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import numpy as np
from enum import Enum
class BodyIdentifier(Enum):
INDEX_FINGER_DIP_right = 0
INDEX_FINGER_MCP_right = 1
INDEX_FINGER_PIP_right = 2
INDEX_FINGER_TIP_right = 3
MIDDLE_FINGER_DIP_right = 4
MIDDLE_FINGER_MCP_right = 5
MIDDLE_FINGER_PIP_right = 6
MIDDLE_FINGER_TIP_right = 7
PINKY_DIP_right = 8
PINKY_MCP_right = 9
PINKY_PIP_right = 10
PINKY_TIP_right = 11
RING_FINGER_DIP_right = 12
RING_FINGER_MCP_right = 13
RING_FINGER_PIP_right = 14
RING_FINGER_TIP_right = 15
THUMB_CMC_right = 16
THUMB_IP_right = 17
THUMB_MCP_right = 18
THUMB_TIP_right = 19
WRIST_right = 20
INDEX_FINGER_DIP_left = 21
INDEX_FINGER_MCP_left = 22
INDEX_FINGER_PIP_left = 23
INDEX_FINGER_TIP_left = 24
MIDDLE_FINGER_DIP_left = 25
MIDDLE_FINGER_MCP_left = 26
MIDDLE_FINGER_PIP_left = 27
MIDDLE_FINGER_TIP_left = 28
PINKY_DIP_left = 29
PINKY_MCP_left = 30
PINKY_PIP_left = 31
PINKY_TIP_left = 32
RING_FINGER_DIP_left = 33
RING_FINGER_MCP_left = 34
RING_FINGER_PIP_left = 35
RING_FINGER_TIP_left = 36
THUMB_CMC_left = 37
THUMB_IP_left = 38
THUMB_MCP_left = 39
THUMB_TIP_left = 40
WRIST_left = 41
RIGHT_SHOULDER = 42
LEFT_SHOULDER = 43
LEFT_ELBOW = 44
RIGHT_ELBOW = 45
class Graph():
""" The Graph to model the skeletons extracted by the openpose
Args:
strategy (string): must be one of the follow candidates
- uniform: Uniform Labeling
- distance: Distance Partitioning
- spatial: Spatial Configuration
For more information, please refer to the section 'Partition Strategies'
in our paper (https://arxiv.org/abs/1801.07455).
layout (string): must be one of the follow candidates
- openpose: Is consists of 18 joints. For more information, please
refer to https://github.com/CMU-Perceptual-Computing-Lab/openpose#output
- ntu-rgb+d: Is consists of 25 joints. For more information, please
refer to https://github.com/shahroudy/NTURGB-D
max_hop (int): the maximal distance between two connected nodes
dilation (int): controls the spacing between the kernel points
"""
def __init__(self,
layout='openpose',
strategy='uniform',
max_hop=1,
dilation=1):
self.max_hop = max_hop
self.dilation = dilation
self.get_edge(layout)
self.hop_dis = get_hop_distance(
self.num_node, self.edge, max_hop=max_hop)
self.get_adjacency(strategy)
def __str__(self):
return self.A
def get_edge(self, layout):
if layout == 'openpose':
self.num_node = 18
self_link = [(i, i) for i in range(self.num_node)]
neighbor_link = [(4, 3), (3, 2), (7, 6), (6, 5), (13, 12), (12,
11),
(10, 9), (9, 8), (11, 5), (8, 2), (5, 1), (2, 1),
(0, 1), (15, 0), (14, 0), (17, 15), (16, 14)]
self.edge = self_link + neighbor_link
self.center = 1
elif layout == 'ntu-rgb+d':
self.num_node = 25
self_link = [(i, i) for i in range(self.num_node)]
neighbor_1base = [(1, 2), (2, 21), (3, 21), (4, 3), (5, 21),
(6, 5), (7, 6), (8, 7), (9, 21), (10, 9),
(11, 10), (12, 11), (13, 1), (14, 13), (15, 14),
(16, 15), (17, 1), (18, 17), (19, 18), (20, 19),
(22, 23), (23, 8), (24, 25), (25, 12)]
neighbor_link = [(i - 1, j - 1) for (i, j) in neighbor_1base]
self.edge = self_link + neighbor_link
self.center = 21 - 1
elif layout == 'ntu_edge':
self.num_node = 24
self_link = [(i, i) for i in range(self.num_node)]
neighbor_1base = [(1, 2), (3, 2), (4, 3), (5, 2), (6, 5), (7, 6),
(8, 7), (9, 2), (10, 9), (11, 10), (12, 11),
(13, 1), (14, 13), (15, 14), (16, 15), (17, 1),
(18, 17), (19, 18), (20, 19), (21, 22), (22, 8),
(23, 24), (24, 12)]
neighbor_link = [(i - 1, j - 1) for (i, j) in neighbor_1base]
self.edge = self_link + neighbor_link
self.center = 2
elif layout == 'mediapipe':
self.num_node = 25
self_link = [(i, i) for i in range(self.num_node)]
neighbor_1base = [(20, 18), (18, 16), (20, 16), (16, 22), (16, 14), (14, 12),
(19, 17), (17, 15), (19, 15), (15, 21), (15, 13), (13, 11),
(12, 11), (12, 24), (24, 23), (23, 11),
(10, 9),
(0, 4), (4, 5), (5, 6), (6, 8),
(0, 1), (1, 2), (2, 3), (3, 7)]
neighbor_link = [(i - 1, j - 1) for (i, j) in neighbor_1base]
self.edge = self_link + neighbor_link
self.center = 10
elif layout == "mediapipe_two_hand":
self.num_node = 46
self_link = [(i, i) for i in range(self.num_node)]
neighbor_1base = [(BodyIdentifier.WRIST_left.value, BodyIdentifier.THUMB_CMC_left.value),
(BodyIdentifier.THUMB_CMC_left.value, BodyIdentifier.THUMB_MCP_left.value),
(BodyIdentifier.THUMB_MCP_left.value, BodyIdentifier.THUMB_IP_left.value),
(BodyIdentifier.THUMB_IP_left.value, BodyIdentifier.THUMB_TIP_left.value),
(BodyIdentifier.WRIST_left.value, BodyIdentifier.INDEX_FINGER_MCP_left.value),
(BodyIdentifier.INDEX_FINGER_MCP_left.value, BodyIdentifier.INDEX_FINGER_PIP_left.value),
(BodyIdentifier.INDEX_FINGER_PIP_left.value, BodyIdentifier.INDEX_FINGER_DIP_left.value),
(BodyIdentifier.INDEX_FINGER_DIP_left.value, BodyIdentifier.INDEX_FINGER_TIP_left.value),
(BodyIdentifier.INDEX_FINGER_MCP_left.value, BodyIdentifier.MIDDLE_FINGER_MCP_left.value),
(BodyIdentifier.MIDDLE_FINGER_MCP_left.value, BodyIdentifier.MIDDLE_FINGER_PIP_left.value),
(BodyIdentifier.MIDDLE_FINGER_PIP_left.value, BodyIdentifier.MIDDLE_FINGER_DIP_left.value),
(BodyIdentifier.MIDDLE_FINGER_DIP_left.value, BodyIdentifier.MIDDLE_FINGER_TIP_left.value),
(BodyIdentifier.MIDDLE_FINGER_MCP_left.value, BodyIdentifier.RING_FINGER_MCP_left.value),
(BodyIdentifier.RING_FINGER_MCP_left.value, BodyIdentifier.RING_FINGER_PIP_left.value),
(BodyIdentifier.RING_FINGER_PIP_left.value, BodyIdentifier.RING_FINGER_DIP_left.value),
(BodyIdentifier.RING_FINGER_DIP_left.value, BodyIdentifier.RING_FINGER_TIP_left.value),
(BodyIdentifier.WRIST_left.value, BodyIdentifier.PINKY_MCP_left.value),
(BodyIdentifier.PINKY_MCP_left.value, BodyIdentifier.PINKY_PIP_left.value),
(BodyIdentifier.PINKY_PIP_left.value, BodyIdentifier.PINKY_DIP_left.value),
(BodyIdentifier.PINKY_DIP_left.value, BodyIdentifier.PINKY_TIP_left.value),
# RIGHT HAND
(BodyIdentifier.WRIST_right.value, BodyIdentifier.THUMB_CMC_right.value),
(BodyIdentifier.THUMB_CMC_right.value, BodyIdentifier.THUMB_MCP_right.value),
(BodyIdentifier.THUMB_MCP_right.value, BodyIdentifier.THUMB_IP_right.value),
(BodyIdentifier.THUMB_IP_right.value, BodyIdentifier.THUMB_TIP_right.value),
(BodyIdentifier.WRIST_right.value, BodyIdentifier.INDEX_FINGER_MCP_right.value),
(BodyIdentifier.INDEX_FINGER_MCP_right.value, BodyIdentifier.INDEX_FINGER_PIP_right.value),
(BodyIdentifier.INDEX_FINGER_PIP_right.value, BodyIdentifier.INDEX_FINGER_DIP_right.value),
(BodyIdentifier.INDEX_FINGER_DIP_right.value, BodyIdentifier.INDEX_FINGER_TIP_right.value),
(BodyIdentifier.INDEX_FINGER_MCP_right.value, BodyIdentifier.MIDDLE_FINGER_MCP_right.value),
(BodyIdentifier.MIDDLE_FINGER_MCP_right.value, BodyIdentifier.MIDDLE_FINGER_PIP_right.value),
(BodyIdentifier.MIDDLE_FINGER_PIP_right.value, BodyIdentifier.MIDDLE_FINGER_DIP_right.value),
(BodyIdentifier.MIDDLE_FINGER_DIP_right.value, BodyIdentifier.MIDDLE_FINGER_TIP_right.value),
(BodyIdentifier.MIDDLE_FINGER_MCP_right.value, BodyIdentifier.RING_FINGER_MCP_right.value),
(BodyIdentifier.RING_FINGER_MCP_right.value, BodyIdentifier.RING_FINGER_PIP_right.value),
(BodyIdentifier.RING_FINGER_PIP_right.value, BodyIdentifier.RING_FINGER_DIP_right.value),
(BodyIdentifier.RING_FINGER_DIP_right.value, BodyIdentifier.RING_FINGER_TIP_right.value),
(BodyIdentifier.WRIST_right.value, BodyIdentifier.PINKY_MCP_right.value),
(BodyIdentifier.PINKY_MCP_right.value, BodyIdentifier.PINKY_PIP_right.value),
(BodyIdentifier.PINKY_PIP_right.value, BodyIdentifier.PINKY_DIP_right.value),
(BodyIdentifier.PINKY_DIP_right.value, BodyIdentifier.PINKY_TIP_right.value),
# 2 HAND + SHOULDER + ELBOW
(BodyIdentifier.RIGHT_SHOULDER.value, BodyIdentifier.RIGHT_ELBOW.value),
(BodyIdentifier.RIGHT_ELBOW.value, BodyIdentifier.WRIST_right.value),
(BodyIdentifier.RIGHT_SHOULDER.value, BodyIdentifier.LEFT_SHOULDER.value),
(BodyIdentifier.LEFT_SHOULDER.value, BodyIdentifier.LEFT_ELBOW.value),
(BodyIdentifier.LEFT_ELBOW.value, BodyIdentifier.WRIST_left.value)]
neighbor_link = [(i, j) for (i, j) in neighbor_1base]
self.edge = self_link + neighbor_link
self.center = BodyIdentifier.RIGHT_SHOULDER.value
# elif layout=='customer settings'
# pass
else:
raise ValueError("Do Not Exist This Layout.")
def get_adjacency(self, strategy):
valid_hop = range(0, self.max_hop + 1, self.dilation)
adjacency = np.zeros((self.num_node, self.num_node))
for hop in valid_hop:
adjacency[self.hop_dis == hop] = 1
normalize_adjacency = normalize_digraph(adjacency)
if strategy == 'uniform':
A = np.zeros((1, self.num_node, self.num_node))
A[0] = normalize_adjacency
self.A = A
elif strategy == 'distance':
A = np.zeros((len(valid_hop), self.num_node, self.num_node))
for i, hop in enumerate(valid_hop):
A[i][self.hop_dis == hop] = normalize_adjacency[self.hop_dis ==
hop]
self.A = A
elif strategy == 'spatial':
A = []
for hop in valid_hop:
a_root = np.zeros((self.num_node, self.num_node))
a_close = np.zeros((self.num_node, self.num_node))
a_further = np.zeros((self.num_node, self.num_node))
for i in range(self.num_node):
for j in range(self.num_node):
if self.hop_dis[j, i] == hop:
if self.hop_dis[j, self.center] == self.hop_dis[
i, self.center]:
a_root[j, i] = normalize_adjacency[j, i]
elif self.hop_dis[j, self.
center] > self.hop_dis[i, self.
center]:
a_close[j, i] = normalize_adjacency[j, i]
else:
a_further[j, i] = normalize_adjacency[j, i]
if hop == 0:
A.append(a_root)
else:
A.append(a_root + a_close)
A.append(a_further)
A = np.stack(A)
self.A = A
else:
raise ValueError("Do Not Exist This Strategy")
def get_hop_distance(num_node, edge, max_hop=1):
A = np.zeros((num_node, num_node))
print(edge)
for i, j in edge:
A[j, i] = 1
A[i, j] = 1
# compute hop steps
hop_dis = np.zeros((num_node, num_node)) + np.inf
transfer_mat = [np.linalg.matrix_power(A, d) for d in range(max_hop + 1)]
arrive_mat = (np.stack(transfer_mat) > 0)
for d in range(max_hop, -1, -1):
hop_dis[arrive_mat[d]] = d
return hop_dis
def normalize_digraph(A):
Dl = np.sum(A, 0)
num_node = A.shape[0]
Dn = np.zeros((num_node, num_node))
for i in range(num_node):
if Dl[i] > 0:
Dn[i, i] = Dl[i]**(-1)
AD = np.dot(A, Dn)
return AD
def normalize_undigraph(A):
Dl = np.sum(A, 0)
num_node = A.shape[0]
Dn = np.zeros((num_node, num_node))
for i in range(num_node):
if Dl[i] > 0:
Dn[i, i] = Dl[i]**(-0.5)
DAD = np.dot(np.dot(Dn, A), Dn)
return DAD |