def transform_world_to_camera(poses_set, cams, ncams=4 ):
"""
Project 3d poses from world coordinate to camera coordinate system
Args
poses_set: dictionary with 3d poses
cams: dictionary with cameras
ncams: number of cameras per subject
Return:
t3d_camera: dictionary with 3d poses in camera coordinate
"""
t3d_camera = {}
for t3dk in sorted( poses_set.keys() ):
subj, action, seqname = t3dk
t3d_world = poses_set[ t3dk ]
for c in range( ncams ):
R, T, f, c, k, p, name = cams[ (subj, c+1) ]
camera_coord = cameras.world_to_camera_frame( np.reshape(t3d_world, [-1, 3]), R, T)
camera_coord = np.reshape( camera_coord, [-1, len(H36M_NAMES)*3] )
sname = seqname[:-3]+"."+name+".h5" # e.g.: Waiting 1.58860488.h5
t3d_camera[ (subj, action, sname) ] = camera_coord
return t3d_camera
def transform_world_to_camera(poses_set, cams, ncams=4):
"""
Project 3d poses from world coordinate to camera coordinate system
Args
poses_set: dictionary with 3d poses
cams: dictionary with cameras
ncams: number of cameras per subject
Return:
t3d_camera: dictionary with 3d poses in camera coordinate
"""
t3d_camera = {}
for t3dk in sorted(
poses_set.keys()): #获取已排序的列表副本，本例中即为键按照某种顺序排序后的列表：好像是字母顺序排列的
subj, action, seqname = t3dk
t3d_world = poses_set[t3dk]
#print("t3d_world的维度大小为",t3d_world.shape) #(n，96)
for c in range(ncams):
R, T, f, c, k, p, name = cams[(subj, c + 1)]
camera_coord = cameras.world_to_camera_frame(
np.reshape(t3d_world, [-1, 3]), R, T) #np.reshape()将其变为(m,3)
#print("原camera_coord的大小",camera_coord.shape)
camera_coord = np.reshape(
camera_coord,
[-1, len(H36M_NAMES) * 3]) #(n,96) 96是因为h3.6m一共有32个点，32*3=96
#print("reshape后camera_coord的大小",camera_coord.shape)
sname = seqname[:-3] + "." + name + ".h5" # e.g.: Waiting 1.58860488.h5 即在.和h5之间加上摄像机的id
#print("action和sname是",action,sname)
t3d_camera[(subj, action, sname)] = camera_coord
return t3d_camera
def transform_world_to_camera(poses_set, cams, ncams=4):
"""
Project 3d poses from world coordinate to camera coordinate system
Args:
poses_set: dictionary with 3d poses
cams: dictionary with cameras
ncams: number of cameras per subject
Return:
t3d_camera: dictionary with 3d poses in camera coordinate
"""
t3d_camera = {}
for t3dk in sorted(poses_set.keys()):
subj, a, seqname = t3dk
t3d_world = poses_set[t3dk]
#print("#### SHAPE OF t3d_world::",t3d_world.shape)
# FIXME this only works for real cameras
for c in range(ncams):
R, T, f, c, k, p, name = cams[(subj, c + 1)]
camera_coord = cameras.world_to_camera_frame(
np.reshape(t3d_world, [-1, 3]), R, T, f, c, k, p)
camera_coord = np.reshape(camera_coord, [-1, 96])
#print("#### SHAPE OF CAMCOORD::",camera_coord.shape)
sname = seqname[:-3] + "." + name + ".h5" #Waiting 1.58860488.h5
t3d_camera[(subj, a, sname)] = camera_coord
return t3d_camera
def transform_world_to_camera(poses_set, cams, ncams=4 ):
"""
Project 3d poses from world coordinate to camera coordinate system
Args
poses_set: dictionary with 3d poses
cams: dictionary with cameras
ncams: number of cameras per subject
Return:
t3d_camera: dictionary with 3d poses in camera coordinate
"""
t3d_camera = {}
for t3dk in sorted( poses_set.keys() ):
subj, action, seqname = t3dk
t3d_world = poses_set[ t3dk ]
for c in range( ncams ):
R, T, f, c, k, p, name = cams[ (subj, c+1) ]
camera_coord = cameras.world_to_camera_frame( np.reshape(t3d_world, [-1, 3]), R, T)
camera_coord = np.reshape( camera_coord, [-1, len(H36M_NAMES)*3] )
sname = seqname[:-3]+"."+name+".h5" # e.g.: Waiting 1.58860488.h5
t3d_camera[ (subj, action, sname) ] = camera_coord
return t3d_camera
def transform_world_to_camera(poses_set, cams, ncams=4, experimental=True):
"""
Project 3d poses from world coordinate to camera coordinate system
Args
poses_set: dictionary with 3d poses
cams: dictionary with cameras
ncams: number of cameras per subject
Return:
t3d_camera: dictionary with 3d poses in camera coordinate
"""
t3d_camera = {}
for t3dk in sorted(poses_set.keys()):
subj, action, seqname = t3dk
t3d_world = poses_set[t3dk]
for c in range(ncams):
R, T, f, c, k, p, name = cams[(subj, c + 1)]
if experimental:
# Checks if a matrix is a valid rotation matrix.
def isRotationMatrix(R):
Rt = np.transpose(R)
shouldBeIdentity = np.dot(Rt, R)
I = np.identity(3, dtype=R.dtype)
n = np.linalg.norm(I - shouldBeIdentity)
return n < 1e-6
# Calculates rotation matrix to euler angles
# The result is the same as MATLAB except the order
# of the euler angles ( x and z are swapped ).
def rotationMatrixToEulerAngles(R):
assert (isRotationMatrix(R))
sy = math.sqrt(R[0, 0] * R[0, 0] + R[1, 0] * R[1, 0])
singular = sy < 1e-6
if not singular:
x = math.atan2(R[2, 1], R[2, 2])
y = math.atan2(-R[2, 0], sy)
z = math.atan2(R[1, 0], R[0, 0])
else:
x = math.atan2(-R[1, 2], R[1, 1])
y = math.atan2(-R[2, 0], sy)
z = 0
return np.array([x, y, z])
# Calculates Rotation Matrix given euler angles.
def eulerAnglesToRotationMatrix(theta):
R_x = np.array(
[[1, 0, 0],
[0, math.cos(theta[0]), -math.sin(theta[0])],
[0, math.sin(theta[0]),
math.cos(theta[0])]])
R_y = np.array(
[[math.cos(theta[1]), 0,
math.sin(theta[1])], [0, 1, 0],
[-math.sin(theta[1]), 0,
math.cos(theta[1])]])
R_z = np.array(
[[math.cos(theta[2]), -math.sin(theta[2]), 0],
[math.sin(theta[2]),
math.cos(theta[2]), 0], [0, 0, 1]])
R = np.dot(R_z, np.dot(R_y, R_x))
return R
## x rotation
# R[0][0] = 1
# R[0][1] = 0
# R[0][2] = 0
# R[1][0] = 0
# R[2][0] = 0
## y rotation
# R[0][1] = 0
# R[1][0] = 0
# R[1][1] = 1
# R[1][2] = 0
# R[2][1] = 0
## z rotation
# R[0][2] = 0
# R[1][2] = 0
# R[2][0] = 0
# R[2][1] = 0
# R[2][2] = 1
## Do the theta thing with euler angles
theta = rotationMatrixToEulerAngles(R)
theta[0] = 0
theta[1] = 0
R = eulerAnglesToRotationMatrix(theta)
camera_coord = cameras.world_to_camera_frame(
np.reshape(t3d_world, [-1, 3]), R, T)
camera_coord = np.reshape(camera_coord, [-1, len(H36M_NAMES) * 3])
sname = seqname[:-3] + "." + name + ".h5" # e.g.: Waiting 1.58860488.h5
t3d_camera[(subj, action, sname)] = camera_coord
return t3d_camera
