Source code for sym.ops.double_sphere_camera_cal.camera_ops

# -----------------------------------------------------------------------------
# This file was autogenerated by symforce from template:
#     cam_package/ops/CLASS/camera_ops.py.jinja
# Do NOT modify by hand.
# -----------------------------------------------------------------------------

# ruff: noqa: PLR0915, F401, PLW0211, PLR0914

import math
import typing as T

import numpy

import sym


[docs]class CameraOps(object): """ Python CameraOps implementation for :py:class:`symforce.cam.double_sphere_camera_cal.DoubleSphereCameraCal`. """
[docs] @staticmethod def focal_length(self): # type: (sym.DoubleSphereCameraCal) -> numpy.ndarray """ Return the focal length. """ # Total ops: 0 # Input arrays _self = self.data # Intermediate terms (0) # Output terms _focal_length = numpy.zeros(2) _focal_length[0] = _self[0] _focal_length[1] = _self[1] return _focal_length
[docs] @staticmethod def principal_point(self): # type: (sym.DoubleSphereCameraCal) -> numpy.ndarray """ Return the principal point. """ # Total ops: 0 # Input arrays _self = self.data # Intermediate terms (0) # Output terms _principal_point = numpy.zeros(2) _principal_point[0] = _self[2] _principal_point[1] = _self[3] return _principal_point
[docs] @staticmethod def pixel_from_camera_point(self, point, epsilon): # type: (sym.DoubleSphereCameraCal, numpy.ndarray, float) -> T.Tuple[numpy.ndarray, float] """ Project a 3D point in the camera frame into 2D pixel coordinates. Returns: pixel: (x, y) coordinate in pixels if valid is_valid: 1 if the operation is within bounds else 0 """ # Total ops: 73 # Input arrays _self = self.data if point.shape == (3,): point = point.reshape((3, 1)) elif point.shape != (3, 1): raise IndexError( "point is expected to have shape (3, 1) or (3,); instead had shape {}".format( point.shape ) ) # Intermediate terms (13) _tmp0 = epsilon**2 + point[0, 0] ** 2 + point[1, 0] ** 2 _tmp1 = math.sqrt(_tmp0 + point[2, 0] ** 2) _tmp2 = _self[4] * _tmp1 + point[2, 0] _tmp3 = min(0, (0.0 if _self[5] - 0.5 == 0 else math.copysign(1, _self[5] - 0.5))) _tmp4 = 2 * _tmp3 _tmp5 = _self[5] - epsilon * (_tmp4 + 1) _tmp6 = -_tmp5 _tmp7 = 1 / max(epsilon, _tmp2 * (_tmp6 + 1) + _tmp5 * math.sqrt(_tmp0 + _tmp2**2)) _tmp8 = _tmp3 + _tmp5 _tmp9 = (1.0 / 2.0) * _tmp4 + _tmp6 + 1 _tmp10 = _self[4] ** 2 _tmp11 = _tmp9**2 / _tmp8**2 _tmp12 = _tmp10 * _tmp11 - _tmp10 + 1 # Output terms _pixel = numpy.zeros(2) _pixel[0] = _self[0] * _tmp7 * point[0, 0] + _self[2] _pixel[1] = _self[1] * _tmp7 * point[1, 0] + _self[3] _is_valid = max( 0, min( max( -(0.0 if _self[4] - 1 == 0 else math.copysign(1, _self[4] - 1)), 1 - max( 0, -( 0.0 if _self[4] * point[2, 0] + _tmp1 == 0 else math.copysign(1, _self[4] * point[2, 0] + _tmp1) ), ), ), max( -(0.0 if _tmp12 == 0 else math.copysign(1, _tmp12)), 1 - max( 0, -( 0.0 if -_tmp1 * ( _self[4] * _tmp11 - _self[4] - _tmp9 * math.sqrt(max(_tmp12, math.sqrt(epsilon))) / _tmp8 ) + point[2, 0] == 0 else math.copysign( 1, -_tmp1 * ( _self[4] * _tmp11 - _self[4] - _tmp9 * math.sqrt(max(_tmp12, math.sqrt(epsilon))) / _tmp8 ) + point[2, 0], ) ), ), ), ), ) return _pixel, _is_valid
[docs] @staticmethod def pixel_from_camera_point_with_jacobians(self, point, epsilon): # type: (sym.DoubleSphereCameraCal, numpy.ndarray, float) -> T.Tuple[numpy.ndarray, float, numpy.ndarray, numpy.ndarray] """ Project a 3D point in the camera frame into 2D pixel coordinates. Returns: pixel: (x, y) coordinate in pixels if valid is_valid: 1 if the operation is within bounds else 0 pixel_D_cal: Derivative of pixel with respect to intrinsic calibration parameters pixel_D_point: Derivative of pixel with respect to point """ # Total ops: 134 # Input arrays _self = self.data if point.shape == (3,): point = point.reshape((3, 1)) elif point.shape != (3, 1): raise IndexError( "point is expected to have shape (3, 1) or (3,); instead had shape {}".format( point.shape ) ) # Intermediate terms (40) _tmp0 = epsilon**2 + point[0, 0] ** 2 + point[1, 0] ** 2 _tmp1 = math.sqrt(_tmp0 + point[2, 0] ** 2) _tmp2 = _self[4] * _tmp1 + point[2, 0] _tmp3 = min(0, (0.0 if _self[5] - 0.5 == 0 else math.copysign(1, _self[5] - 0.5))) _tmp4 = 2 * _tmp3 _tmp5 = _self[5] - epsilon * (_tmp4 + 1) _tmp6 = -_tmp5 _tmp7 = _tmp6 + 1 _tmp8 = math.sqrt(_tmp0 + _tmp2**2) _tmp9 = _tmp2 * _tmp7 + _tmp5 * _tmp8 _tmp10 = max(_tmp9, epsilon) _tmp11 = 1 / _tmp10 _tmp12 = _self[0] * _tmp11 _tmp13 = _self[1] * _tmp11 _tmp14 = _self[4] * point[2, 0] _tmp15 = _tmp3 + _tmp5 _tmp16 = (1.0 / 2.0) * _tmp4 + _tmp6 + 1 _tmp17 = _self[4] ** 2 _tmp18 = _tmp16**2 / _tmp15**2 _tmp19 = _tmp17 * _tmp18 - _tmp17 + 1 _tmp20 = _tmp5 / _tmp8 _tmp21 = _tmp2 * _tmp20 _tmp22 = _tmp1 * _tmp21 + _tmp1 * _tmp7 _tmp23 = ( (1.0 / 2.0) * ((0.0 if _tmp9 - epsilon == 0 else math.copysign(1, _tmp9 - epsilon)) + 1) / _tmp10**2 ) _tmp24 = _self[0] * point[0, 0] _tmp25 = _tmp23 * _tmp24 _tmp26 = _self[1] * point[1, 0] _tmp27 = _tmp23 * _tmp26 _tmp28 = -_tmp2 + _tmp8 _tmp29 = 1 / _tmp1 _tmp30 = _self[4] * _tmp29 _tmp31 = _tmp30 * _tmp7 _tmp32 = 2 * point[0, 0] _tmp33 = _tmp2 * _tmp30 _tmp34 = (1.0 / 2.0) * _tmp20 _tmp35 = _tmp23 * (_tmp31 * point[0, 0] + _tmp34 * (_tmp32 * _tmp33 + _tmp32)) _tmp36 = 2 * point[1, 0] _tmp37 = _tmp31 * point[1, 0] + _tmp34 * (_tmp33 * _tmp36 + _tmp36) _tmp38 = _tmp14 * _tmp29 + 1 _tmp39 = _tmp21 * _tmp38 + _tmp38 * _tmp7 # Output terms _pixel = numpy.zeros(2) _pixel[0] = _self[2] + _tmp12 * point[0, 0] _pixel[1] = _self[3] + _tmp13 * point[1, 0] _is_valid = max( 0, min( max( -(0.0 if _self[4] - 1 == 0 else math.copysign(1, _self[4] - 1)), 1 - max(0, -(0.0 if _tmp1 + _tmp14 == 0 else math.copysign(1, _tmp1 + _tmp14))), ), max( -(0.0 if _tmp19 == 0 else math.copysign(1, _tmp19)), 1 - max( 0, -( 0.0 if -_tmp1 * ( _self[4] * _tmp18 - _self[4] - _tmp16 * math.sqrt(max(_tmp19, math.sqrt(epsilon))) / _tmp15 ) + point[2, 0] == 0 else math.copysign( 1, -_tmp1 * ( _self[4] * _tmp18 - _self[4] - _tmp16 * math.sqrt(max(_tmp19, math.sqrt(epsilon))) / _tmp15 ) + point[2, 0], ) ), ), ), ), ) _pixel_D_cal = numpy.zeros((2, 6)) _pixel_D_cal[0, 0] = _tmp11 * point[0, 0] _pixel_D_cal[1, 0] = 0 _pixel_D_cal[0, 1] = 0 _pixel_D_cal[1, 1] = _tmp11 * point[1, 0] _pixel_D_cal[0, 2] = 1 _pixel_D_cal[1, 2] = 0 _pixel_D_cal[0, 3] = 0 _pixel_D_cal[1, 3] = 1 _pixel_D_cal[0, 4] = -_tmp22 * _tmp25 _pixel_D_cal[1, 4] = -_tmp22 * _tmp27 _pixel_D_cal[0, 5] = -_tmp25 * _tmp28 _pixel_D_cal[1, 5] = -_tmp27 * _tmp28 _pixel_D_point = numpy.zeros((2, 3)) _pixel_D_point[0, 0] = _tmp12 - _tmp24 * _tmp35 _pixel_D_point[1, 0] = -_tmp26 * _tmp35 _pixel_D_point[0, 1] = -_tmp25 * _tmp37 _pixel_D_point[1, 1] = _tmp13 - _tmp27 * _tmp37 _pixel_D_point[0, 2] = -_tmp25 * _tmp39 _pixel_D_point[1, 2] = -_tmp27 * _tmp39 return _pixel, _is_valid, _pixel_D_cal, _pixel_D_point
[docs] @staticmethod def camera_ray_from_pixel(self, pixel, epsilon): # type: (sym.DoubleSphereCameraCal, numpy.ndarray, float) -> T.Tuple[numpy.ndarray, float] """ Backproject a 2D pixel coordinate into a 3D ray in the camera frame. Returns: camera_ray: The ray in the camera frame (NOT normalized) is_valid: 1 if the operation is within bounds else 0 """ # Total ops: 62 # Input arrays _self = self.data if pixel.shape == (2,): pixel = pixel.reshape((2, 1)) elif pixel.shape != (2, 1): raise IndexError( "pixel is expected to have shape (2, 1) or (2,); instead had shape {}".format( pixel.shape ) ) # Intermediate terms (12) _tmp0 = -_self[2] + pixel[0, 0] _tmp1 = -_self[3] + pixel[1, 0] _tmp2 = _tmp1**2 / _self[1] ** 2 + _tmp0**2 / _self[0] ** 2 _tmp3 = -_tmp2 * (2 * _self[5] - 1) + 1 _tmp4 = _self[5] * math.sqrt(max(_tmp3, epsilon)) - _self[5] + 1 _tmp5 = _tmp4 + epsilon * (2 * min(0, (0.0 if _tmp4 == 0 else math.copysign(1, _tmp4))) + 1) _tmp6 = -(_self[5] ** 2) * _tmp2 + 1 _tmp7 = _tmp6 / _tmp5 _tmp8 = _tmp6**2 / _tmp5**2 _tmp9 = _tmp2 * (1 - _self[4] ** 2) + _tmp8 _tmp10 = _tmp2 + _tmp8 _tmp11 = (_self[4] * _tmp7 + math.sqrt(max(_tmp9, epsilon))) / ( _tmp10 + epsilon * (2 * min(0, (0.0 if _tmp10 == 0 else math.copysign(1, _tmp10))) + 1) ) # Output terms _camera_ray = numpy.zeros(3) _camera_ray[0] = _tmp0 * _tmp11 / _self[0] _camera_ray[1] = _tmp1 * _tmp11 / _self[1] _camera_ray[2] = -_self[4] + _tmp11 * _tmp7 _is_valid = min( 1 - max(0, -(0.0 if _tmp3 == 0 else math.copysign(1, _tmp3))), 1 - max(0, -(0.0 if _tmp9 == 0 else math.copysign(1, _tmp9))), ) return _camera_ray, _is_valid
[docs] @staticmethod def camera_ray_from_pixel_with_jacobians(self, pixel, epsilon): # type: (sym.DoubleSphereCameraCal, numpy.ndarray, float) -> T.Tuple[numpy.ndarray, float, numpy.ndarray, numpy.ndarray] """ Backproject a 2D pixel coordinate into a 3D ray in the camera frame. Returns: camera_ray: The ray in the camera frame (NOT normalized) is_valid: 1 if the operation is within bounds else 0 point_D_cal: Derivative of point with respect to intrinsic calibration parameters point_D_pixel: Derivation of point with respect to pixel """ # Total ops: 298 # Input arrays _self = self.data if pixel.shape == (2,): pixel = pixel.reshape((2, 1)) elif pixel.shape != (2, 1): raise IndexError( "pixel is expected to have shape (2, 1) or (2,); instead had shape {}".format( pixel.shape ) ) # Intermediate terms (117) _tmp0 = -_self[2] + pixel[0, 0] _tmp1 = 1 / _self[0] _tmp2 = _tmp0**2 _tmp3 = _self[0] ** (-2) _tmp4 = -_self[3] + pixel[1, 0] _tmp5 = _tmp4**2 _tmp6 = _self[1] ** (-2) _tmp7 = _tmp2 * _tmp3 + _tmp5 * _tmp6 _tmp8 = 2 * _self[5] _tmp9 = _tmp8 - 1 _tmp10 = -_tmp7 * _tmp9 + 1 _tmp11 = math.sqrt(max(_tmp10, epsilon)) _tmp12 = _self[5] * _tmp11 - _self[5] + 1 _tmp13 = _tmp12 + epsilon * ( 2 * min(0, (0.0 if _tmp12 == 0 else math.copysign(1, _tmp12))) + 1 ) _tmp14 = 1 / _tmp13 _tmp15 = _self[5] ** 2 _tmp16 = -_tmp15 * _tmp7 + 1 _tmp17 = _tmp14 * _tmp16 _tmp18 = _tmp13 ** (-2) _tmp19 = _tmp16**2 _tmp20 = _tmp18 * _tmp19 _tmp21 = 1 - _self[4] ** 2 _tmp22 = _tmp20 + _tmp21 * _tmp7 _tmp23 = math.sqrt(max(_tmp22, epsilon)) _tmp24 = _self[4] * _tmp17 + _tmp23 _tmp25 = _tmp20 + _tmp7 _tmp26 = _tmp25 + epsilon * ( 2 * min(0, (0.0 if _tmp25 == 0 else math.copysign(1, _tmp25))) + 1 ) _tmp27 = 1 / _tmp26 _tmp28 = _tmp24 * _tmp27 _tmp29 = _tmp1 * _tmp28 _tmp30 = 1 / _self[1] _tmp31 = _tmp28 * _tmp30 _tmp32 = _tmp2 / _self[0] ** 3 _tmp33 = 2 * _tmp32 _tmp34 = _self[5] * _tmp9 _tmp35 = _tmp19 / _tmp13**3 _tmp36 = -epsilon _tmp37 = ((0.0 if _tmp10 + _tmp36 == 0 else math.copysign(1, _tmp10 + _tmp36)) + 1) / _tmp11 _tmp38 = _tmp35 * _tmp37 _tmp39 = _tmp34 * _tmp38 _tmp40 = _tmp16 * _tmp18 _tmp41 = 4 * _tmp40 _tmp42 = _tmp15 * _tmp41 _tmp43 = -_tmp32 * _tmp39 + _tmp32 * _tmp42 _tmp44 = ((0.0 if _tmp22 + _tmp36 == 0 else math.copysign(1, _tmp22 + _tmp36)) + 1) / _tmp23 _tmp45 = (1.0 / 4.0) * _tmp44 _tmp46 = (1.0 / 2.0) * _tmp37 _tmp47 = _tmp40 * _tmp46 _tmp48 = _self[4] * _tmp47 _tmp49 = _tmp34 * _tmp48 _tmp50 = _tmp14 * _tmp15 _tmp51 = _self[4] * _tmp50 _tmp52 = _tmp27 * ( -_tmp32 * _tmp49 + _tmp33 * _tmp51 + _tmp45 * (-_tmp21 * _tmp33 + _tmp43) ) _tmp53 = _tmp0 * _tmp1 _tmp54 = -_tmp33 + _tmp43 _tmp55 = _tmp24 / _tmp26**2 _tmp56 = _tmp53 * _tmp55 _tmp57 = _tmp0 * _tmp3 _tmp58 = _tmp28 * _tmp57 _tmp59 = _tmp30 * _tmp4 _tmp60 = _tmp55 * _tmp59 _tmp61 = _tmp28 * _tmp50 _tmp62 = _tmp17 * _tmp55 _tmp63 = _tmp34 * _tmp47 _tmp64 = _tmp5 / _self[1] ** 3 _tmp65 = 2 * _tmp64 _tmp66 = _tmp34 * _tmp64 _tmp67 = -_tmp38 * _tmp66 + _tmp42 * _tmp64 _tmp68 = _tmp45 * (-_tmp21 * _tmp65 + _tmp67) - _tmp48 * _tmp66 + _tmp51 * _tmp65 _tmp69 = _tmp27 * _tmp68 _tmp70 = -_tmp65 + _tmp67 _tmp71 = _tmp4 * _tmp6 _tmp72 = _tmp28 * _tmp71 _tmp73 = _tmp17 * _tmp27 _tmp74 = 2 * _tmp57 _tmp75 = _tmp21 * _tmp74 _tmp76 = _tmp39 * _tmp57 _tmp77 = _tmp42 * _tmp57 _tmp78 = -_tmp76 + _tmp77 _tmp79 = _tmp49 * _tmp57 _tmp80 = _tmp51 * _tmp74 _tmp81 = _tmp45 * (-_tmp75 + _tmp78) - _tmp79 + _tmp80 _tmp82 = _tmp27 * _tmp81 _tmp83 = -_tmp74 + _tmp78 _tmp84 = _tmp61 * _tmp74 _tmp85 = _tmp58 * _tmp63 _tmp86 = 2 * _tmp71 _tmp87 = _tmp39 * _tmp71 _tmp88 = _tmp42 * _tmp71 _tmp89 = -_tmp87 + _tmp88 _tmp90 = -_tmp86 + _tmp89 _tmp91 = _tmp21 * _tmp86 _tmp92 = _tmp49 * _tmp71 _tmp93 = _tmp51 * _tmp86 _tmp94 = _tmp45 * (_tmp89 - _tmp91) - _tmp92 + _tmp93 _tmp95 = _tmp27 * _tmp94 _tmp96 = _tmp61 * _tmp86 _tmp97 = _tmp63 * _tmp72 _tmp98 = _self[4] * _tmp7 _tmp99 = _tmp17 - 1.0 / 2.0 * _tmp44 * _tmp98 _tmp100 = _tmp27 * _tmp99 _tmp101 = _self[5] * _tmp7 _tmp102 = -_tmp101 * _tmp46 + _tmp11 - 1 _tmp103 = -_tmp101 * _tmp41 - 2 * _tmp102 * _tmp35 _tmp104 = _tmp103 * _tmp55 _tmp105 = _tmp14 * _tmp8 _tmp106 = _tmp102 * _tmp40 _tmp107 = -_self[4] * _tmp106 + _tmp103 * _tmp45 - _tmp105 * _tmp98 _tmp108 = _tmp107 * _tmp27 _tmp109 = _tmp76 - _tmp77 _tmp110 = _tmp45 * (_tmp109 + _tmp75) + _tmp79 - _tmp80 _tmp111 = _tmp110 * _tmp27 _tmp112 = _tmp109 + _tmp74 _tmp113 = _tmp87 - _tmp88 _tmp114 = _tmp113 + _tmp86 _tmp115 = _tmp45 * (_tmp113 + _tmp91) + _tmp92 - _tmp93 _tmp116 = _tmp115 * _tmp27 # Output terms _camera_ray = numpy.zeros(3) _camera_ray[0] = _tmp0 * _tmp29 _camera_ray[1] = _tmp31 * _tmp4 _camera_ray[2] = -_self[4] + _tmp17 * _tmp28 _is_valid = min( 1 - max(0, -(0.0 if _tmp10 == 0 else math.copysign(1, _tmp10))), 1 - max(0, -(0.0 if _tmp22 == 0 else math.copysign(1, _tmp22))), ) _point_D_cal = numpy.zeros((3, 6)) _point_D_cal[0, 0] = _tmp52 * _tmp53 - _tmp54 * _tmp56 - _tmp58 _point_D_cal[1, 0] = _tmp52 * _tmp59 - _tmp54 * _tmp60 _point_D_cal[2, 0] = ( _tmp17 * _tmp52 - _tmp28 * _tmp32 * _tmp63 + _tmp33 * _tmp61 - _tmp54 * _tmp62 ) _point_D_cal[0, 1] = _tmp53 * _tmp69 - _tmp56 * _tmp70 _point_D_cal[1, 1] = _tmp59 * _tmp69 - _tmp60 * _tmp70 - _tmp72 _point_D_cal[2, 1] = ( -_tmp28 * _tmp47 * _tmp66 + _tmp61 * _tmp65 - _tmp62 * _tmp70 + _tmp68 * _tmp73 ) _point_D_cal[0, 2] = -_tmp29 + _tmp53 * _tmp82 - _tmp56 * _tmp83 _point_D_cal[1, 2] = _tmp59 * _tmp82 - _tmp60 * _tmp83 _point_D_cal[2, 2] = -_tmp62 * _tmp83 + _tmp73 * _tmp81 + _tmp84 - _tmp85 _point_D_cal[0, 3] = _tmp53 * _tmp95 - _tmp56 * _tmp90 _point_D_cal[1, 3] = -_tmp31 + _tmp59 * _tmp95 - _tmp60 * _tmp90 _point_D_cal[2, 3] = -_tmp62 * _tmp90 + _tmp73 * _tmp94 + _tmp96 - _tmp97 _point_D_cal[0, 4] = _tmp100 * _tmp53 _point_D_cal[1, 4] = _tmp100 * _tmp59 _point_D_cal[2, 4] = _tmp73 * _tmp99 - 1 _point_D_cal[0, 5] = -_tmp104 * _tmp53 + _tmp108 * _tmp53 _point_D_cal[1, 5] = -_tmp103 * _tmp60 + _tmp108 * _tmp59 _point_D_cal[2, 5] = ( -_tmp104 * _tmp17 - _tmp105 * _tmp28 * _tmp7 - _tmp106 * _tmp28 + _tmp107 * _tmp73 ) _point_D_pixel = numpy.zeros((3, 2)) _point_D_pixel[0, 0] = _tmp111 * _tmp53 - _tmp112 * _tmp56 + _tmp29 _point_D_pixel[1, 0] = _tmp111 * _tmp59 - _tmp112 * _tmp60 _point_D_pixel[2, 0] = _tmp110 * _tmp73 - _tmp112 * _tmp62 - _tmp84 + _tmp85 _point_D_pixel[0, 1] = -_tmp114 * _tmp56 + _tmp116 * _tmp53 _point_D_pixel[1, 1] = -_tmp114 * _tmp60 + _tmp116 * _tmp59 + _tmp31 _point_D_pixel[2, 1] = -_tmp114 * _tmp62 + _tmp115 * _tmp73 - _tmp96 + _tmp97 return _camera_ray, _is_valid, _point_D_cal, _point_D_pixel