forked from jkirsons/FacialMotionCapture
-
Notifications
You must be signed in to change notification settings - Fork 3
/
OpenCVAnimOperator.py
181 lines (145 loc) · 7.89 KB
/
OpenCVAnimOperator.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
import bpy
from imutils import face_utils
import dlib
import cv2
import time
import numpy
from bpy.props import FloatProperty
class OpenCVAnimOperator(bpy.types.Operator):
"""Operator which runs its self from a timer"""
bl_idname = "wm.opencv_operator"
bl_label = "OpenCV Animation Operator"
# p = our pre-treined model directory
#p = "/Users/jason/Downloads/shape_predictor_68_face_landmarks.dat" # macOS
p = "/home/jason/Downloads/shape_predictor_68_face_landmarks.dat" # linux
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(p)
_timer = None
_cap = None
width = 800
height = 600
stop :bpy.props.BoolProperty()
# 3D model points.
model_points = numpy.array([
(0.0, 0.0, 0.0), # Nose tip
(0.0, -330.0, -65.0), # Chin
(-225.0, 170.0, -135.0), # Left eye left corner
(225.0, 170.0, -135.0), # Right eye right corne
(-150.0, -150.0, -125.0), # Left Mouth corner
(150.0, -150.0, -125.0) # Right mouth corner
], dtype = numpy.float32)
# Camera internals
camera_matrix = numpy.array(
[[height, 0.0, width/2],
[0.0, height, height/2],
[0.0, 0.0, 1.0]], dtype = numpy.float32
)
# Keeps a moving average of given length
def smooth_value(self, name, length, value):
if not hasattr(self, 'smooth'):
self.smooth = {}
if not name in self.smooth:
self.smooth[name] = numpy.array([value])
else:
self.smooth[name] = numpy.insert(arr=self.smooth[name], obj=0, values=value)
if self.smooth[name].size > length:
self.smooth[name] = numpy.delete(self.smooth[name], self.smooth[name].size-1, 0)
sum = 0
for val in self.smooth[name]:
sum += val
return sum / self.smooth[name].size
# Keeps min and max values, then returns the value in a ranve 0 - 1
def get_range(self, name, value):
if not hasattr(self, 'range'):
self.range = {}
if not name in self.range:
self.range[name] = numpy.array([value, value])
else:
self.range[name] = numpy.array([min(value, self.range[name][0]), max(value, self.range[name][1])] )
val_range = self.range[name][1] - self.range[name][0]
if val_range != 0:
return (value - self.range[name][0]) / val_range
else:
return 0
def modal(self, context, event):
if (event.type in {'RIGHTMOUSE', 'ESC'}) or self.stop == True:
self.cancel(context)
return {'CANCELLED'}
if event.type == 'TIMER':
self.init_camera()
_, image = self._cap.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
rects = self.detector(gray, 0)
# bpy.context.scene.frame_set(frame_num)
# For each detected face, find the landmark.
for (i, rect) in enumerate(rects):
shape = self.predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
#2D image points. If you change the image, you need to change vector
image_points = numpy.array([shape[30], # Nose tip - 31
shape[8], # Chin - 9
shape[36], # Left eye left corner - 37
shape[45], # Right eye right corne - 46
shape[48], # Left Mouth corner - 49
shape[54] # Right mouth corner - 55
], dtype = numpy.float32)
dist_coeffs = numpy.zeros((4,1)) # Assuming no lens distortion
if hasattr(self, 'rotation_vector'):
(success, self.rotation_vector, self.translation_vector) = cv2.solvePnP(self.model_points,
image_points, self.camera_matrix, dist_coeffs, flags=cv2.SOLVEPNP_ITERATIVE,
rvec=self.rotation_vector, tvec=self.translation_vector,
useExtrinsicGuess=True)
else:
(success, self.rotation_vector, self.translation_vector) = cv2.solvePnP(self.model_points,
image_points, self.camera_matrix, dist_coeffs, flags=cv2.SOLVEPNP_ITERATIVE,
useExtrinsicGuess=False)
if not hasattr(self, 'first_angle'):
self.first_angle = numpy.copy(self.rotation_vector)
bones = bpy.data.objects["RIG-Vincent"].pose.bones
bones["head_fk"].rotation_euler[0] = self.smooth_value("h_x", 3, (self.rotation_vector[0] - self.first_angle[0])) / 1 # Up/Down
bones["head_fk"].rotation_euler[2] = self.smooth_value("h_y", 3, -(self.rotation_vector[1] - self.first_angle[1])) / 1.5 # Rotate
bones["head_fk"].rotation_euler[1] = self.smooth_value("h_z", 3, (self.rotation_vector[2] - self.first_angle[2])) / 1.3 # Left/Right
bones["mouth_ctrl"].location[2] = self.smooth_value("m_h", 2, -self.get_range("mouth_height", numpy.linalg.norm(shape[62] - shape[66])) * 0.06 )
bones["mouth_ctrl"].location[0] = self.smooth_value("m_w", 2, (self.get_range("mouth_width", numpy.linalg.norm(shape[54] - shape[48])) - 0.5) * -0.04)
bones["brow_ctrl_L"].location[2] = self.smooth_value("b_l", 3, (self.get_range("brow_left", numpy.linalg.norm(shape[19] - shape[27])) -0.5) * 0.04)
bones["brow_ctrl_R"].location[2] = self.smooth_value("b_r", 3, (self.get_range("brow_right", numpy.linalg.norm(shape[24] - shape[27])) -0.5) * 0.04)
bones["head_fk"].keyframe_insert(data_path="rotation_euler", index=-1)
bones["mouth_ctrl"].keyframe_insert(data_path="location", index=-1)
bones["brow_ctrl_L"].keyframe_insert(data_path="location", index=2)
bones["brow_ctrl_R"].keyframe_insert(data_path="location", index=2)
for (x, y) in shape:
cv2.circle(image, (x, y), 2, (0, 255, 255), -1)
cv2.imshow("Output", image)
cv2.waitKey(1)
return {'PASS_THROUGH'}
def init_camera(self):
if self._cap == None:
self._cap = cv2.VideoCapture(0)
self._cap.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
self._cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
self._cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
time.sleep(0.5)
def stop_playback(self, scene):
print(format(scene.frame_current) + " / " + format(scene.frame_end))
if scene.frame_current == scene.frame_end:
bpy.ops.screen.animation_cancel(restore_frame=False)
def execute(self, context):
bpy.app.handlers.frame_change_pre.append(self.stop_playback)
wm = context.window_manager
self._timer = wm.event_timer_add(0.02, window=context.window)
wm.modal_handler_add(self)
return {'RUNNING_MODAL'}
def cancel(self, context):
wm = context.window_manager
wm.event_timer_remove(self._timer)
cv2.destroyAllWindows()
self._cap.release()
self._cap = None
def register():
bpy.utils.register_class(OpenCVAnimOperator)
def unregister():
bpy.utils.unregister_class(OpenCVAnimOperator)
if __name__ == "__main__":
register()
# test call
#bpy.ops.wm.opencv_operator()