/usr/lib/python2.7/dist-packages/image_geometry/cameramodels.py is in python-image-geometry 1.11.11+ds-1.
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import cv2
import sensor_msgs.msg
import math
import copy
import numpy
def mkmat(rows, cols, L):
mat = numpy.matrix(L, dtype='float64')
mat.resize((rows,cols))
return mat
class PinholeCameraModel:
"""
A pinhole camera is an idealized monocular camera.
"""
def __init__(self):
self.K = None
self.D = None
self.R = None
self.P = None
self.full_K = None
self.full_P = None
self.width = None
self.height = None
self.binning_x = None
self.binning_y = None
self.raw_roi = None
self.tf_frame = None
self.stamp = None
def fromCameraInfo(self, msg):
"""
:param msg: camera parameters
:type msg: sensor_msgs.msg.CameraInfo
Set the camera parameters from the :class:`sensor_msgs.msg.CameraInfo` message.
"""
self.K = mkmat(3, 3, msg.K)
if msg.D:
self.D = mkmat(len(msg.D), 1, msg.D)
else:
self.D = None
self.R = mkmat(3, 3, msg.R)
self.P = mkmat(3, 4, msg.P)
self.full_K = mkmat(3, 3, msg.K)
self.full_P = mkmat(3, 4, msg.P)
self.width = msg.width
self.height = msg.height
self.binning_x = max(1, msg.binning_x)
self.binning_y = max(1, msg.binning_y)
self.raw_roi = copy.copy(msg.roi)
# ROI all zeros is considered the same as full resolution
if (self.raw_roi.x_offset == 0 and self.raw_roi.y_offset == 0 and
self.raw_roi.width == 0 and self.raw_roi.height == 0):
self.raw_roi.width = self.width
self.raw_roi.height = self.height
self.tf_frame = msg.header.frame_id
self.stamp = msg.header.stamp
# Adjust K and P for binning and ROI
self.K[0,0] /= self.binning_x
self.K[1,1] /= self.binning_y
self.K[0,2] = (self.K[0,2] - self.raw_roi.x_offset) / self.binning_x
self.K[1,2] = (self.K[1,2] - self.raw_roi.y_offset) / self.binning_y
self.P[0,0] /= self.binning_x
self.P[1,1] /= self.binning_y
self.P[0,2] = (self.P[0,2] - self.raw_roi.x_offset) / self.binning_x
self.P[1,2] = (self.P[1,2] - self.raw_roi.y_offset) / self.binning_y
def rectifyImage(self, raw, rectified):
"""
:param raw: input image
:type raw: :class:`CvMat` or :class:`IplImage`
:param rectified: rectified output image
:type rectified: :class:`CvMat` or :class:`IplImage`
Applies the rectification specified by camera parameters :math:`K` and and :math:`D` to image `raw` and writes the resulting image `rectified`.
"""
self.mapx = numpy.ndarray(shape=(self.height, self.width, 1),
dtype='float32')
self.mapy = numpy.ndarray(shape=(self.height, self.width, 1),
dtype='float32')
cv2.initUndistortRectifyMap(self.K, self.D, self.R, self.P,
(self.width, self.height), cv2.CV_32FC1, self.mapx, self.mapy)
cv2.remap(raw, self.mapx, self.mapy, cv2.INTER_CUBIC, rectified)
def rectifyPoint(self, uv_raw):
"""
:param uv_raw: pixel coordinates
:type uv_raw: (u, v)
Applies the rectification specified by camera parameters
:math:`K` and and :math:`D` to point (u, v) and returns the
pixel coordinates of the rectified point.
"""
src = mkmat(1, 2, list(uv_raw))
src.resize((1,1,2))
dst = cv2.undistortPoints(src, self.K, self.D, R=self.R, P=self.P)
return dst[0,0]
def project3dToPixel(self, point):
"""
:param point: 3D point
:type point: (x, y, z)
Returns the rectified pixel coordinates (u, v) of the 3D point,
using the camera :math:`P` matrix.
This is the inverse of :meth:`projectPixelTo3dRay`.
"""
src = mkmat(4, 1, [point[0], point[1], point[2], 1.0])
dst = self.P * src
x = dst[0,0]
y = dst[1,0]
w = dst[2,0]
if w != 0:
return (x / w, y / w)
else:
return (float('nan'), float('nan'))
def projectPixelTo3dRay(self, uv):
"""
:param uv: rectified pixel coordinates
:type uv: (u, v)
Returns the unit vector which passes from the camera center to through rectified pixel (u, v),
using the camera :math:`P` matrix.
This is the inverse of :meth:`project3dToPixel`.
"""
x = (uv[0] - self.cx()) / self.fx()
y = (uv[1] - self.cy()) / self.fy()
norm = math.sqrt(x*x + y*y + 1)
x /= norm
y /= norm
z = 1.0 / norm
return (x, y, z)
def getDeltaU(self, deltaX, Z):
"""
:param deltaX: delta X, in cartesian space
:type deltaX: float
:param Z: Z, in cartesian space
:type Z: float
:rtype: float
Compute delta u, given Z and delta X in Cartesian space.
For given Z, this is the inverse of :meth:`getDeltaX`.
"""
fx = self.P[0, 0]
if Z == 0:
return float('inf')
else:
return fx * deltaX / Z
def getDeltaV(self, deltaY, Z):
"""
:param deltaY: delta Y, in cartesian space
:type deltaY: float
:param Z: Z, in cartesian space
:type Z: float
:rtype: float
Compute delta v, given Z and delta Y in Cartesian space.
For given Z, this is the inverse of :meth:`getDeltaY`.
"""
fy = self.P[1, 1]
if Z == 0:
return float('inf')
else:
return fy * deltaY / Z
def getDeltaX(self, deltaU, Z):
"""
:param deltaU: delta u in pixels
:type deltaU: float
:param Z: Z, in cartesian space
:type Z: float
:rtype: float
Compute delta X, given Z in cartesian space and delta u in pixels.
For given Z, this is the inverse of :meth:`getDeltaU`.
"""
fx = self.P[0, 0]
return Z * deltaU / fx
def getDeltaY(self, deltaV, Z):
"""
:param deltaV: delta v in pixels
:type deltaV: float
:param Z: Z, in cartesian space
:type Z: float
:rtype: float
Compute delta Y, given Z in cartesian space and delta v in pixels.
For given Z, this is the inverse of :meth:`getDeltaV`.
"""
fy = self.P[1, 1]
return Z * deltaV / fy
def intrinsicMatrix(self):
""" Returns :math:`K`, also called camera_matrix in cv docs """
return self.K
def distortionCoeffs(self):
""" Returns :math:`D` """
return self.D
def rotationMatrix(self):
""" Returns :math:`R` """
return self.R
def projectionMatrix(self):
""" Returns :math:`P` """
return self.P
def fullIntrinsicMatrix(self):
""" Return the original camera matrix for full resolution """
return self.full_K
def fullProjectionMatrix(self):
""" Return the projection matrix for full resolution """
return self.full_P
def cx(self):
""" Returns x center """
return self.P[0,2]
def cy(self):
""" Returns y center """
return self.P[1,2]
def fx(self):
""" Returns x focal length """
return self.P[0,0]
def fy(self):
""" Returns y focal length """
return self.P[1,1]
def Tx(self):
""" Return the x-translation term of the projection matrix """
return self.P[0,3]
def Ty(self):
""" Return the y-translation term of the projection matrix """
return self.P[1,3]
def tfFrame(self):
""" Returns the tf frame name - a string - of the camera.
This is the frame of the :class:`sensor_msgs.msg.CameraInfo` message.
"""
return self.tf_frame
class StereoCameraModel:
"""
An idealized stereo camera.
"""
def __init__(self):
self.left = PinholeCameraModel()
self.right = PinholeCameraModel()
def fromCameraInfo(self, left_msg, right_msg):
"""
:param left_msg: left camera parameters
:type left_msg: sensor_msgs.msg.CameraInfo
:param right_msg: right camera parameters
:type right_msg: sensor_msgs.msg.CameraInfo
Set the camera parameters from the :class:`sensor_msgs.msg.CameraInfo` messages.
"""
self.left.fromCameraInfo(left_msg)
self.right.fromCameraInfo(right_msg)
# [ Fx, 0, Cx, Fx*-Tx ]
# [ 0, Fy, Cy, 0 ]
# [ 0, 0, 1, 0 ]
fx = self.right.P[0, 0]
fy = self.right.P[1, 1]
cx = self.right.P[0, 2]
cy = self.right.P[1, 2]
tx = -self.right.P[0, 3] / fx
# Q is:
# [ 1, 0, 0, -Clx ]
# [ 0, 1, 0, -Cy ]
# [ 0, 0, 0, Fx ]
# [ 0, 0, 1 / Tx, (Crx-Clx)/Tx ]
self.Q = numpy.zeros((4, 4), dtype='float64')
self.Q[0, 0] = 1.0
self.Q[0, 3] = -cx
self.Q[1, 1] = 1.0
self.Q[1, 3] = -cy
self.Q[2, 3] = fx
self.Q[3, 2] = 1 / tx
def tfFrame(self):
"""
Returns the tf frame name - a string - of the 3d points. This is
the frame of the :class:`sensor_msgs.msg.CameraInfo` message. It
may be used as a source frame in :class:`tf.TransformListener`.
"""
return self.left.tfFrame()
def project3dToPixel(self, point):
"""
:param point: 3D point
:type point: (x, y, z)
Returns the rectified pixel coordinates (u, v) of the 3D point, for each camera, as ((u_left, v_left), (u_right, v_right))
using the cameras' :math:`P` matrices.
This is the inverse of :meth:`projectPixelTo3d`.
"""
l = self.left.project3dToPixel(point)
r = self.right.project3dToPixel(point)
return (l, r)
def projectPixelTo3d(self, left_uv, disparity):
"""
:param left_uv: rectified pixel coordinates
:type left_uv: (u, v)
:param disparity: disparity, in pixels
:type disparity: float
Returns the 3D point (x, y, z) for the given pixel position,
using the cameras' :math:`P` matrices.
This is the inverse of :meth:`project3dToPixel`.
Note that a disparity of zero implies that the 3D point is at infinity.
"""
src = mkmat(4, 1, [left_uv[0], left_uv[1], disparity, 1.0])
dst = self.Q * src
x = dst[0, 0]
y = dst[1, 0]
z = dst[2, 0]
w = dst[3, 0]
if w != 0:
return (x / w, y / w, z / w)
else:
return (0.0, 0.0, 0.0)
def getZ(self, disparity):
"""
:param disparity: disparity, in pixels
:type disparity: float
Returns the depth at which a point is observed with a given disparity.
This is the inverse of :meth:`getDisparity`.
Note that a disparity of zero implies Z is infinite.
"""
if disparity == 0:
return float('inf')
Tx = -self.right.P[0, 3]
return Tx / disparity
def getDisparity(self, Z):
"""
:param Z: Z (depth), in cartesian space
:type Z: float
Returns the disparity observed for a point at depth Z.
This is the inverse of :meth:`getZ`.
"""
if Z == 0:
return float('inf')
Tx = -self.right.P[0, 3]
return Tx / Z
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