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stereo.c
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// Copyright (c) 2017-2023 California Institute of Technology ("Caltech"). U.S.
// Government sponsorship acknowledged. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
// Apparently I need this in MSVC to get constants
#define _USE_MATH_DEFINES
#include <math.h>
#include <float.h>
#include "mrcal.h"
#include "minimath/minimath.h"
#include "util.h"
// The equivalent function in Python is _rectified_resolution_python() in
// stereo.py
//
// Documentation is in the docstring of mrcal.rectified_resolution()
bool mrcal_rectified_resolution( // output and input
// > 0: use given value
// < 0: autodetect and scale
double* pixels_per_deg_az,
double* pixels_per_deg_el,
// input
const mrcal_lensmodel_t* lensmodel,
const double* intrinsics,
const mrcal_point2_t* azel_fov_deg,
const mrcal_point2_t* azel0_deg,
const double* R_cam0_rect0,
const mrcal_lensmodel_type_t rectification_model_type)
{
// Get the rectified image resolution
if( *pixels_per_deg_az < 0 ||
*pixels_per_deg_el < 0)
{
const mrcal_point2_t azel0 = {.x = azel0_deg->x * M_PI/180.,
.y = azel0_deg->y * M_PI/180. };
// I need to compute the resolution of the rectified images. I try to
// match the resolution of the cameras. I just look at camera0. If your
// two cameras are different, pass in the pixels_per_deg yourself
//
// I look at the center of the stereo field of view. There I have q =
// project(v) where v is a unit projection vector. I compute dq/dth where
// th is an angular perturbation applied to v.
double v[3];
double dv_dazel[3*2];
if(rectification_model_type == MRCAL_LENSMODEL_LATLON)
mrcal_unproject_latlon((mrcal_point3_t*)v, (mrcal_point2_t*)dv_dazel,
&azel0,
1,
(double[]){1.,1.,0.,0.});
else if(rectification_model_type == MRCAL_LENSMODEL_LONLAT)
mrcal_unproject_lonlat((mrcal_point3_t*)v, (mrcal_point2_t*)dv_dazel,
&azel0,
1,
(double[]){1.,1.,0.,0.});
else if(rectification_model_type == MRCAL_LENSMODEL_PINHOLE)
{
mrcal_point2_t q0_normalized = {.x = tan(azel0.x),
.y = tan(azel0.y)};
mrcal_unproject_pinhole((mrcal_point3_t*)v, (mrcal_point2_t*)dv_dazel,
&q0_normalized,
1,
(double[]){1.,1.,0.,0.});
// dq/dth = dtanth/dth = 1/cos^2(th)
double cos_az0 = cos(azel0.x);
double cos_el0 = cos(azel0.y);
for(int i=0; i<3; i++)
{
dv_dazel[2*i + 0] /= cos_az0*cos_az0;
dv_dazel[2*i + 1] /= cos_el0*cos_el0;
}
}
else
{
MSG("Unsupported rectification model");
return false;
}
double v0[3];
mrcal_rotate_point_R(v0, NULL,NULL,
R_cam0_rect0,
v);
// dv0_dazel = nps.matmult(R_cam0_rect0, dv_dazel)
double dv0_daz[3] = {};
double dv0_del[3] = {};
for(int j=0; j<3; j++)
for(int k=0; k<3; k++)
{
dv0_daz[j] += R_cam0_rect0[j*3+k]*dv_dazel[2*k + 0];
dv0_del[j] += R_cam0_rect0[j*3+k]*dv_dazel[2*k + 1];
}
mrcal_point2_t qdummy;
mrcal_point3_t dq_dv0[2];
// _,dq_dv0,_ = mrcal.project(v0, *model.intrinsics(), get_gradients = True)
mrcal_project(&qdummy,dq_dv0,NULL,
(const mrcal_point3_t*)v0, 1, lensmodel, intrinsics);
// More complex method that's probably not any better
//
// if False:
// // I rotate my v to a coordinate system where u = rotate(v) is [0,0,1].
// // Then u = [a,b,0] are all orthogonal to v. So du/dth = [cos, sin, 0].
// // I then have dq/dth = dq/dv dv/du [cos, sin, 0]t
// // ---> dq/dth = dq/dv dv/du[:,:2] [cos, sin]t = M [cos,sin]t
// //
// // norm2(dq/dth) = [cos,sin] MtM [cos,sin]t is then an ellipse with the
// // eigenvalues of MtM giving me the best and worst sensitivities. I can
// // use mrcal.worst_direction_stdev() to find the densest direction. But I
// // actually know the directions I care about, so I evaluate them
// // independently for the az and el directions
// Ruv = mrcal.R_aligned_to_vector(v0);
// M = nps.matmult(dq_dv0, nps.transpose(Ruv[:2,:]))
// // I pick the densest direction: highest |dq/dth|
// pixels_per_rad = mrcal.worst_direction_stdev( nps.matmult( nps.transpose(M),M) );
// dq_dazel = nps.matmult(dq_dv0, dv0_dazel)
double dq_daz[2] =
{ dq_dv0[0].x*dv0_daz[0] + dq_dv0[0].y*dv0_daz[1] + dq_dv0[0].z*dv0_daz[2],
dq_dv0[1].x*dv0_daz[0] + dq_dv0[1].y*dv0_daz[1] + dq_dv0[1].z*dv0_daz[2] };
double dq_del[2] =
{ dq_dv0[0].x*dv0_del[0] + dq_dv0[0].y*dv0_del[1] + dq_dv0[0].z*dv0_del[2],
dq_dv0[1].x*dv0_del[0] + dq_dv0[1].y*dv0_del[1] + dq_dv0[1].z*dv0_del[2] };
if(*pixels_per_deg_az < 0)
{
double dq_daz_norm2 = 0.;
for(int i=0; i<2; i++) dq_daz_norm2 += dq_daz[i]*dq_daz[i];
double pixels_per_deg_az_have = sqrt(dq_daz_norm2)*M_PI/180.;
*pixels_per_deg_az *= -pixels_per_deg_az_have;
}
if(*pixels_per_deg_el < 0)
{
double dq_del_norm2 = 0.;
for(int i=0; i<2; i++) dq_del_norm2 += dq_del[i]*dq_del[i];
double pixels_per_deg_el_have = sqrt(dq_del_norm2)*M_PI/180.;
*pixels_per_deg_el *= -pixels_per_deg_el_have;
}
}
// I now have the desired pixels_per_deg
//
// With LENSMODEL_LATLON or LENSMODEL_LONLAT we have even angular spacing, so
// q = f th + c -> dq/dth = f everywhere. I can thus compute the rectified
// image size and adjust the resolution accordingly
//
// With LENSMODEL_PINHOLE this is much more complex, so this function just
// leaves the desired pixels_per_deg as it is
if(rectification_model_type == MRCAL_LENSMODEL_LATLON ||
rectification_model_type == MRCAL_LENSMODEL_LONLAT)
{
int Naz = (int)round(azel_fov_deg->x * (*pixels_per_deg_az));
int Nel = (int)round(azel_fov_deg->y * (*pixels_per_deg_el));
*pixels_per_deg_az = (double)Naz/azel_fov_deg->x;
*pixels_per_deg_el = (double)Nel/azel_fov_deg->y;
}
return true;
}
// The equivalent function in Python is _rectified_system_python() in stereo.py
//
// Documentation is in the docstring of mrcal.rectified_system()
bool mrcal_rectified_system(// output
unsigned int* imagersize_rectified,
double* fxycxy_rectified,
double* rt_rect0_ref,
double* baseline,
// input, output
// > 0: use given value
// < 0: autodetect and scale
double* pixels_per_deg_az,
double* pixels_per_deg_el,
// input, output
// if(..._autodetect) { the results are returned here }
mrcal_point2_t* azel_fov_deg,
mrcal_point2_t* azel0_deg,
// input
const mrcal_lensmodel_t* lensmodel0,
const double* intrinsics0,
const double* rt_cam0_ref,
const double* rt_cam1_ref,
const mrcal_lensmodel_type_t rectification_model_type,
bool az0_deg_autodetect,
bool el0_deg_autodetect,
bool az_fov_deg_autodetect,
bool el_fov_deg_autodetect)
{
if(el0_deg_autodetect)
{
MSG("el0_deg_autodetect is unsupported");
return false;
}
if(az_fov_deg_autodetect)
{
MSG("az_fov_deg_autodetect is unsupported");
return false;
}
if(el_fov_deg_autodetect)
{
MSG("el_fov_deg_autodetect is unsupported");
return false;
}
if( !(rectification_model_type == MRCAL_LENSMODEL_LATLON ||
rectification_model_type == MRCAL_LENSMODEL_PINHOLE) )
{
MSG("Unsupported rectification model '%s'. Only LENSMODEL_LATLON and LENSMODEL_PINHOLE are supported",
mrcal_lensmodel_name_unconfigured( &(mrcal_lensmodel_t){.type = rectification_model_type}));
return false;
}
mrcal_lensmodel_metadata_t meta =
mrcal_lensmodel_metadata( lensmodel0 );
if(meta.noncentral)
{
if(lensmodel0->type == MRCAL_LENSMODEL_CAHVORE)
{
// CAHVORE is generally noncentral, but if E=0, then it is
const int Nintrinsics = mrcal_lensmodel_num_params(lensmodel0);
for(int i=Nintrinsics-3; i<Nintrinsics; i++)
if(intrinsics0[i] != 0)
{
MSG("Stereo rectification is only possible with a central projection. Please centralize your models. This is CAHVORE, so set E=0 to centralize. This will ignore all noncentral effects near the lens");
return false;
}
}
else
{
MSG("Stereo rectification is only possible with a central projection. Please centralize your models");
return false;
}
}
///// TODAY this C implementation supports MRCAL_LENSMODEL_LATLON only. This
///// isn't a design choice, I just don't want to do the extra work yet. The
///// API already is general enough to support both rectification schemes.
if( rectification_model_type != MRCAL_LENSMODEL_LATLON )
{
MSG("Today this C implementation supports MRCAL_LENSMODEL_LATLON only.");
return false;
}
if(*pixels_per_deg_az == 0)
{
MSG("pixels_per_deg_az == 0 is illegal. Must be >0 if we're trying to specify a value, or <0 to autodetect");
return false;
}
if(*pixels_per_deg_el == 0)
{
MSG("pixels_per_deg_el == 0 is illegal. Must be >0 if we're trying to specify a value, or <0 to autodetect");
return false;
}
if( azel_fov_deg->x <= 0. ||
azel_fov_deg->y <= 0.)
{
MSG("az_fov_deg, el_fov_deg must be > 0. No auto-detection implemented yet");
return false;
}
// Compute the geometry of the rectified stereo system. This is a
// rotation, centered at camera0. More or less we have axes:
//
// x: from camera0 to camera1
// y: completes the system from x,z
// z: component of the cameras' viewing direction
// normal to the baseline
double Rt_cam0_ref[4*3];
double Rt_cam1_ref[4*3];
mrcal_Rt_from_rt(Rt_cam0_ref, NULL, rt_cam0_ref);
mrcal_Rt_from_rt(Rt_cam1_ref, NULL, rt_cam1_ref);
double Rt01[4*3];
double Rt_ref_cam1[4*3];
mrcal_invert_Rt(Rt_ref_cam1,Rt_cam1_ref);
mrcal_compose_Rt(Rt01, Rt_cam0_ref, Rt_ref_cam1);
// Rotation relating camera0 coords to the rectified camera coords. I fill in
// each row separately
double Rt_rect0_cam0[4*3] = {};
double* R_rect0_cam0 = Rt_rect0_cam0;
// Axes of the rectified system, in the cam0 coord system
double* right = &R_rect0_cam0[0*3 + 0];
double* down = &R_rect0_cam0[1*3 + 0];
double* forward = &R_rect0_cam0[2*3 + 0];
// "right" of the rectified coord system: towards the origin of camera1 from
// camera0, in camera0 coords
for(int i=0; i<3; i++) right[i] = Rt01[3*3 + i];
*baseline = 0.0;
for(int i=0; i<3; i++) *baseline += right[i]*right[i];
*baseline = sqrt(*baseline);
for(int i=0; i<3; i++) right[i] /= (*baseline);
// "forward" of the rectified coord system, in camera0 coords. The mean
// optical-axis direction of the two cameras: component orthogonal to "right"
double forward01[3] =
{
Rt01[0*3 + 2],
Rt01[1*3 + 2],
Rt01[2*3 + 2] + 1.,
};
double forward01_proj_right = 0.0;
for(int i=0; i<3; i++) forward01_proj_right += forward01[i]*right[i];
for(int i=0; i<3; i++) forward[i] = forward01[i] - forward01_proj_right*right[i];
double norm2_forward = 0.;
for(int i=0; i<3; i++) norm2_forward += forward[i]*forward[i];
for(int i=0; i<3; i++) forward[i] /= sqrt(norm2_forward);
// "down" of the rectified coord system, in camera0 coords. Completes the
// right,down,forward coordinate system
// down = cross(forward,right)
down[0] = forward[1]*right[2] - forward[2]*right[1];
down[1] = forward[2]*right[0] - forward[0]*right[2];
down[2] = forward[0]*right[1] - forward[1]*right[0];
// Done with the geometry! Now to get the az/el grid. I need to figure
// out the resolution and the extents
mrcal_point2_t azel0 = { .x = azel0_deg->x * M_PI/180.,
.y = azel0_deg->y * M_PI/180. };
if(az0_deg_autodetect)
{
// In the rectified system az=0 sits perpendicular to the baseline.
// Normally the cameras are looking out perpendicular to the baseline
// also, so I center my azimuth samples around 0 to match the cameras'
// field of view. But what if the geometry isn't square, and one camera
// is behind the other? Like this:
//
// camera
// view
// ^
// |
// \ | /
// \_/
// . /
// . /az=0
// ./
// .
// baseline .
// .
// \ /
// \_/
//
// Here the center-of-view axis of each camera is not at all
// perpendicular to the baseline. Thus I compute the mean "forward"
// direction of the cameras in the rectified system, and set that as the
// center azimuth az0.
double norm2_forward01 = 0.0;
for(int i=0; i<3; i++) norm2_forward01 += forward01[i]*forward01[i];
azel0.x = asin( forward01_proj_right / sqrt(norm2_forward01) );
azel0_deg->x = azel0.x * 180./M_PI;
}
double R_cam0_rect0[3*3];
mrcal_invert_R(R_cam0_rect0, R_rect0_cam0);
if(!mrcal_rectified_resolution( // output
pixels_per_deg_az,
pixels_per_deg_el,
// input
lensmodel0,
intrinsics0,
azel_fov_deg,
azel0_deg,
R_cam0_rect0,
rectification_model_type))
return false;
// How do we apply the desired pixels_per_deg?
//
// With LENSMODEL_LATLON we have even angular spacing, so q = f th + c ->
// dq/dth = f everywhere.
//
// With LENSMODEL_PINHOLE the angular resolution changes across the image: q
// = f tan(th) + c -> dq/dth = f/cos^2(th). So at the center, th=0 and we
// have the maximum resolution
fxycxy_rectified[0] = *pixels_per_deg_az / M_PI*180.;
fxycxy_rectified[1] = *pixels_per_deg_el / M_PI*180.;
// if rectification_model == 'LENSMODEL_LATLON':
// # The angular resolution is consistent everywhere, so fx,fy are already
// # set. Let's set cx,cy such that
// # (az0,el0) = unproject(imager center)
// Naz = round(az_fov_deg*pixels_per_deg_az)
// Nel = round(el_fov_deg*pixels_per_deg_el)
imagersize_rectified[0] = (int)round(azel_fov_deg->x * (*pixels_per_deg_az));
imagersize_rectified[1] = (int)round(azel_fov_deg->y * (*pixels_per_deg_el));
// fxycxy[2:] =
// np.array(((Naz-1.)/2.,(Nel-1.)/2.)) -
// np.array((az0,el0)) * fxycxy[:2]
fxycxy_rectified[2] = ((double)(imagersize_rectified[0] - 1)) / 2 - azel0.x * fxycxy_rectified[0];
fxycxy_rectified[3] = ((double)(imagersize_rectified[1] - 1)) / 2 - azel0.y * fxycxy_rectified[1];
if(imagersize_rectified[1] <= 0)
{
MSG("Resulting stereo geometry has Nel=%d. This is nonsensical. You should examine the geometry or adjust the elevation bounds or pixels-per-deg",
imagersize_rectified[1]);
return false;
}
// The geometry
double Rt_rect0_ref[4*3];
mrcal_compose_Rt(Rt_rect0_ref,
Rt_rect0_cam0, Rt_cam0_ref);
mrcal_rt_from_Rt(rt_rect0_ref, NULL, Rt_rect0_ref);
return true;
}
static
void set_rectification_map_pixel(// output
float* rectification_map0,
float* rectification_map1,
// input
const int i, const int j,
const mrcal_point3_t* v,
const mrcal_lensmodel_t* lensmodel0,
const double* intrinsics0,
const double* R_cam0_rect,
const mrcal_lensmodel_t* lensmodel1,
const double* intrinsics1,
const double* R_cam1_rect,
const unsigned int* imagersize_rectified)
{
mrcal_point3_t vcam;
mrcal_point2_t q;
vcam = *v;
mrcal_rotate_point_R(vcam.xyz, NULL, NULL,
R_cam0_rect, v->xyz);
mrcal_project(&q, NULL, NULL,
&vcam, 1,
lensmodel0, intrinsics0);
rectification_map0[(i*imagersize_rectified[0] + j)*2 + 0] = (float)q.x;
rectification_map0[(i*imagersize_rectified[0] + j)*2 + 1] = (float)q.y;
vcam = *v;
mrcal_rotate_point_R(vcam.xyz, NULL, NULL,
R_cam1_rect, v->xyz);
mrcal_project(&q, NULL, NULL,
&vcam, 1,
lensmodel1, intrinsics1);
rectification_map1[(i*imagersize_rectified[0] + j)*2 + 0] = (float)q.x;
rectification_map1[(i*imagersize_rectified[0] + j)*2 + 1] = (float)q.y;
}
bool mrcal_rectification_maps(// output
// Dense array of shape (Ncameras=2, Nel, Naz, Nxy=2)
float* rectification_maps,
// input
const mrcal_lensmodel_t* lensmodel0,
const double* intrinsics0,
const double* r_cam0_ref,
const mrcal_lensmodel_t* lensmodel1,
const double* intrinsics1,
const double* r_cam1_ref,
const mrcal_lensmodel_type_t rectification_model_type,
const double* fxycxy_rectified,
const unsigned int* imagersize_rectified,
const double* r_rect0_ref)
{
///// TODAY this C implementation supports MRCAL_LENSMODEL_LATLON only. This
///// isn't a design choice, I just don't want to do the extra work yet. The
///// API already is general enough to support both rectification schemes.
if( ! (rectification_model_type == MRCAL_LENSMODEL_LATLON ||
rectification_model_type == MRCAL_LENSMODEL_PINHOLE) )
{
MSG("%s() supports MRCAL_LENSMODEL_LATLON and MRCAL_LENSMODEL_PINHOLE only",
__func__);
return false;
}
double R_cam0_ref[3*3];
double R_cam1_ref[3*3];
mrcal_R_from_r(R_cam0_ref, NULL, r_cam0_ref);
mrcal_R_from_r(R_cam1_ref, NULL, r_cam1_ref);
double R_cam0_rect[3*3];
double R_cam1_rect[3*3];
double R_rect0_ref[3*3];
mrcal_R_from_r(R_rect0_ref, NULL, r_rect0_ref);
mul_genN3_gen33t_vout(3, R_cam0_ref, R_rect0_ref, R_cam0_rect);
mul_genN3_gen33t_vout(3, R_cam1_ref, R_rect0_ref, R_cam1_rect);
float* rectification_map0 = &(rectification_maps[0]);
float* rectification_map1 = &(rectification_maps[imagersize_rectified[0]*imagersize_rectified[1]*2]);
// I had this:
// for(int i=0; i<imagersize_rectified[1]; i++)
// for(int j=0; j<imagersize_rectified[0]; j++)
// {
// mrcal_point2_t q = {.x = j, .y = i};
// mrcal_point3_t v;
// mrcal_unproject_latlon(&v, NULL,
// &q,
// 1,
// fxycxy_rectified);
// ....
//
// I'm inlining the mrcal_unproject_latlon() call, and moving some constant
// guts outside the loops.
//
// And I'm computing sin,cos incrementally:
// sin(x0 + dx) = sin(x0)*cos(dx) + cos(x0)*sin(dx)
// cos(x0 + dx) = cos(x0)*cos(dx) - sin(x0)*sin(dx)
//
// Since dx is constant here I can compute the sin/cos sequence very
// quickly. One concern about this is that each computation would accumulate
// floating-point error, which could add up. The test-rectification-maps.py
// test explicitly checks for this, and determines that this isn't an issue
const double fx = fxycxy_rectified[0];
const double fy = fxycxy_rectified[1];
const double fx_recip = 1./fx;
const double fy_recip = 1./fy;
const double c_over_f_x = fxycxy_rectified[2] * fx_recip;
const double c_over_f_y = fxycxy_rectified[3] * fy_recip;
if(rectification_model_type == MRCAL_LENSMODEL_LATLON)
{
double sdlon = sin(fy_recip);
double cdlon = cos(fy_recip);
double sdlat = sin(fx_recip);
double cdlat = cos(fx_recip);
double lon0 = -c_over_f_y;
double slon0 = sin(lon0);
double clon0 = cos(lon0);
double lat0 = -c_over_f_x;
double slat0 = sin(lat0);
double clat0 = cos(lat0);
double slon = slon0, clon = clon0;
for(unsigned int i=0; i<imagersize_rectified[1]; i++)
{
double slat = slat0, clat = clat0;
for(unsigned int j=0; j<imagersize_rectified[0]; j++)
{
mrcal_point3_t v =
(mrcal_point3_t){.x = slat,
.y = clat * slon,
.z = clat * clon};
set_rectification_map_pixel( rectification_map0,
rectification_map1,
i,j,&v,
lensmodel0,
intrinsics0,
R_cam0_rect,
lensmodel1,
intrinsics1,
R_cam1_rect,
imagersize_rectified);
double _slat = slat;
slat = _slat*cdlat + clat*sdlat;
clat = clat*cdlat - _slat*sdlat;
}
double _slon = slon;
slon = _slon*cdlon + clon*sdlon;
clon = clon*cdlon - _slon*sdlon;
}
}
else
{
// MRCAL_LENSMODEL_PINHOLE
for(unsigned int i=0; i<imagersize_rectified[1]; i++)
{
for(unsigned int j=0; j<imagersize_rectified[0]; j++)
{
mrcal_point3_t v =
(mrcal_point3_t){.x = (double)j*fx_recip - c_over_f_x,
.y = (double)i*fy_recip - c_over_f_y,
.z = 1.0};
set_rectification_map_pixel( rectification_map0,
rectification_map1,
i,j,&v,
lensmodel0,
intrinsics0,
R_cam0_rect,
lensmodel1,
intrinsics1,
R_cam1_rect,
imagersize_rectified);
}
}
}
return true;
}
// Logic from GetColorValueFromFormula() in src/getcolor.c in the gnuplot
// sources
static bool
gnuplot_color_formula(uint8_t* out,
int formula, float x)
{
/* the input gray x is supposed to be in interval [0,1] */
if (formula < 0) { /* negate the value for negative formula */
x = 1.f - x;
formula = -formula;
}
switch (formula) {
case 0:
x = 0.f;
break;
case 1:
x = 0.5f;
break;
case 2:
x = 1.f;
break;
case 3: /* x = x */
break;
case 4:
x = x * x;
break;
case 5:
x = x * x * x;
break;
case 6:
x = x * x * x * x;
break;
case 7:
x = sqrtf(x);
break;
case 8:
x = sqrtf(sqrtf(x));
break;
case 9:
x = sinf(90.f * x * M_PI/180.f);
break;
case 10:
x = cosf(90.f * x * M_PI/180.f);
break;
case 11:
x = fabsf(x - 0.5f);
break;
case 12:
x = (2.f * x - 1.f) * (2.0 * x - 1.f);
break;
case 13:
x = sinf(180.f * x * M_PI/180.f);
break;
case 14:
x = fabsf(cosf(180.f * x * M_PI/180.f));
break;
case 15:
x = sinf(360.f * x * M_PI/180.f);
break;
case 16:
x = cosf(360.f * x * M_PI/180.f);
break;
case 17:
x = fabsf(sinf(360.f * x * M_PI/180.f));
break;
case 18:
x = fabsf(cosf(360.f * x * M_PI/180.f));
break;
case 19:
x = fabsf(sinf(720.f * x * M_PI/180.f));
break;
case 20:
x = fabsf(cosf(720.f * x * M_PI/180.f));
break;
case 21:
x = 3.f * x;
break;
case 22:
x = 3.f * x - 1.f;
break;
case 23:
x = 3.f * x - 2.f;
break;
case 24:
x = fabsf(3.f * x - 1.f);
break;
case 25:
x = fabsf(3.f * x - 2.f);
break;
case 26:
x = (1.5f * x - 0.5f);
break;
case 27:
x = (1.5f * x - 1.f);
break;
case 28:
x = fabsf(1.5f * x - 0.5f);
break;
case 29:
x = fabsf(1.5f * x - 1.f);
break;
case 30:
if (x <= 0.25f)
x = 0.f;
else if (x >= 0.57f)
x = 1.f;
else
x = x / 0.32f - 0.78125f;
break;
case 31:
if (x <= 0.42f)
x = 0.f;
else if (x >= 0.92f)
x = 1.f;
else
x = 2.f * x - 0.84f;
break;
case 32:
if (x <= 0.42f)
x *= 4.f;
else
x = (x <= 0.92f) ? -2.f * x + 1.84f : x / 0.08f - 11.5f;
break;
case 33:
x = fabsf(2.f * x - 0.5f);
break;
case 34:
x = 2.f * x;
break;
case 35:
x = 2.f * x - 0.5f;
break;
case 36:
x = 2.f * x - 1.f;
break;
default:
return false;
}
if (x <= 0.f) x = 0.f;
else if (x >= 1.f) x = 1.f;
// round to nearest integer
*out = (uint8_t)(0.5f + 255.0f*x);
return true;
}
// Color-code an array
// I use gnuplot's color-mapping functions to do this. gnuplot's "show palette"
// help message displays the current gnuplot settings and "test palette"
// displays the palette. The function definitions are given by "show palette
// rgbformulae":
//
// > show palette rgbformulae
// * there are 37 available rgb color mapping formulae:
// 0: 0 1: 0.5 2: 1
// 3: x 4: x^2 5: x^3
// 6: x^4 7: sqrt(x) 8: sqrt(sqrt(x))
// 9: sin(90x) 10: cos(90x) 11: |x-0.5|
// 12: (2x-1)^2 13: sin(180x) 14: |cos(180x)|
// 15: sin(360x) 16: cos(360x) 17: |sin(360x)|
// 18: |cos(360x)| 19: |sin(720x)| 20: |cos(720x)|
// 21: 3x 22: 3x-1 23: 3x-2
// 24: |3x-1| 25: |3x-2| 26: (3x-1)/2
// 27: (3x-2)/2 28: |(3x-1)/2| 29: |(3x-2)/2|
// 30: x/0.32-0.78125 31: 2*x-0.84 32: 4x;1;-2x+1.84;x/0.08-11.5
// 33: |2*x - 0.5| 34: 2*x 35: 2*x - 0.5
// 36: 2*x - 1
// * negative numbers mean inverted=negative colour component
// * thus the ranges in `set pm3d rgbformulae' are -36..36
#define DEFINE_mrcal_apply_color_map(T,Tname,T_MIN,T_MAX) \
bool mrcal_apply_color_map_##Tname( \
mrcal_image_bgr_t* out, \
const mrcal_image_##Tname##_t* in, \
\
/* If true, I set in_min/in_max from the */ \
/* min/max of the input data */ \
const bool auto_min, \
const bool auto_max, \
\
/* If true, I implement gnuplot's default 7,5,15 mapping. */ \
/* This is a reasonable default choice. */ \
/* function_red/green/blue are ignored if true */ \
const bool auto_function, \
\
/* min/max input values to use if not */ \
/* auto_min/auto_max */ \
T in_min, /* will map to 0 */ \
T in_max, /* will map to 255 */ \
\
/* The color mappings to use. If !auto_function */ \
int function_red, \
int function_green, \
int function_blue) \
{ \
const int w = in->width; \
const int h = in->height; \
if(!(w == out->width && h == out->height)) \
{ \
MSG("%s(): input and output images MUST have the same dimensions", \
__func__); \
return false; \
} \
\
if(auto_min || auto_max) \
{ \
if(auto_min) in_min = T_MAX; \
if(auto_max) in_max = T_MIN; \
\
for(int y=0; y<h; y++) \
for(int x=0; x<w; x++) \
{ \
const T v = *mrcal_image_##Tname##_at_const(in, x,y); \
if(auto_min && v < in_min) in_min = v; \
if(auto_max && v > in_max) in_max = v; \
} \
} \
\
if(auto_function) \
{ \
function_red = 7; \
function_green = 5; \
function_blue = 15; \
} \
\
for(int y=0; y<h; y++) \
{ \
for(int x=0; x<w; x++) \
{ \
const T* in_T = mrcal_image_##Tname##_at_const(in, x,y); \
\
mrcal_bgr_t* out_bgr = mrcal_image_bgr_at( out, x,y); \
\
float x; \
if (*in_T <= in_min) \
x = 0.0f; \
else if(*in_T >= in_max) \
x = 1.0f; \
else \
x = (float)(*in_T - in_min) / (float)(in_max - in_min); \
\
if(!gnuplot_color_formula(&out_bgr->bgr[2], function_red, x) || \
!gnuplot_color_formula(&out_bgr->bgr[1], function_green, x) || \
!gnuplot_color_formula(&out_bgr->bgr[0], function_blue, x)) \
return false; \
} \
} \
\
return true; \
}
DEFINE_mrcal_apply_color_map(uint8_t, uint8, 0, UINT8_MAX)
DEFINE_mrcal_apply_color_map(uint16_t, uint16, 0, UINT16_MAX)
DEFINE_mrcal_apply_color_map(uint32_t, uint32, 0, UINT32_MAX)
DEFINE_mrcal_apply_color_map(uint64_t, uint64, 0, UINT64_MAX)
DEFINE_mrcal_apply_color_map(int8_t, int8, INT8_MIN, INT8_MAX)
DEFINE_mrcal_apply_color_map(int16_t, int16, INT16_MIN, INT16_MAX)
DEFINE_mrcal_apply_color_map(int32_t, int32, INT32_MIN, INT32_MAX)
DEFINE_mrcal_apply_color_map(int64_t, int64, INT64_MIN, INT64_MAX)
DEFINE_mrcal_apply_color_map(float, float, FLT_MIN, FLT_MAX)
DEFINE_mrcal_apply_color_map(double, double, DBL_MIN, DBL_MAX)
static bool _validate_rectification_model_type(const mrcal_lensmodel_type_t rectification_model_type)
{
if(rectification_model_type == MRCAL_LENSMODEL_LATLON ||
rectification_model_type == MRCAL_LENSMODEL_PINHOLE)
return true;
// ERROR
const char* rectification_model_string =
mrcal_lensmodel_name_unconfigured( &(mrcal_lensmodel_t){.type = rectification_model_type} );
if(rectification_model_string == NULL)
{
MSG("Unknown rectification_model_type=%d\n", rectification_model_type);
return false;
}
MSG("Invalid rectification_model_type for rectification: %s; I know about MRCAL_LENSMODEL_LATLON and MRCAL_LENSMODEL_PINHOLE\n",
rectification_model_string);
return false;
}
static double _stereo_range_one(const double disparity,
const mrcal_point2_t qrect0,
// models_rectified
const mrcal_lensmodel_type_t rectification_model_type,
const double* fxycxy_rectified,
const double baseline )
{
// See the docstring for mrcal.stereo_range() for the derivation
const double fx = fxycxy_rectified[0];
const double fy = fxycxy_rectified[1];
const double cx = fxycxy_rectified[2];
const double cy = fxycxy_rectified[3];
if(rectification_model_type == MRCAL_LENSMODEL_LATLON)
{
const double az0 = (qrect0.x - cx)/fx;
const double disparity_rad = disparity / fx;
const double range =
baseline *
cos(az0 - disparity_rad) / sin(disparity_rad);
if(!isfinite(range)) return 0.0;
return range;
}
// _validate_rectification_model_type() makes sure this is true
// if(rectification_model_type == MRCAL_LENSMODEL_PINHOLE)
{
const double tanaz0 = (qrect0.x - cx) / fx;
const double tanel = (qrect0.y - cy) / fy;
const double s_sq_recip = tanel*tanel + 1.;
const double tanaz0_tanaz1 = disparity / fx;
const double tanaz1 = tanaz0 - tanaz0_tanaz1;
const double range =
baseline /
sqrt(s_sq_recip + tanaz0*tanaz0) *
( (s_sq_recip + tanaz0*tanaz1) / tanaz0_tanaz1 +
tanaz0 );
if(!isfinite(range)) return 0.0;
return range;
}
}
bool mrcal_stereo_range_sparse(// output
double* range, // N of these
// input
const double* disparity, // N of these
const mrcal_point2_t* qrect0, // N of these
const int N, // how many points
const double disparity_min,
const double disparity_max,
// models_rectified
const mrcal_lensmodel_type_t rectification_model_type,
const double* fxycxy_rectified,
const double baseline)
{
if(!_validate_rectification_model_type(rectification_model_type))
return false;
if(disparity_min >= disparity_max)
{
MSG("Must have disparity_max > disparity_min");
return false;
}
for(int i=0; i<N; i++)
{
if(disparity[i] <= 0.0 ||
disparity[i] < disparity_min ||
disparity[i] > disparity_max )
{
range[i] = 0.0;
}
else
range[i] = _stereo_range_one(disparity[i],
qrect0[i],
rectification_model_type,