Source code for sym.ops.atan_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

from __future__ import annotations

import math
import typing as T

import numpy

import sym


[docs] class CameraOps(object): """ Python CameraOps implementation for :py:class:`symforce.cam.atan_camera_cal.ATANCameraCal`. """
[docs] @staticmethod def focal_length(self: sym.ATANCameraCal) -> 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: sym.ATANCameraCal) -> 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: sym.ATANCameraCal, point: numpy.ndarray, epsilon: float ) -> 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: 25 # 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 (4) _tmp0 = max(epsilon, point[2, 0]) _tmp1 = _tmp0 ** (-2) _tmp2 = math.sqrt(_tmp1 * point[0, 0] ** 2 + _tmp1 * point[1, 0] ** 2 + epsilon) _tmp3 = math.atan(2 * _tmp2 * math.tan(0.5 * _self[4])) / (_self[4] * _tmp0 * _tmp2) # Output terms _pixel = numpy.zeros(2) _pixel[0] = _self[0] * _tmp3 * point[0, 0] + _self[2] _pixel[1] = _self[1] * _tmp3 * point[1, 0] + _self[3] _is_valid = max(0, (0.0 if point[2, 0] == 0 else math.copysign(1, point[2, 0]))) return _pixel, _is_valid
[docs] @staticmethod def pixel_from_camera_point_with_jacobians( self: sym.ATANCameraCal, point: numpy.ndarray, epsilon: float ) -> 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: 110 # 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 (45) _tmp0 = point[0, 0] ** 2 _tmp1 = max(epsilon, point[2, 0]) _tmp2 = _tmp1 ** (-2) _tmp3 = point[1, 0] ** 2 _tmp4 = _tmp0 * _tmp2 + _tmp2 * _tmp3 + epsilon _tmp5 = math.sqrt(_tmp4) _tmp6 = 1 / _tmp5 _tmp7 = 1 / _tmp1 _tmp8 = _tmp6 * _tmp7 _tmp9 = math.tan(0.5 * _self[4]) _tmp10 = 2 * _tmp9 _tmp11 = math.atan(_tmp10 * _tmp5) _tmp12 = 1 / _self[4] _tmp13 = _tmp11 * _tmp12 _tmp14 = _tmp13 * point[0, 0] _tmp15 = _tmp14 * _tmp8 _tmp16 = _tmp13 * _tmp8 _tmp17 = _tmp16 * point[1, 0] _tmp18 = _tmp9**2 _tmp19 = 1.0 * _tmp18 + 1.0 _tmp20 = _self[0] * point[0, 0] _tmp21 = _tmp12 / (4 * _tmp18 * _tmp4 + 1) _tmp22 = _tmp20 * _tmp21 _tmp23 = _tmp22 * _tmp7 _tmp24 = _tmp11 * _tmp8 / _self[4] ** 2 _tmp25 = _self[1] * point[1, 0] _tmp26 = _tmp25 * _tmp7 _tmp27 = _tmp21 * _tmp26 _tmp28 = _self[0] * _tmp0 _tmp29 = _tmp1 ** (-3) _tmp30 = 1 / _tmp4 _tmp31 = _tmp10 * _tmp29 * _tmp30 _tmp32 = _tmp21 * _tmp31 _tmp33 = _tmp4 ** (-3.0 / 2.0) _tmp34 = _tmp29 * _tmp33 _tmp35 = _tmp13 * _tmp34 _tmp36 = _tmp14 * _tmp34 _tmp37 = _self[1] * _tmp3 _tmp38 = ( 0.0 if -epsilon + point[2, 0] == 0 else math.copysign(1, -epsilon + point[2, 0]) ) + 1 _tmp39 = _tmp29 * _tmp38 _tmp40 = -_tmp0 * _tmp39 - _tmp3 * _tmp39 _tmp41 = _tmp30 * _tmp40 * _tmp9 _tmp42 = (1.0 / 2.0) * _tmp33 * _tmp40 _tmp43 = _self[0] * _tmp14 _tmp44 = (1.0 / 2.0) * _tmp2 * _tmp38 * _tmp6 # Output terms _pixel = numpy.zeros(2) _pixel[0] = _self[0] * _tmp15 + _self[2] _pixel[1] = _self[1] * _tmp17 + _self[3] _is_valid = max(0, (0.0 if point[2, 0] == 0 else math.copysign(1, point[2, 0]))) _pixel_D_cal = numpy.zeros((2, 5)) _pixel_D_cal[0, 0] = _tmp15 _pixel_D_cal[1, 0] = 0 _pixel_D_cal[0, 1] = 0 _pixel_D_cal[1, 1] = _tmp17 _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] = _tmp19 * _tmp23 - _tmp20 * _tmp24 _pixel_D_cal[1, 4] = _tmp19 * _tmp27 - _tmp24 * _tmp25 _pixel_D_point = numpy.zeros((2, 3)) _pixel_D_point[0, 0] = _self[0] * _tmp16 + _tmp28 * _tmp32 - _tmp28 * _tmp35 _pixel_D_point[1, 0] = _tmp25 * _tmp32 * point[0, 0] - _tmp25 * _tmp36 _pixel_D_point[0, 1] = -_self[0] * _tmp36 * point[1, 0] + _tmp22 * _tmp31 * point[1, 0] _pixel_D_point[1, 1] = _self[1] * _tmp16 + _tmp32 * _tmp37 - _tmp35 * _tmp37 _pixel_D_point[0, 2] = _tmp23 * _tmp41 - _tmp42 * _tmp43 * _tmp7 - _tmp43 * _tmp44 _pixel_D_point[1, 2] = ( -_tmp13 * _tmp25 * _tmp44 - _tmp13 * _tmp26 * _tmp42 + _tmp27 * _tmp41 ) return _pixel, _is_valid, _pixel_D_cal, _pixel_D_point
[docs] @staticmethod def camera_ray_from_pixel( self: sym.ATANCameraCal, pixel: numpy.ndarray, epsilon: float ) -> 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: 27 # 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 (5) _tmp0 = -_self[2] + pixel[0, 0] _tmp1 = -_self[3] + pixel[1, 0] _tmp2 = math.sqrt(epsilon + _tmp1**2 / _self[1] ** 2 + _tmp0**2 / _self[0] ** 2) _tmp3 = _self[4] * _tmp2 _tmp4 = (1.0 / 2.0) * math.tan(_tmp3) / (_tmp2 * math.tan(0.5 * _self[4])) # Output terms _camera_ray = numpy.zeros(3) _camera_ray[0] = _tmp0 * _tmp4 / _self[0] _camera_ray[1] = _tmp1 * _tmp4 / _self[1] _camera_ray[2] = 1 _is_valid = max( 0, ( 0.0 if -abs(_tmp3) + (1.0 / 2.0) * math.pi == 0 else math.copysign(1, -abs(_tmp3) + (1.0 / 2.0) * math.pi) ), ) return _camera_ray, _is_valid
[docs] @staticmethod def camera_ray_from_pixel_with_jacobians( self: sym.ATANCameraCal, pixel: numpy.ndarray, epsilon: float ) -> 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: 107 # 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 (49) _tmp0 = -_self[2] + pixel[0, 0] _tmp1 = _tmp0**2 _tmp2 = _self[0] ** (-2) _tmp3 = -_self[3] + pixel[1, 0] _tmp4 = _tmp3**2 _tmp5 = _self[1] ** (-2) _tmp6 = _tmp1 * _tmp2 + _tmp4 * _tmp5 + epsilon _tmp7 = math.sqrt(_tmp6) _tmp8 = _self[4] * _tmp7 _tmp9 = math.tan(_tmp8) _tmp10 = _tmp9 / _tmp7 _tmp11 = 1 / _self[0] _tmp12 = math.tan(0.5 * _self[4]) _tmp13 = (1.0 / 2.0) / _tmp12 _tmp14 = _tmp11 * _tmp13 _tmp15 = _tmp10 * _tmp14 _tmp16 = 1 / _self[1] _tmp17 = _tmp13 * _tmp16 _tmp18 = _tmp17 * _tmp3 _tmp19 = _tmp0**3 / _self[0] ** 4 _tmp20 = _tmp9**2 + 1 _tmp21 = _self[4] / _tmp6 _tmp22 = _tmp13 * _tmp20 * _tmp21 _tmp23 = _tmp9 / _tmp6 ** (3.0 / 2.0) _tmp24 = _tmp13 * _tmp23 _tmp25 = _tmp10 * _tmp13 _tmp26 = _tmp0 * _tmp2 _tmp27 = _tmp1 / _self[0] ** 3 _tmp28 = _tmp18 * _tmp20 _tmp29 = _tmp21 * _tmp28 _tmp30 = _tmp18 * _tmp23 _tmp31 = _tmp4 / _self[1] ** 3 _tmp32 = _tmp0 * _tmp14 _tmp33 = _tmp23 * _tmp32 _tmp34 = _tmp20 * _tmp32 _tmp35 = _tmp21 * _tmp34 _tmp36 = _tmp3**3 / _self[1] ** 4 _tmp37 = _tmp3 * _tmp5 _tmp38 = _tmp22 * _tmp27 _tmp39 = _tmp24 * _tmp27 _tmp40 = _tmp26 * _tmp30 _tmp41 = _tmp26 * _tmp29 _tmp42 = _tmp33 * _tmp37 _tmp43 = _tmp35 * _tmp37 _tmp44 = _tmp22 * _tmp31 _tmp45 = _tmp24 * _tmp31 _tmp46 = _tmp10 * _tmp17 _tmp47 = _tmp12**2 _tmp48 = 0.25 * _tmp10 * (_tmp47 + 1) / _tmp47 # Output terms _camera_ray = numpy.zeros(3) _camera_ray[0] = _tmp0 * _tmp15 _camera_ray[1] = _tmp10 * _tmp18 _camera_ray[2] = 1 _is_valid = max( 0, ( 0.0 if -abs(_tmp8) + (1.0 / 2.0) * math.pi == 0 else math.copysign(1, -abs(_tmp8) + (1.0 / 2.0) * math.pi) ), ) _point_D_cal = numpy.zeros((3, 5)) _point_D_cal[0, 0] = -_tmp19 * _tmp22 + _tmp19 * _tmp24 - _tmp25 * _tmp26 _point_D_cal[1, 0] = -_tmp27 * _tmp29 + _tmp27 * _tmp30 _point_D_cal[2, 0] = 0 _point_D_cal[0, 1] = _tmp31 * _tmp33 - _tmp31 * _tmp35 _point_D_cal[1, 1] = -_tmp22 * _tmp36 + _tmp24 * _tmp36 - _tmp25 * _tmp37 _point_D_cal[2, 1] = 0 _point_D_cal[0, 2] = -_tmp15 - _tmp38 + _tmp39 _point_D_cal[1, 2] = _tmp40 - _tmp41 _point_D_cal[2, 2] = 0 _point_D_cal[0, 3] = _tmp42 - _tmp43 _point_D_cal[1, 3] = -_tmp44 + _tmp45 - _tmp46 _point_D_cal[2, 3] = 0 _point_D_cal[0, 4] = -_tmp0 * _tmp11 * _tmp48 + _tmp34 _point_D_cal[1, 4] = -_tmp16 * _tmp3 * _tmp48 + _tmp28 _point_D_cal[2, 4] = 0 _point_D_pixel = numpy.zeros((3, 2)) _point_D_pixel[0, 0] = _tmp15 + _tmp38 - _tmp39 _point_D_pixel[1, 0] = -_tmp40 + _tmp41 _point_D_pixel[2, 0] = 0 _point_D_pixel[0, 1] = -_tmp42 + _tmp43 _point_D_pixel[1, 1] = _tmp44 - _tmp45 + _tmp46 _point_D_pixel[2, 1] = 0 return _camera_ray, _is_valid, _point_D_cal, _point_D_pixel