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mrcal.c
6847 lines (6015 loc) · 295 KB
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mrcal.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 <stdio.h>
#include <stdlib.h>
#include <inttypes.h>
#include <dogleg.h>
#include <assert.h>
#include <stdbool.h>
#include <math.h>
#include <string.h>
#include "mrcal.h"
#include "minimath/minimath.h"
#include "cahvore.h"
#include "minimath/minimath-extra.h"
#include "util.h"
#include "scales.h"
#define MSG_IF_VERBOSE(...) do { if(verbose) MSG( __VA_ARGS__ ); } while(0)
// Returns a static string, using "..." as a placeholder for any configuration
// values
#define LENSMODEL_PRINT_CFG_ELEMENT_TEMPLATE(name, type, pybuildvaluecode, PRIcode,SCNcode, bitfield, cookie) \
"_" #name "=..."
#define LENSMODEL_PRINT_CFG_ELEMENT_FMT(name, type, pybuildvaluecode, PRIcode,SCNcode, bitfield, cookie) \
"_" #name "=%" PRIcode
#define LENSMODEL_PRINT_CFG_ELEMENT_VAR(name, type, pybuildvaluecode, PRIcode,SCNcode, bitfield, cookie) \
,config->name
#define LENSMODEL_SCAN_CFG_ELEMENT_FMT(name, type, pybuildvaluecode, PRIcode,SCNcode, bitfield, cookie) \
"_" #name "=%" SCNcode
#define LENSMODEL_SCAN_CFG_ELEMENT_VAR(name, type, pybuildvaluecode, PRIcode,SCNcode, bitfield, cookie) \
,&config->name
#define LENSMODEL_SCAN_CFG_ELEMENT_PLUS1(name, type, pybuildvaluecode, PRIcode,SCNcode, bitfield, cookie) \
+1
const char* mrcal_lensmodel_name_unconfigured( const mrcal_lensmodel_t* lensmodel )
{
switch(lensmodel->type)
{
#define CASE_STRING_NOCONFIG(s,n) case MRCAL_##s: ; \
return #s;
#define _CASE_STRING_WITHCONFIG(s,n,s_CONFIG_LIST) case MRCAL_##s: ; \
return #s s_CONFIG_LIST(LENSMODEL_PRINT_CFG_ELEMENT_TEMPLATE, );
#define CASE_STRING_WITHCONFIG(s,n) _CASE_STRING_WITHCONFIG(s,n,MRCAL_ ## s ## _CONFIG_LIST)
MRCAL_LENSMODEL_NOCONFIG_LIST( CASE_STRING_NOCONFIG )
MRCAL_LENSMODEL_WITHCONFIG_STATIC_NPARAMS_LIST( CASE_STRING_WITHCONFIG )
MRCAL_LENSMODEL_WITHCONFIG_DYNAMIC_NPARAMS_LIST( CASE_STRING_WITHCONFIG )
default:
return NULL;
#undef CASE_STRING_NOCONFIG
#undef CASE_STRING_WITHCONFIG
}
return NULL;
}
// Write the model name WITH the full config into the given buffer. Identical to
// mrcal_lensmodel_name_unconfigured() for configuration-free models
static int LENSMODEL_CAHVORE__snprintf_model
(char* out, int size,
const mrcal_LENSMODEL_CAHVORE__config_t* config)
{
return
snprintf( out, size, "LENSMODEL_CAHVORE"
MRCAL_LENSMODEL_CAHVORE_CONFIG_LIST(LENSMODEL_PRINT_CFG_ELEMENT_FMT, )
MRCAL_LENSMODEL_CAHVORE_CONFIG_LIST(LENSMODEL_PRINT_CFG_ELEMENT_VAR, ));
}
static int LENSMODEL_SPLINED_STEREOGRAPHIC__snprintf_model
(char* out, int size,
const mrcal_LENSMODEL_SPLINED_STEREOGRAPHIC__config_t* config)
{
return
snprintf( out, size, "LENSMODEL_SPLINED_STEREOGRAPHIC"
MRCAL_LENSMODEL_SPLINED_STEREOGRAPHIC_CONFIG_LIST(LENSMODEL_PRINT_CFG_ELEMENT_FMT, )
MRCAL_LENSMODEL_SPLINED_STEREOGRAPHIC_CONFIG_LIST(LENSMODEL_PRINT_CFG_ELEMENT_VAR, ));
}
bool mrcal_lensmodel_name( char* out, int size, const mrcal_lensmodel_t* lensmodel )
{
switch(lensmodel->type)
{
#define CASE_STRING_NOCONFIG(s,n) case MRCAL_##s: \
return size > snprintf(out,size, #s);
#define CASE_STRING_WITHCONFIG(s,n) case MRCAL_##s: \
return size > s##__snprintf_model(out, size, &lensmodel->s##__config);
MRCAL_LENSMODEL_NOCONFIG_LIST( CASE_STRING_NOCONFIG )
MRCAL_LENSMODEL_WITHCONFIG_STATIC_NPARAMS_LIST( CASE_STRING_WITHCONFIG )
MRCAL_LENSMODEL_WITHCONFIG_DYNAMIC_NPARAMS_LIST( CASE_STRING_WITHCONFIG )
default:
return NULL;
#undef CASE_STRING_NOCONFIG
#undef CASE_STRING_WITHCONFIG
}
return NULL;
}
static bool LENSMODEL_CAHVORE__scan_model_config( mrcal_LENSMODEL_CAHVORE__config_t* config, const char* config_str)
{
int pos;
int Nelements = 0 MRCAL_LENSMODEL_CAHVORE_CONFIG_LIST(LENSMODEL_SCAN_CFG_ELEMENT_PLUS1, );
return
Nelements ==
sscanf( config_str,
MRCAL_LENSMODEL_CAHVORE_CONFIG_LIST(LENSMODEL_SCAN_CFG_ELEMENT_FMT, )"%n"
MRCAL_LENSMODEL_CAHVORE_CONFIG_LIST(LENSMODEL_SCAN_CFG_ELEMENT_VAR, ),
&pos) &&
config_str[pos] == '\0';
}
static bool LENSMODEL_SPLINED_STEREOGRAPHIC__scan_model_config( mrcal_LENSMODEL_SPLINED_STEREOGRAPHIC__config_t* config, const char* config_str)
{
int pos;
int Nelements = 0 MRCAL_LENSMODEL_SPLINED_STEREOGRAPHIC_CONFIG_LIST(LENSMODEL_SCAN_CFG_ELEMENT_PLUS1, );
return
Nelements ==
sscanf( config_str,
MRCAL_LENSMODEL_SPLINED_STEREOGRAPHIC_CONFIG_LIST(LENSMODEL_SCAN_CFG_ELEMENT_FMT, )"%n"
MRCAL_LENSMODEL_SPLINED_STEREOGRAPHIC_CONFIG_LIST(LENSMODEL_SCAN_CFG_ELEMENT_VAR, ),
&pos) &&
config_str[pos] == '\0';
}
const char* const* mrcal_supported_lensmodel_names( void )
{
#define NAMESTRING_NOCONFIG(s,n) #s,
#define _NAMESTRING_WITHCONFIG(s,n,s_CONFIG_LIST) #s s_CONFIG_LIST(LENSMODEL_PRINT_CFG_ELEMENT_TEMPLATE, ),
#define NAMESTRING_WITHCONFIG(s,n) _NAMESTRING_WITHCONFIG(s,n,MRCAL_ ## s ## _CONFIG_LIST)
static const char* names[] = {
MRCAL_LENSMODEL_NOCONFIG_LIST( NAMESTRING_NOCONFIG)
MRCAL_LENSMODEL_WITHCONFIG_STATIC_NPARAMS_LIST( NAMESTRING_WITHCONFIG)
MRCAL_LENSMODEL_WITHCONFIG_DYNAMIC_NPARAMS_LIST(NAMESTRING_WITHCONFIG)
NULL };
return names;
}
#undef LENSMODEL_PRINT_CFG_ELEMENT_TEMPLATE
#undef LENSMODEL_PRINT_CFG_ELEMENT_FMT
#undef LENSMODEL_PRINT_CFG_ELEMENT_VAR
#undef LENSMODEL_SCAN_CFG_ELEMENT_FMT
#undef LENSMODEL_SCAN_CFG_ELEMENT_VAR
#undef LENSMODEL_SCAN_CFG_ELEMENT_PLUS1
// parses the model name AND the configuration into a mrcal_lensmodel_t structure.
// On error returns false with lensmodel->type set to MRCAL_LENSMODEL_INVALID_...
bool mrcal_lensmodel_from_name( // output
mrcal_lensmodel_t* lensmodel,
// input
const char* name )
{
#define CHECK_AND_RETURN_NOCONFIG(s,n) \
if( 0 == strcmp( name, #s) ) \
{ \
*lensmodel = (mrcal_lensmodel_t){.type = MRCAL_##s}; \
return true; \
}
#define CHECK_AND_RETURN_WITHCONFIG(s,n) \
/* Configured model. I need to extract the config from the string. */ \
/* The string format is NAME_cfg1=var1_cfg2=var2... */ \
{ \
const int len_s = strlen(#s); \
if( 0 == strncmp( name, #s, len_s ) ) \
{ \
if(name[len_s] == '\0') \
{ \
*lensmodel = (mrcal_lensmodel_t){.type = MRCAL_LENSMODEL_INVALID_MISSINGCONFIG}; \
return false; \
} \
if(name[len_s] == '_') \
{ \
/* found name. Now extract the config */ \
*lensmodel = (mrcal_lensmodel_t){.type = MRCAL_##s}; \
mrcal_##s##__config_t* config = &lensmodel->s##__config; \
\
const char* config_str = &name[len_s]; \
\
if(s##__scan_model_config(config, config_str)) \
return true; \
\
*lensmodel = (mrcal_lensmodel_t){.type = MRCAL_LENSMODEL_INVALID_BADCONFIG}; \
return false; \
} \
} \
}
if(name == NULL)
{
*lensmodel = (mrcal_lensmodel_t){.type = MRCAL_LENSMODEL_INVALID_TYPE};
return false;
}
MRCAL_LENSMODEL_NOCONFIG_LIST( CHECK_AND_RETURN_NOCONFIG );
MRCAL_LENSMODEL_WITHCONFIG_STATIC_NPARAMS_LIST( CHECK_AND_RETURN_WITHCONFIG );
MRCAL_LENSMODEL_WITHCONFIG_DYNAMIC_NPARAMS_LIST( CHECK_AND_RETURN_WITHCONFIG );
*lensmodel = (mrcal_lensmodel_t){.type = MRCAL_LENSMODEL_INVALID_TYPE};
return false;
#undef CHECK_AND_RETURN_NOCONFIG
#undef CHECK_AND_RETURN_WITHCONFIG
}
// parses the model name only. The configuration is ignored. Even if it's
// missing or unparseable. Unknown model names return
// MRCAL_LENSMODEL_INVALID_TYPE
mrcal_lensmodel_type_t mrcal_lensmodel_type_from_name( const char* name )
{
#define CHECK_AND_RETURN_NOCONFIG(s,n) \
if( 0 == strcmp( name, #s) ) return MRCAL_##s;
#define CHECK_AND_RETURN_WITHCONFIG(s,n) \
/* Configured model. If the name is followed by _ or nothing, I */ \
/* accept this model */ \
{ \
const int len_s = strlen(#s); \
if( 0 == strncmp( name, #s, len_s) && \
( name[len_s] == '\0' || \
name[len_s] == '_' ) ) \
return MRCAL_##s; \
}
if(name == NULL)
return MRCAL_LENSMODEL_INVALID_TYPE;
MRCAL_LENSMODEL_NOCONFIG_LIST( CHECK_AND_RETURN_NOCONFIG );
MRCAL_LENSMODEL_WITHCONFIG_STATIC_NPARAMS_LIST( CHECK_AND_RETURN_WITHCONFIG );
MRCAL_LENSMODEL_WITHCONFIG_DYNAMIC_NPARAMS_LIST( CHECK_AND_RETURN_WITHCONFIG );
return MRCAL_LENSMODEL_INVALID_TYPE;
#undef CHECK_AND_RETURN_NOCONFIG
#undef CHECK_AND_RETURN_WITHCONFIG
}
mrcal_lensmodel_metadata_t mrcal_lensmodel_metadata( const mrcal_lensmodel_t* lensmodel )
{
switch(lensmodel->type)
{
case MRCAL_LENSMODEL_SPLINED_STEREOGRAPHIC:
case MRCAL_LENSMODEL_STEREOGRAPHIC:
case MRCAL_LENSMODEL_LONLAT:
case MRCAL_LENSMODEL_LATLON:
return (mrcal_lensmodel_metadata_t) { .has_core = true,
.can_project_behind_camera = true,
.has_gradients = true,
.noncentral = false};
case MRCAL_LENSMODEL_PINHOLE:
case MRCAL_LENSMODEL_OPENCV4:
case MRCAL_LENSMODEL_OPENCV5:
case MRCAL_LENSMODEL_OPENCV8:
case MRCAL_LENSMODEL_OPENCV12:
case MRCAL_LENSMODEL_CAHVOR:
return (mrcal_lensmodel_metadata_t) { .has_core = true,
.can_project_behind_camera = false,
.has_gradients = true,
.noncentral = false };
case MRCAL_LENSMODEL_CAHVORE:
return (mrcal_lensmodel_metadata_t) { .has_core = true,
.can_project_behind_camera = false,
.has_gradients = true,
.noncentral = true };
default: ;
}
MSG("Unknown lens model %d. Barfing out", lensmodel->type);
assert(0);
}
static
bool modelHasCore_fxfycxcy( const mrcal_lensmodel_t* lensmodel )
{
mrcal_lensmodel_metadata_t meta = mrcal_lensmodel_metadata(lensmodel);
return meta.has_core;
}
static
bool model_supports_projection_behind_camera( const mrcal_lensmodel_t* lensmodel )
{
mrcal_lensmodel_metadata_t meta = mrcal_lensmodel_metadata(lensmodel);
return meta.can_project_behind_camera;
}
static int LENSMODEL_SPLINED_STEREOGRAPHIC__lensmodel_num_params(const mrcal_LENSMODEL_SPLINED_STEREOGRAPHIC__config_t* config)
{
return
// I have two surfaces: one for x and another for y
(int)config->Nx * (int)config->Ny * 2 +
// and I have a core
4;
}
int mrcal_lensmodel_num_params(const mrcal_lensmodel_t* lensmodel)
{
#define CHECK_CONFIG_NPARAM_NOCONFIG(s,n) \
_Static_assert(n >= 0, "no-config implies known-at-compile-time param count");
switch(lensmodel->type)
{
#define CASE_NUM_STATIC(s,n) \
case MRCAL_##s: return n;
#define CASE_NUM_DYNAMIC(s,n) \
case MRCAL_##s: return s##__lensmodel_num_params(&lensmodel->s##__config);
MRCAL_LENSMODEL_NOCONFIG_LIST( CASE_NUM_STATIC )
MRCAL_LENSMODEL_WITHCONFIG_STATIC_NPARAMS_LIST( CASE_NUM_STATIC )
MRCAL_LENSMODEL_WITHCONFIG_DYNAMIC_NPARAMS_LIST( CASE_NUM_DYNAMIC )
default: ;
}
return -1;
#undef CASE_NUM_NOCONFIG
#undef CASE_NUM_WITHCONFIG
}
static
int get_num_distortions_optimization_params(mrcal_problem_selections_t problem_selections,
const mrcal_lensmodel_t* lensmodel)
{
if( !problem_selections.do_optimize_intrinsics_distortions )
return 0;
int N = mrcal_lensmodel_num_params(lensmodel);
if(modelHasCore_fxfycxcy(lensmodel))
N -= 4; // ignoring fx,fy,cx,cy
return N;
}
int mrcal_num_intrinsics_optimization_params(mrcal_problem_selections_t problem_selections,
const mrcal_lensmodel_t* lensmodel)
{
int N = get_num_distortions_optimization_params(problem_selections, lensmodel);
if( problem_selections.do_optimize_intrinsics_core &&
modelHasCore_fxfycxcy(lensmodel) )
N += 4; // fx,fy,cx,cy
return N;
}
int mrcal_num_states(int Ncameras_intrinsics, int Ncameras_extrinsics,
int Nframes,
int Npoints, int Npoints_fixed, int Nobservations_board,
mrcal_problem_selections_t problem_selections,
const mrcal_lensmodel_t* lensmodel)
{
return
mrcal_num_states_intrinsics(Ncameras_intrinsics,
problem_selections,
lensmodel) +
mrcal_num_states_extrinsics(Ncameras_extrinsics,
problem_selections) +
mrcal_num_states_frames(Nframes,
problem_selections) +
mrcal_num_states_points(Npoints, Npoints_fixed,
problem_selections) +
mrcal_num_states_calobject_warp( problem_selections,
Nobservations_board);
}
static int num_regularization_terms_percamera(mrcal_problem_selections_t problem_selections,
const mrcal_lensmodel_t* lensmodel)
{
if(!problem_selections.do_apply_regularization)
return 0;
// distortions
int N = get_num_distortions_optimization_params(problem_selections, lensmodel);
// optical center
if(problem_selections.do_optimize_intrinsics_core)
N += 2;
return N;
}
int mrcal_measurement_index_boards(int i_observation_board,
int Nobservations_board,
int Nobservations_point,
int calibration_object_width_n,
int calibration_object_height_n)
{
if(Nobservations_board <= 0)
return -1;
// *2 because I have separate x and y measurements
return
0 +
mrcal_num_measurements_boards(i_observation_board,
calibration_object_width_n,
calibration_object_height_n);
}
int mrcal_num_measurements_boards(int Nobservations_board,
int calibration_object_width_n,
int calibration_object_height_n)
{
if(Nobservations_board <= 0)
return 0;
// *2 because I have separate x and y measurements
return
Nobservations_board *
calibration_object_width_n*calibration_object_height_n *
2;
return mrcal_measurement_index_boards( Nobservations_board,
0,0,
calibration_object_width_n,
calibration_object_height_n);
}
int mrcal_measurement_index_points(int i_observation_point,
int Nobservations_board,
int Nobservations_point,
int calibration_object_width_n,
int calibration_object_height_n)
{
if(Nobservations_point <= 0)
return -1;
// 2: x,y measurements
return
mrcal_num_measurements_boards(Nobservations_board,
calibration_object_width_n,
calibration_object_height_n) +
i_observation_point * 2;
}
#warning "triangulated-solve: need known-range points, at-infinity points"
int mrcal_num_measurements_points(int Nobservations_point)
{
// 2: x,y measurements
return Nobservations_point * 2;
}
#warning "triangulated-solve: Add a test for mrcal_measurement_index_points_triangulated()"
int mrcal_measurement_index_points_triangulated(int i_point_triangulated,
int Nobservations_board,
int Nobservations_point,
// May be NULL if we don't have any of these
const mrcal_observation_point_triangulated_t* observations_point_triangulated,
int Nobservations_point_triangulated,
int calibration_object_width_n,
int calibration_object_height_n)
{
if(observations_point_triangulated == NULL ||
Nobservations_point_triangulated <= 0)
return -1;
return
mrcal_num_measurements_boards(Nobservations_board,
calibration_object_width_n,
calibration_object_height_n) +
mrcal_num_measurements_points(Nobservations_point) +
mrcal_num_measurements_points_triangulated_initial_Npoints(observations_point_triangulated,
Nobservations_point_triangulated,
i_point_triangulated);
}
#warning "triangulated-solve: python-wrap this function"
int mrcal_num_measurements_points_triangulated_initial_Npoints(// May be NULL if we don't have any of these
const mrcal_observation_point_triangulated_t* observations_point_triangulated,
int Nobservations_point_triangulated,
// Only consider the leading Npoints. If Npoints < 0: take ALL the points
int Npoints)
{
if(observations_point_triangulated == NULL ||
Nobservations_point_triangulated <= 0)
return 0;
// Similar loop as in _mrcal_num_j_nonzero(). If the data layout changes,
// update this and that
int Nmeas = 0;
int ipoint = 0;
int iobservation = 0;
while( iobservation < Nobservations_point_triangulated &&
(Npoints < 0 || ipoint < Npoints))
{
int Nset = 1;
while(!observations_point_triangulated[iobservation].last_in_set)
{
Nmeas += Nset++;
iobservation++;
}
ipoint++;
iobservation++;
}
return Nmeas;
}
int mrcal_num_measurements_points_triangulated(// May be NULL if we don't have any of these
const mrcal_observation_point_triangulated_t* observations_point_triangulated,
int Nobservations_point_triangulated)
{
return
mrcal_num_measurements_points_triangulated_initial_Npoints( observations_point_triangulated,
Nobservations_point_triangulated,
-1 );
}
#warning "triangulated-solve: python-wrap this function"
bool mrcal_decode_observation_indices_points_triangulated(
// output
int* iobservation0,
int* iobservation1,
int* iobservation_point0,
int* Nobservations_this_point,
int* Nmeasurements_this_point,
int* ipoint,
// input
const int imeasurement,
const mrcal_observation_point_triangulated_t* observations_point_triangulated,
int Nobservations_point_triangulated)
{
if(observations_point_triangulated == NULL ||
Nobservations_point_triangulated <= 0)
return false;
// Similar loop as in
// mrcal_num_measurements_points_triangulated_initial_Npoints(). If the data
// layout changes, update this and that
int Nmeas = 0;
int iobservation = 0;
*ipoint = 0;
while( iobservation < Nobservations_point_triangulated )
{
int Nset = 1;
while(!observations_point_triangulated[iobservation].last_in_set)
{
Nset++;
iobservation++;
}
// This point has Nset observations. Each pair of observations produces
// a measurement, so:
const int Nmeas_thispoint = Nset*(Nset-1) / 2;
// Done with this point. It is described by Nmeas_thispoint
// measurements, with the first one at Nmeas. The last observation is at
// iobservation
if(imeasurement < Nmeas+Nmeas_thispoint)
{
// The measurement I care about observes THIS point. I find the
// specific observations.
//
// I simplify the notation: "m" is "imeasurement", "o" is
// "iobservation".
const int No = Nset;
const int Nm = Nmeas_thispoint;
const int m = imeasurement - Nmeas;
// Within this point o is in range(No) and m is in range(Nm). A pair
// (o0,o1) describes one measurement. Both o0 and o1 are in
// range(No) and o1>o0. A sample table of measurement indices m for
// No = 5:
//
// o1
// 0 1 2 3 4
// ---------
// 0| 0 1 2 3
// o0 1| 4 5 6
// 2| 7 8
// 3| 9
// 4|
//
// For a given o0, the maximum m =
//
// m_max = (No-1) + (No-2) + (No-3) ... - 1
//
// for a total of o0+1 (No...) terms so
//
// m_max = ((No-1) + (No-o0-1))/2 * (o0+1) - 1
// = (2*No - 2 - o0)/2 * (o0+1) - 1
//
// m_min = m_max(o0-1) + 1
// = (2*No - 2 - o0 + 1)/2 * o0
// = (2*No - 1 - o0) * o0 / 2
// = (-o0^2 + (2*No - 1)*o0 ) / 2
//
// -> (-1/2) o0^2 + (2*No - 1)/2 o0 - m_min = 0
// -> o0 = (2*No - 1)/2 +- sqrt( (2*No - 1)^2/4 - 2*m_min)
// = (2*No - 1)/2 - sqrt( (2*No - 1)^2/4 - 2*m_min)
// = (2*No - 1 - sqrt( (2*No - 1)^2 - 8*m_min))/2
//
// o0(m) = floor(o0(m))
//
// Now that I have o0 I compute
//
// o1 = m - m_min(o0) + o0 + 1
// = m - (-o0^2 + (2*No - 1)*o0 ) / 2 + o0 + 1
// = m + (o0^2 + (3- 2*No)*o0 + 2) / 2
// = m + o0*(o0 + 3 - 2*No)/2 + 1
const double x = 2.*(double)No - 1.;
*iobservation0 = (int)((x - sqrt( x*x - 8.*(double)m))/2.);
*iobservation1 = m + (*iobservation0)*((*iobservation0) + 3 - 2*No)/2 + 1;
// Reference the observations from the first
*iobservation_point0 = iobservation-Nset+1;
*iobservation0 += *iobservation_point0;
*iobservation1 += *iobservation_point0;
*Nobservations_this_point = No;
*Nmeasurements_this_point = Nm;
return true;
}
Nmeas += Nmeas_thispoint;
iobservation++;
(*ipoint)++;
}
return false;
}
int mrcal_measurement_index_regularization(
#warning "triangulated-solve: this argument order is weird. Put then triangulated stuff at the end?"
// May be NULL if we don't have any of these
const mrcal_observation_point_triangulated_t* observations_point_triangulated,
int Nobservations_point_triangulated,
int calibration_object_width_n,
int calibration_object_height_n,
int Ncameras_intrinsics, int Ncameras_extrinsics,
int Nframes,
int Npoints, int Npoints_fixed, int Nobservations_board, int Nobservations_point,
mrcal_problem_selections_t problem_selections,
const mrcal_lensmodel_t* lensmodel)
{
if(mrcal_num_measurements_regularization(Ncameras_intrinsics, Ncameras_extrinsics,
Nframes,
Npoints, Npoints_fixed, Nobservations_board,
problem_selections,
lensmodel) <= 0)
return -1;
return
mrcal_num_measurements_boards(Nobservations_board,
calibration_object_width_n,
calibration_object_height_n) +
mrcal_num_measurements_points(Nobservations_point) +
mrcal_num_measurements_points_triangulated(observations_point_triangulated,
Nobservations_point_triangulated);
}
int mrcal_num_measurements_regularization(int Ncameras_intrinsics, int Ncameras_extrinsics,
int Nframes,
int Npoints, int Npoints_fixed, int Nobservations_board,
mrcal_problem_selections_t problem_selections,
const mrcal_lensmodel_t* lensmodel)
{
return
Ncameras_intrinsics *
num_regularization_terms_percamera(problem_selections, lensmodel) +
((problem_selections.do_apply_regularization_unity_cam01 &&
problem_selections.do_optimize_extrinsics &&
Ncameras_extrinsics > 0) ? 1 : 0);
}
int mrcal_num_measurements(int Nobservations_board,
int Nobservations_point,
// May be NULL if we don't have any of these
const mrcal_observation_point_triangulated_t* observations_point_triangulated,
int Nobservations_point_triangulated,
int calibration_object_width_n,
int calibration_object_height_n,
int Ncameras_intrinsics, int Ncameras_extrinsics,
int Nframes,
int Npoints, int Npoints_fixed,
mrcal_problem_selections_t problem_selections,
const mrcal_lensmodel_t* lensmodel)
{
return
mrcal_num_measurements_boards( Nobservations_board,
calibration_object_width_n,
calibration_object_height_n) +
mrcal_num_measurements_points(Nobservations_point) +
mrcal_num_measurements_points_triangulated(observations_point_triangulated,
Nobservations_point_triangulated) +
mrcal_num_measurements_regularization(Ncameras_intrinsics, Ncameras_extrinsics,
Nframes,
Npoints, Npoints_fixed, Nobservations_board,
problem_selections,
lensmodel);
}
static bool has_calobject_warp(mrcal_problem_selections_t problem_selections,
int Nobservations_board)
{
return problem_selections.do_optimize_calobject_warp && Nobservations_board>0;
}
int _mrcal_num_j_nonzero(int Nobservations_board,
int Nobservations_point,
// May be NULL if we don't have any of these
const mrcal_observation_point_triangulated_t* observations_point_triangulated,
int Nobservations_point_triangulated,
int calibration_object_width_n,
int calibration_object_height_n,
int Ncameras_intrinsics, int Ncameras_extrinsics,
int Nframes,
int Npoints, int Npoints_fixed,
const mrcal_observation_board_t* observations_board,
const mrcal_observation_point_t* observations_point,
mrcal_problem_selections_t problem_selections,
const mrcal_lensmodel_t* lensmodel)
{
// each observation depends on all the parameters for THAT frame and for
// THAT camera. Camera0 doesn't have extrinsics, so I need to loop through
// all my observations
// Each projected point has an x and y measurement, and each one depends on
// some number of the intrinsic parameters. Parametric models are simple:
// each one depends on ALL of the intrinsics. Splined models are sparse,
// however, and there's only a partial dependence
int Nintrinsics_per_measurement;
if(lensmodel->type == MRCAL_LENSMODEL_SPLINED_STEREOGRAPHIC)
{
int run_len =
lensmodel->LENSMODEL_SPLINED_STEREOGRAPHIC__config.order + 1;
Nintrinsics_per_measurement =
(problem_selections.do_optimize_intrinsics_core ? 4 : 0) +
(problem_selections.do_optimize_intrinsics_distortions ? (run_len*run_len) : 0);
}
else
Nintrinsics_per_measurement =
mrcal_num_intrinsics_optimization_params(problem_selections, lensmodel);
// x depends on fx,cx but NOT on fy, cy. And similarly for y.
if( problem_selections.do_optimize_intrinsics_core &&
modelHasCore_fxfycxcy(lensmodel) )
Nintrinsics_per_measurement -= 2;
int N = Nobservations_board * ( (problem_selections.do_optimize_frames ? 6 : 0) +
(problem_selections.do_optimize_extrinsics ? 6 : 0) +
(has_calobject_warp(problem_selections,Nobservations_board) ? MRCAL_NSTATE_CALOBJECT_WARP : 0) +
Nintrinsics_per_measurement );
// initial estimate counts extrinsics for the reference camera, which need
// to be subtracted off
if(problem_selections.do_optimize_extrinsics)
for(int i=0; i<Nobservations_board; i++)
if(observations_board[i].icam.extrinsics < 0)
N -= 6;
// *2 because I have separate x and y measurements
N *= 2*calibration_object_width_n*calibration_object_height_n;
// Now the point observations
for(int i=0; i<Nobservations_point; i++)
{
N += 2*Nintrinsics_per_measurement;
if( problem_selections.do_optimize_frames &&
observations_point[i].i_point < Npoints-Npoints_fixed )
N += 2*3;
if( problem_selections.do_optimize_extrinsics &&
observations_point[i].icam.extrinsics >= 0 )
N += 2*6;
}
// And the triangulated point observations
if(observations_point_triangulated != NULL &&
Nobservations_point_triangulated > 0)
{
// Similar loop as in
// mrcal_num_measurements_points_triangulated_initial_Npoints(). If the
// data layout changes, update this and that
for(int i0=0; i0<Nobservations_point_triangulated; i0++)
{
if(observations_point_triangulated[i0].last_in_set)
continue;
int Nvars0 = Nintrinsics_per_measurement;
if( problem_selections.do_optimize_extrinsics &&
observations_point_triangulated[i0].icam.extrinsics >= 0 )
Nvars0 += 6;
int i1 = i0;
do
{
i1++;
int Nvars1 = Nintrinsics_per_measurement;
if( problem_selections.do_optimize_extrinsics &&
observations_point_triangulated[i1].icam.extrinsics >= 0 )
Nvars1 += 6;
N += Nvars0 + Nvars1;
} while(!observations_point_triangulated[i1].last_in_set);
}
}
// Regularization
if(lensmodel->type == MRCAL_LENSMODEL_SPLINED_STEREOGRAPHIC)
{
if(problem_selections.do_apply_regularization)
{
// Each regularization term depends on
// - two values for distortions
// - one value for the center pixel
N +=
Ncameras_intrinsics *
2 *
num_regularization_terms_percamera(problem_selections,
lensmodel);
// I multiplied by 2, so I double-counted the center pixel
// contributions. Subtract those off
if(problem_selections.do_optimize_intrinsics_core)
N -= Ncameras_intrinsics*2;
}
}
else
N +=
Ncameras_intrinsics *
num_regularization_terms_percamera(problem_selections,
lensmodel);
if(problem_selections.do_apply_regularization_unity_cam01 &&
problem_selections.do_optimize_extrinsics &&
Ncameras_extrinsics > 0)
{
#warning "triangulated-solve: I assume that camera0 is at the reference"
N += 3; // translation only
}
return N;
}
// Used in the spline-based projection function.
//
// See bsplines.py for the derivation of the spline expressions and for
// justification of the 2D scheme
//
// Here we sample two interpolated surfaces at once: one each for the x and y
// focal-length scales
//
// The sampling function assumes evenly spaced knots.
// a,b,c,d are sequential control points
// x is in [0,1] between b and c. Function looks like this:
// double A = fA(x);
// double B = fB(x);
// double C = fC(x);
// double D = fD(x);
// return A*a + B*b + C*c + D*d;
// I need to sample many such 1D segments, so I compute A,B,C,D separately,
// and apply them together
static
void get_sample_coeffs__cubic(double* ABCD, double* ABCDgrad, double x)
{
double x2 = x*x;
double x3 = x2*x;
ABCD[0] = (-x3 + 3*x2 - 3*x + 1)/6;
ABCD[1] = (3 * x3/2 - 3*x2 + 2)/3;
ABCD[2] = (-3 * x3 + 3*x2 + 3*x + 1)/6;
ABCD[3] = x3 / 6;
ABCDgrad[0] = -x2/2 + x - 1./2.;
ABCDgrad[1] = 3*x2/2 - 2*x;
ABCDgrad[2] = -3*x2/2 + x + 1./2.;
ABCDgrad[3] = x2 / 2;
}
static
void interp__cubic(double* out, const double* ABCDx, const double* ABCDy,
// control points
const double* c,
int stridey)
{
double cinterp[4][2];
const int stridex = 2;
for(int iy=0; iy<4; iy++)
for(int k=0;k<2;k++)
cinterp[iy][k] =
ABCDx[0] * c[iy*stridey + 0*stridex + k] +
ABCDx[1] * c[iy*stridey + 1*stridex + k] +
ABCDx[2] * c[iy*stridey + 2*stridex + k] +
ABCDx[3] * c[iy*stridey + 3*stridex + k];
for(int k=0;k<2;k++)
out[k] =
ABCDy[0] * cinterp[0][k] +
ABCDy[1] * cinterp[1][k] +
ABCDy[2] * cinterp[2][k] +
ABCDy[3] * cinterp[3][k];
}
static
void sample_bspline_surface_cubic(double* out,
double* dout_dx,
double* dout_dy,
double* ABCDx_ABCDy,
double x, double y,
// control points
const double* c,
int stridey
// stridex is 2: the control points from the
// two surfaces are next to each other. Better
// cache locality maybe
)
{
double* ABCDx = &ABCDx_ABCDy[0];
double* ABCDy = &ABCDx_ABCDy[4];
// 4 samples along one dimension, and then one sample along the other
// dimension, using the 4 samples as the control points. Order doesn't
// matter. See bsplines.py
//
// I do this twice: one for each focal length surface
double ABCDgradx[4];
double ABCDgrady[4];
get_sample_coeffs__cubic(ABCDx, ABCDgradx, x);
get_sample_coeffs__cubic(ABCDy, ABCDgrady, y);
// the intrinsics gradient is flatten(ABCDx[0..3] * ABCDy[0..3]) for both x
// and y. By returning ABCD[xy] and not the cartesian products, I make
// smaller temporary data arrays
interp__cubic(out, ABCDx, ABCDy, c, stridey);
interp__cubic(dout_dx, ABCDgradx, ABCDy, c, stridey);
interp__cubic(dout_dy, ABCDx, ABCDgrady, c, stridey);
}
// The sampling function assumes evenly spaced knots.
// a,b,c are sequential control points
// x is in [-1/2,1/2] around b. Function looks like this:
// double A = fA(x);
// double B = fB(x);
// double C = fC(x);
// return A*a + B*b + C*c;
// I need to sample many such 1D segments, so I compute A,B,C separately,
// and apply them together
static
void get_sample_coeffs__quadratic(double* ABC, double* ABCgrad, double x)
{
double x2 = x*x;
ABC[0] = (4*x2 - 4*x + 1)/8;
ABC[1] = (3 - 4*x2)/4;
ABC[2] = (4*x2 + 4*x + 1)/8;
ABCgrad[0] = x - 1./2.;
ABCgrad[1] = -2.*x;
ABCgrad[2] = x + 1./2.;
}
static
void interp__quadratic(double* out, const double* ABCx, const double* ABCy,
// control points
const double* c,
int stridey)
{
double cinterp[3][2];
const int stridex = 2;
for(int iy=0; iy<3; iy++)
for(int k=0;k<2;k++)
cinterp[iy][k] =
ABCx[0] * c[iy*stridey + 0*stridex + k] +
ABCx[1] * c[iy*stridey + 1*stridex + k] +
ABCx[2] * c[iy*stridey + 2*stridex + k];
for(int k=0;k<2;k++)
out[k] =
ABCy[0] * cinterp[0][k] +