion'.format(selected_bone.name)
if self.rot_type == "EULER":
return 'pose.bones["{0}"].rotation_euler'.format(selected_bone.name)
return None
def get_curve_data(self,channel):
armat = algorithms.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 = 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,v 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:
algorithms.print_log_report("INFO","Aligning Z axis of {0} with Z axis of {1}".format(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 != None:
armature_z_axis[b_name] = source_armature.data.edit_bones[source_bone_name].z_axis.copy()
else:
algorithms.print_log_report("DEBUG","Bone {0} non mapped".format(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)
def name_combinations(self, 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(b_id+junct+s_id)
combinations.append(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, debug = False):
if len(childr_identifiers) > 0:
for bone_name in bones_to_scan:
x_bone = self.get_bone(armat,bone_name)
if x_bone:
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
def get_bones_by_index(self, 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 != None:
try:
return bones_chain[index]
except:
algorithms.print_log_report("WARNING","The chain {0} of mocap file has less bones than the chain in the lab".format(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
def get_bone_chains(self, armat, bone_names):
found_chains = []
for bone_name in bone_names:
bn = armat.data.bones[bone_name]
chain_names = [b.name for b in bn.parent_recursive]
chain = [bone_name]+chain_names
found_chains.append(chain)
return found_chains
def get_all_bone_names(self,armat):
bone_names = []
for bn in armat.data.bones:
bone_names.append(bn.name)
return bone_names
def is_in_side(self,bone_names,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"]
combo_bones_start = []
combo_bones_end = []
score_level = 0.0
if side == "RIGHT":
ID_side1 = "r"
ID_side2 = "right"
ID_side3 = ["r.","r_"]
ID_side4 = ["_r",".r"]
if side == "LEFT":
ID_side1 = "l"
ID_side2 = "left"
ID_side3 = ["l.","l_"]
ID_side4 = ["_l",".l"]
for b_ID in bone_IDs:
combo_bones_start.append(ID_side1 + b_ID)
combo_bones_end.append(b_ID + ID_side1)
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 len(bone_names) != 0:
final_score = score_level/len(bone_names)
else:
return 0
return final_score
def order_with_list(self,bones_set,bones_list):
ordered_bones = []
for nm in bones_list:
if nm in bones_set:
ordered_bones.append(nm)
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):
if chain_inters == None:
chain_inters = chain
else:
chain_inters = chain_inters.intersection(chain)
result_chain = self.order_with_list(chain_inters,chains[i])
return result_chain
def filter_chains_by_max_length(self,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 len(center_chains) == 0:
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
def filter_chains_by_tail(self,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
def clear_chain_by_dot_product(self, 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:
algorithms.print_log_report("INFO","Retarget: Bone {0} removed BY DOT".format(bone_name))
chain.remove(bone_name)
algorithms.select_and_change_mode(armature,'POSE')#TODO: store the status and restore it
return chain
def clear_chain_by_length(self, 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:
algorithms.print_log_report("INFO","Retarget: Bone {0} removed BY LENGTH".format(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)
def filter_chains_by_ID(self,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
def filter_chains_by_order(self, chains, n_ord):
named_fingers = ["thu","ind","mid","ring","pink"]
identifiers = []
for chain in chains:
if len(chain) > 0:
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, debug = False):
arm_chain_IDs = ["arm","elbow","hand","wrist","finger","thumb","index","ring","pink","mid"]
leg_chain_IDs = ["thigh","upperleg","upper_leg","leg","knee","shin","calf","lowerleg","lower_leg","foot","ankle","toe","ball"]
head_chain_IDs = ["head","neck","skull","face","spine"]
finger_chain_IDs = ["finger","thumb","index","ring","pink","mid"]
foot_chain_IDs = ["foot","ankle","toe","ball"]
max_right_arm_chain = []
max_left_arm_chain = []
max_right_leg_chain = []
max_left_leg_chain = []
max_head_chain = []
max_left_finger_chains = []
max_right_finger_chains = []
left_chains,center_chains,right_chains = self.filter_chains_by_side(chains)
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)
arms_tail_chains = self.filter_chains_by_ID(chains,arm_chain_IDs)
arms_tail_chains = self.filter_chains_by_max_length(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)
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)
right_fingers_tail_chains = self.filter_chains_by_tail(right_chains,finger_chain_IDs)
left_fingers_tail_chains = self.filter_chains_by_tail(left_chains,finger_chain_IDs)
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)
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)
feet_tail_chains = self.filter_chains_by_tail(chains,foot_chain_IDs)
spine_chain = self.chains_intersection(arms_tail_chains)
head_and_spine_chains = self.chains_intersection(head_tail_chains)
head_chain = self.chains_difference(head_and_spine_chains,spine_chain)
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]
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]
r_arm_spine_chain = self.chains_intersection(right_arm_tail_chains)
right_arm_chain = self.chains_difference(r_arm_spine_chain,spine_chain)
l_arm_spine_chain = self.chains_intersection(left_arm_tail_chains)
left_arm_chain = self.chains_difference(l_arm_spine_chain,spine_chain)
r_leg_and_spine_chain = self.chains_intersection(right_foot_tail_chains)
l_leg_and_spine_chain = self.chains_intersection(left_foot_tail_chains)
right_leg_chain = self.chains_difference(r_leg_and_spine_chain,spine_chain)
left_leg_chain = self.chains_difference(l_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_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)
pelvis_chain = self.chains_intersection(feet_tail_chains)
r_finger0_chain = self.filter_chains_by_order(right_fingers_chain, 0)
r_finger1_chain = self.filter_chains_by_order(right_fingers_chain, 1)
r_finger2_chain = self.filter_chains_by_order(right_fingers_chain, 2)
r_finger3_chain = self.filter_chains_by_order(right_fingers_chain, 3)
r_finger4_chain = self.filter_chains_by_order(right_fingers_chain, 4)
l_finger0_chain = self.filter_chains_by_order(left_fingers_chain, 0)
l_finger1_chain = self.filter_chains_by_order(left_fingers_chain, 1)
l_finger2_chain = self.filter_chains_by_order(left_fingers_chain, 2)
l_finger3_chain = self.filter_chains_by_order(left_fingers_chain, 3)
l_finger4_chain = self.filter_chains_by_order(left_fingers_chain, 4)
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 = r_finger0_chain
self.rfinger1_bones_names = r_finger1_chain
self.rfinger2_bones_names = r_finger2_chain
self.rfinger3_bones_names = r_finger3_chain
self.rfinger4_bones_names = r_finger4_chain
self.lfinger0_bones_names = l_finger0_chain
self.lfinger1_bones_names = l_finger1_chain
self.lfinger2_bones_names = l_finger2_chain
self.lfinger3_bones_names = l_finger3_chain
self.lfinger4_bones_names = l_finger4_chain
def get_ending_bones(self, armat):
found_bones = set()
for bn in armat.data.bones:
if len(bn.children) == 0:
found_bones.add(bn.name)
return found_bones
def string_similarity(self, 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 self.knowledge_database:
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:
algorithms.print_log_report("INFO","Retarget: Bone {0} found BY EXACT NAME".format(bone_type))
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
algorithms.print_log_report("INFO","Retarget: {0} added to mapped bones".format(result))
return result
if s_method == "by_similar_name":
result = self.get_bone_by_similar_ID(bones_chain, main_IDs, side)
if result:
algorithms.print_log_report("INFO","Retarget: Bone {0} found BY SIMILAR NAME".format(bone_type))
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
algorithms.print_log_report("INFO","Retarget: {0} added to mapped bones".format(result))
return result
if s_method == "by_children":
result = self.get_bone_by_childr(armat, bones_chain, children_IDs)
if result:
algorithms.print_log_report("INFO","Retarget: Bone {0} found BY CHILDREN".format(bone_type))
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
algorithms.print_log_report("INFO","Retarget: {0} added to mapped bones".format(result))
return result
if s_method == "by_chain_index":
result = self.get_bones_by_index(bones_chain,position_in_chain)
if result:
algorithms.print_log_report("INFO","Retarget: Bone {0} found BY CHAIN INDEX".format(bone_type))
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
algorithms.print_log_report("INFO","Retarget: {0} added to mapped bones".format(result))
return result
algorithms.print_log_report("WARNING","All retarget methods failed for {0}.".format(bone_type))
#algorithms.print_log_report("WARNING","No candidates found in: {0}, or the candidate found is already mapped to another bone".format(bones_chain))
return None
else:
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
def get_target_editbone(self,armat,b_name,):
if bpy.context.object.mode == "EDIT":
if b_name:
ebone = algorithms.get_edit_bone(armat, b_name)
if ebone:
return ebone
else:
algorithms.print_log_report("WARNING","{0} not found in edit mode of target armature {1}".format(b_name,armat))
return None
else:
algorithms.print_log_report("WARNING","Warning: Can't get the edit bone of {0} because the mode is {1}".format(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
else:
algorithms.print_log_report("WARNING","{0} not found in edit mode of source armature {1}".format(b_name,armat))
return None
else:
algorithms.print_log_report("WARNING","Warning: Can't get the edit bone of {0} because the mode is {1}".format(bpy.context.scene.objects.active,bpy.context.object.mode))
return None
def get_mapped_name(self, b_name):
if b_name in self.skeleton_mapped:
return self.skeleton_mapped[b_name]
else:
return None
def map_bone(self,armat,b_name,b_type,s_method):
mapped_name = self.find_bone(armat,b_type,s_method)
if mapped_name != 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
algorithms.print_log_report("WARNING","Error in mapping {1} as direct parent of {0}".format(childr_name,map_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,False)
self.filter_chains_by_length(armat)
self.filter_chains_by_dotprod(armat)
self.map_bone(armat,"clavicle_L","LCLAVICLE","by_exact_name")
self.map_bone(armat,"clavicle_R","RCLAVICLE","by_exact_name")
self.map_bone(armat,"head","HEAD","by_exact_name")
self.map_bone(armat,"lowerarm_R","RFOREARM","by_exact_name")
self.map_bone(armat,"lowerarm_L","LFOREARM","by_exact_name")
self.map_bone(armat,"upperarm_R","RUPPERARM","by_children")
self.map_bone(armat,"upperarm_L","LUPPERARM","by_children")
self.map_bone(armat,"hand_R","RHAND","by_exact_name")
self.map_bone(armat,"hand_L","LHAND","by_exact_name")
self.map_bone(armat,"breast_R","RBREAST","by_exact_name")
self.map_bone(armat,"breast_L","LBREAST","by_exact_name")
self.map_bone(armat,"calf_R","RCALF","by_exact_name")
self.map_bone(armat,"calf_L","LCALF","by_exact_name")
self.map_bone(armat,"foot_R","RFOOT","by_exact_name")
self.map_bone(armat,"foot_L","LFOOT","by_exact_name")
self.map_bone(armat,"toes_R","RTOE","by_exact_name")
self.map_bone(armat,"toes_L","LTOE","by_exact_name")
self.map_bone(armat,"pelvis","PELVIS","by_exact_name")
self.map_bone(armat,"spine03","CHEST","by_chain_index")
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")
self.map_bone(armat,"thumb03_R","RTHUMB03","by_chain_index")
self.map_bone(armat,"thumb02_R","RTHUMB02","by_chain_index")
self.map_bone(armat,"thumb01_R","RTHUMB01","by_chain_index")
self.map_bone(armat,"index03_R","RINDEX03","by_chain_index")
self.map_bone(armat,"index02_R","RINDEX02","by_chain_index")
self.map_bone(armat,"index01_R","RINDEX01","by_chain_index")
self.map_bone(armat,"index00_R","RINDEX00","by_exact_name")
self.map_bone(armat,"middle03_R","RMIDDLE03","by_chain_index")
self.map_bone(armat,"middle02_R","RMIDDLE02","by_chain_index")
self.map_bone(armat,"middle01_R","RMIDDLE01","by_chain_index")
self.map_bone(armat,"middle00_R","RMIDDLE00","by_exact_name")
self.map_bone(armat,"ring03_R","RRING03","by_chain_index")
self.map_bone(armat,"ring02_R","RRING02","by_chain_index")
self.map_bone(armat,"ring01_R","RRING01","by_chain_index")
self.map_bone(armat,"ring00_R","RRING00","by_exact_name")
self.map_bone(armat,"pinky03_R","RPINKY03","by_chain_index")
self.map_bone(armat,"pinky02_R","RPINKY02","by_chain_index")
self.map_bone(armat,"pinky01_R","RPINKY01","by_chain_index")
self.map_bone(armat,"pinky00_R","RPINKY00","by_exact_name")
self.map_bone(armat,"thumb03_L","LTHUMB03","by_chain_index")
self.map_bone(armat,"thumb02_L","LTHUMB02","by_chain_index")