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import cv2
import numpy as np
def get_eye_nose_landmarks(landmarks):
assert landmarks.shape[0]==50 or landmarks.shape[0]==68
if landmarks.shape[0] == 50:
lm_6 = landmarks[[20, 23, 26, 29, 15, 19], :] # the eye and nose landmarks
elif landmarks.shape[0] == 68:
lm_6 = landmarks[[36, 39, 42, 45, 31, 35], :] # the eye and nose landmarks
return lm_6
def get_eye_mouth_landmarks(landmarks):
assert landmarks.shape[0]==50 or landmarks.shape[0]==68
if landmarks.shape[0] == 50:
lm_6 = landmarks[[20, 23, 26, 29, 32, 38], :] # the eye and nose landmarks
elif landmarks.shape[0] == 68:
lm_6 = landmarks[[36,39,42,45,48,54], :] # the eye and nose landmarks
return lm_6
def mean_eye_nose(landmarks):
assert landmarks.shape[0]==6
# get the face center
two_eye_center = np.mean(landmarks[0:4, :], axis=0).reshape(1,-1)
nose_center = np.mean(landmarks[4:6, :], axis=0).reshape(1,-1)
face_center = np.mean(np.concatenate((two_eye_center, nose_center), axis=0), axis=0).reshape(1,-1)
return face_center
def mean_eye_mouth(landmarks):
assert landmarks.shape[0]==6
face_center = np.mean(landmarks, axis=0).reshape(1,-1)
return face_center
def get_face_center_by_nose(hR, ht, face_model_load):
face_model = get_eye_nose_landmarks(face_model_load) # the eye and nose landmarks
Fc = np.dot(hR, face_model.T) + ht # 3D positions of facial landmarks
face_center = mean_eye_nose(Fc.T).reshape((3, 1)) # get the face center
return face_center, Fc
def get_face_center_by_mouth(hR, ht, face_model_load):
face_model = get_eye_mouth_landmarks(face_model_load) # the eye and nose landmarks
Fc = np.dot(hR, face_model.T) + ht # 3D positions of facial landmarks
face_center = mean_eye_mouth(Fc.T).reshape((3, 1)) # get the face center
return face_center, Fc
def lm68_to_50(lm_68):
'''
lm_68: (68,2)
'''
lm_50 = np.zeros((50,2))
lm_50[0] = lm_68[8]
lm_50[1:44] = lm_68[17:60]
lm_50[44:47] = lm_68[61:64]
lm_50[47:50] = lm_68[65:68]
return lm_50
def lm68_subset(lm_68, NUM_KPTS_TO_USE):
'''
lm_68: (68,2)
'''
if NUM_KPTS_TO_USE == 6:
lm_68 = np.array(lm_68, dtype=np.float32)
return lm_68[[36, 39, 42, 45, 31, 35], :]
elif NUM_KPTS_TO_USE ==50:
return lm68_to_50(lm_68)
else:
print('not supported yet')
exit(0)
def lm50_subset(lm_50, NUM_KPTS_TO_USE):
'''
lm_50: (50,2)
'''
lm_50 = lm_50.copy()
if NUM_KPTS_TO_USE == 6:
lm_50 = lm_50[[20, 23, 26, 29, 15, 19], :]
return lm_50
elif NUM_KPTS_TO_USE ==50:
return lm_50
else:
print('not supported yet')
exit(0)
def get_face_center(landmarks_3d):
'''
landmarks_3d: (3, 6)
-->
face_center: (3,1)
'''
two_eye_center = np.mean(landmarks_3d[:, 0:4], axis=1).reshape((3, 1))
nose_center = np.mean(landmarks_3d[:, 4:6], axis=1).reshape((3, 1))
face_center = np.mean(np.concatenate((two_eye_center, nose_center), axis=1), axis=1).reshape((3, 1))
return face_center
def compute_R(lm6, dataname):
'''
6 landmarks in opencv coordinate
dataname: mpii or xgaze
the face center are computed differently
for mpii: the 6 landmarks are 4 eye + 2 mouth
for xgaze: the 6 landmarks are 4 eye + 2 nose
'''
if dataname=='mpii':
left_center = np.mean(lm6[2:4,:],axis=0)
right_center = np.mean(lm6[:2,:],axis=0)
face_center = np.mean(lm6,axis=0)
elif dataname=='xgaze':
left_center = np.mean(lm6[2:4,:],axis=0)
right_center = np.mean(lm6[:2,:],axis=0)
nose_center = np.mean(lm6[[4,5],:],axis=0)
face_center = ( (left_center + right_center)/2 + nose_center ) /2
distance = np.linalg.norm(face_center)
hRx = left_center - right_center
hRx /= np.linalg.norm(hRx)
forward = (face_center/distance).reshape(3)
down = np.cross(forward, hRx)
down /= np.linalg.norm(down)
right = np.cross(down, forward)
right /= np.linalg.norm(right)
R = np.c_[right, down, forward].T
return R
def rotation_matrix(x, y, z):
'''
x, y, z: roll, pitch, yaw, (radians)
'''
Rx = np.array([[1,0,0],
[0, np.cos(x), -np.sin(x)],
[0, np.sin(x), np.cos(x)]])
Ry = np.array([[ np.cos(y), 0, np.sin(y)],
[ 0, 1, 0],
[-np.sin(y), 0, np.cos(y)]])
Rz = np.array([[np.cos(z), -np.sin(z), 0],
[np.sin(z), np.cos(z), 0],
[0,0,1]])
return Rz@Ry@Rx
def get_rotation(from_pose, target_pose):
rotation1 = rotation_matrix( -from_pose[0], from_pose[1], 0)
rotation2 = rotation_matrix(-target_pose[0], target_pose[1], 0)
rotation = rotation2@np.linalg.inv(rotation1)
return rotation
def hR_2_hr(hR):
hr = np.array([np.arcsin(hR[1, 2]),
np.arctan2(hR[0, 2], hR[2, 2])])
return hr
def hr_2_hR(hr):
hR = rotation_matrix( -hr[0], hr[1], 0)
return hR
if __name__ == '__main__':
# hr_norm = np.array([0.15, 0.2])
# pose = np.array([-0.1, 0.3])
# rotation1 = rotation_matrix( -hr_norm[0], hr_norm[1], 0)
# rot = cv2.Rodrigues( np.array([hr_norm[0], hr_norm[1], 0]) )[0]
def to_hR(hr_norm):
hR_norm = rotation_matrix( -hr_norm[0], hr_norm[1], 0)
return hR_norm
hr1 = np.array([0.15, 0.2])
hr2 = np.array([0.10, 0.2])
hr_t = np.array([-0.1, 0.3])
hR1 = to_hR(hr1)
hR2 = to_hR(hr2)
print('hR1: ', hR1)
print('hR2: ', hR2)
R1t = get_rotation(hr1, hr_t)
hR1_ = np.dot(R1t, hR1)
print('rotated hR_: ', hR1_)
hr1_ = np.array([np.arcsin(hR1_[1, 2]),
np.arctan2(hR1_[0, 2], hR1_[2, 2])])
print('rotated hr1_: ', hr1_)
print('hR t: ', to_hR(hr_t))
hR2_ = np.dot(R1t, hR2)
print('rotated hR2_: ', hR2_)
# rotation2 = rotation_matrix( -pose[0], pose[1], 0)
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