Python cv2.decomposeProjectionMatrix() Examples
The following are 5
code examples of cv2.decomposeProjectionMatrix().
You can vote up the ones you like or vote down the ones you don't like,
and go to the original project or source file by following the links above each example.
You may also want to check out all available functions/classes of the module
cv2
, or try the search function
.
.
Example #1
| Source File: head_pose_solver.py From talking-head-anime-demo with MIT License | 8 votes |
|
def solve_head_pose(self, face_landmarks):
indices = [17, 21, 22, 26, 36, 39, 42, 45, 31, 35]
image_pts = np.zeros((len(indices), 2))
for i in range(len(indices)):
part = face_landmarks.part(indices[i])
image_pts[i, 0] = part.x
image_pts[i, 1] = part.y
_, rotation_vec, translation_vec = cv2.solvePnP(self.face_model_points,
image_pts,
self.camera_matrix,
self.distortion_coeffs)
projected_head_pose_box_points, _ = cv2.projectPoints(self.head_pose_box_points,
rotation_vec,
translation_vec,
self.camera_matrix,
self.distortion_coeffs)
projected_head_pose_box_points = tuple(map(tuple, projected_head_pose_box_points.reshape(8, 2)))
# Calculate euler angle
rotation_mat, _ = cv2.Rodrigues(rotation_vec)
pose_mat = cv2.hconcat((rotation_mat, translation_vec))
_, _, _, _, _, _, euler_angles = cv2.decomposeProjectionMatrix(pose_mat)
return projected_head_pose_box_points, euler_angles
Example #2
| Source File: headpose.py From face_landmark with Apache License 2.0 | 5 votes |
|
def get_head_pose(shape,img):
h,w,_=img.shape
K = [w, 0.0, w//2,
0.0, w, h//2,
0.0, 0.0, 1.0]
# Assuming no lens distortion
D = [0, 0, 0.0, 0.0, 0]
cam_matrix = np.array(K).reshape(3, 3).astype(np.float32)
dist_coeffs = np.array(D).reshape(5, 1).astype(np.float32)
# image_pts = np.float32([shape[17], shape[21], shape[22], shape[26], shape[36],
# shape[39], shape[42], shape[45], shape[31], shape[35],
# shape[48], shape[54], shape[57], shape[8]])
image_pts = np.float32([shape[17], shape[21], shape[22], shape[26], shape[36],
shape[39], shape[42], shape[45], shape[31], shape[35]])
_, rotation_vec, translation_vec = cv2.solvePnP(object_pts, image_pts, cam_matrix, dist_coeffs)
reprojectdst, _ = cv2.projectPoints(reprojectsrc, rotation_vec, translation_vec, cam_matrix,
dist_coeffs)
reprojectdst = tuple(map(tuple, reprojectdst.reshape(8, 2)))
# calc euler angle
rotation_mat, _ = cv2.Rodrigues(rotation_vec)
pose_mat = cv2.hconcat((rotation_mat, translation_vec))
_, _, _, _, _, _, euler_angle = cv2.decomposeProjectionMatrix(pose_mat)
return reprojectdst, euler_angle
Example #3
| Source File: pose.py From Peppa_Pig_Face_Engine with Apache License 2.0 | 5 votes |
|
def get_head_pose(shape,img):
h,w,_=img.shape
K = [w, 0.0, w//2,
0.0, w, h//2,
0.0, 0.0, 1.0]
# Assuming no lens distortion
D = [0, 0, 0.0, 0.0, 0]
cam_matrix = np.array(K).reshape(3, 3).astype(np.float32)
dist_coeffs = np.array(D).reshape(5, 1).astype(np.float32)
# image_pts = np.float32([shape[17], shape[21], shape[22], shape[26], shape[36],
# shape[39], shape[42], shape[45], shape[31], shape[35],
# shape[48], shape[54], shape[57], shape[8]])
image_pts = np.float32([shape[17], shape[21], shape[22], shape[26], shape[36],
shape[39], shape[42], shape[45], shape[31], shape[35]])
_, rotation_vec, translation_vec = cv2.solvePnP(object_pts, image_pts, cam_matrix, dist_coeffs)
reprojectdst, _ = cv2.projectPoints(reprojectsrc, rotation_vec, translation_vec, cam_matrix,
dist_coeffs)
reprojectdst = tuple(map(tuple, reprojectdst.reshape(8, 2)))
# calc euler angle
rotation_mat, _ = cv2.Rodrigues(rotation_vec)
pose_mat = cv2.hconcat((rotation_mat, translation_vec))
_, _, _, _, _, _, euler_angle = cv2.decomposeProjectionMatrix(pose_mat)
return reprojectdst, euler_angle
Example #4
| Source File: headpose.py From PINTO_model_zoo with MIT License | 5 votes |
|
def get_head_pose(shape,img):
h,w,_=img.shape
K = [w, 0.0, w//2,
0.0, w, h//2,
0.0, 0.0, 1.0]
# Assuming no lens distortion
D = [0, 0, 0.0, 0.0, 0]
cam_matrix = np.array(K).reshape(3, 3).astype(np.float32)
dist_coeffs = np.array(D).reshape(5, 1).astype(np.float32)
# image_pts = np.float32([shape[17], shape[21], shape[22], shape[26], shape[36],
# shape[39], shape[42], shape[45], shape[31], shape[35],
# shape[48], shape[54], shape[57], shape[8]])
image_pts = np.float32([shape[17], shape[21], shape[22], shape[26], shape[36],
shape[39], shape[42], shape[45], shape[31], shape[35]])
_, rotation_vec, translation_vec = cv2.solvePnP(object_pts, image_pts, cam_matrix, dist_coeffs)
reprojectdst, _ = cv2.projectPoints(reprojectsrc, rotation_vec, translation_vec, cam_matrix,
dist_coeffs)
reprojectdst = tuple(map(tuple, reprojectdst.reshape(8, 2)))
# calc euler angle
rotation_mat, _ = cv2.Rodrigues(rotation_vec)
pose_mat = cv2.hconcat((rotation_mat, translation_vec))
_, _, _, _, _, _, euler_angle = cv2.decomposeProjectionMatrix(pose_mat)
return reprojectdst, euler_angle
Example #5
| Source File: pose_estimation.py From Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV with MIT License | 4 votes |
|
def face_orientation(frame, landmarks):
size = frame.shape #(height, width, color_channel)
image_points = np.array([
(landmarks[4], landmarks[5]), # Nose tip
(landmarks[10], landmarks[11]), # Chin
(landmarks[0], landmarks[1]), # Left eye left corner
(landmarks[2], landmarks[3]), # Right eye right corne
(landmarks[6], landmarks[7]), # Left Mouth corner
(landmarks[8], landmarks[9]) # Right mouth corner
], dtype="double")
model_points = np.array([
(0.0, 0.0, 0.0), # Nose tip
(0.0, -330.0, -65.0), # Chin
(-165.0, 170.0, -135.0), # Left eye left corner
(165.0, 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
])
# Camera internals
center = (size[1]/2, size[0]/2)
focal_length = center[0] / np.tan(60/2 * np.pi / 180)
camera_matrix = np.array(
[[focal_length, 0, center[0]],
[0, focal_length, center[1]],
[0, 0, 1]], dtype = "double"
)
dist_coeffs = np.zeros((4,1)) # Assuming no lens distortion
(success, rotation_vector, translation_vector) = cv2.solvePnP(model_points, image_points, camera_matrix, dist_coeffs, flags=cv2.CV_ITERATIVE)
axis = np.float32([[500,0,0],
[0,500,0],
[0,0,500]])
imgpts, jac = cv2.projectPoints(axis, rotation_vector, translation_vector, camera_matrix, dist_coeffs)
modelpts, jac2 = cv2.projectPoints(model_points, rotation_vector, translation_vector, camera_matrix, dist_coeffs)
rvec_matrix = cv2.Rodrigues(rotation_vector)[0]
proj_matrix = np.hstack((rvec_matrix, translation_vector))
eulerAngles = cv2.decomposeProjectionMatrix(proj_matrix)[6]
pitch, yaw, roll = [math.radians(_) for _ in eulerAngles]
pitch = math.degrees(math.asin(math.sin(pitch)))
roll = -math.degrees(math.asin(math.sin(roll)))
yaw = math.degrees(math.asin(math.sin(yaw)))
return imgpts, modelpts, (str(int(roll)), str(int(pitch)), str(int(yaw))), (landmarks[4], landmarks[5])
