220 lines
8.4 KiB
C++
220 lines
8.4 KiB
C++
|
// Ceres Solver - A fast non-linear least squares minimizer
|
||
|
|
// Copyright 2015 Google Inc. All rights reserved.
|
||
|
|
// http://ceres-solver.org/
|
||
|
|
//
|
||
|
|
// Redistribution and use in source and binary forms, with or without
|
||
|
|
// modification, are permitted provided that the following conditions are met:
|
||
|
|
//
|
||
|
|
// * Redistributions of source code must retain the above copyright notice,
|
||
|
|
// this list of conditions and the following disclaimer.
|
||
|
|
// * Redistributions in binary form must reproduce the above copyright notice,
|
||
|
|
// this list of conditions and the following disclaimer in the documentation
|
||
|
|
// and/or other materials provided with the distribution.
|
||
|
|
// * Neither the name of Google Inc. nor the names of its contributors may be
|
||
|
|
// used to endorse or promote products derived from this software without
|
||
|
|
// specific prior written permission.
|
||
|
|
//
|
||
|
|
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
||
|
|
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
||
|
|
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
|
||
|
|
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
|
||
|
|
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
||
|
|
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
||
|
|
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
||
|
|
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
||
|
|
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
||
|
|
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
||
|
|
// POSSIBILITY OF SUCH DAMAGE.
|
||
|
|
//
|
||
|
|
// Author: keir@google.com (Keir Mierle)
|
||
|
|
// sameeragarwal@google.com (Sameer Agarwal)
|
||
|
|
|
||
|
|
#include "ceres/residual_block.h"
|
||
|
|
|
||
|
|
#include <algorithm>
|
||
|
|
#include <cstddef>
|
||
|
|
#include <vector>
|
||
|
|
#include "ceres/corrector.h"
|
||
|
|
#include "ceres/parameter_block.h"
|
||
|
|
#include "ceres/residual_block_utils.h"
|
||
|
|
#include "ceres/cost_function.h"
|
||
|
|
#include "ceres/internal/eigen.h"
|
||
|
|
#include "ceres/internal/fixed_array.h"
|
||
|
|
#include "ceres/local_parameterization.h"
|
||
|
|
#include "ceres/loss_function.h"
|
||
|
|
#include "ceres/small_blas.h"
|
||
|
|
|
||
|
|
using Eigen::Dynamic;
|
||
|
|
|
||
|
|
namespace ceres {
|
||
|
|
namespace internal {
|
||
|
|
|
||
|
|
ResidualBlock::ResidualBlock(
|
||
|
|
const CostFunction* cost_function,
|
||
|
|
const LossFunction* loss_function,
|
||
|
|
const std::vector<ParameterBlock*>& parameter_blocks,
|
||
|
|
int index)
|
||
|
|
: cost_function_(cost_function),
|
||
|
|
loss_function_(loss_function),
|
||
|
|
parameter_blocks_(
|
||
|
|
new ParameterBlock* [
|
||
|
|
cost_function->parameter_block_sizes().size()]),
|
||
|
|
index_(index) {
|
||
|
|
std::copy(parameter_blocks.begin(),
|
||
|
|
parameter_blocks.end(),
|
||
|
|
parameter_blocks_.get());
|
||
|
|
}
|
||
|
|
|
||
|
|
bool ResidualBlock::Evaluate(const bool apply_loss_function,
|
||
|
|
double* cost,
|
||
|
|
double* residuals,
|
||
|
|
double** jacobians,
|
||
|
|
double* scratch) const {
|
||
|
|
const int num_parameter_blocks = NumParameterBlocks();
|
||
|
|
const int num_residuals = cost_function_->num_residuals();
|
||
|
|
|
||
|
|
// Collect the parameters from their blocks. This will rarely allocate, since
|
||
|
|
// residuals taking more than 8 parameter block arguments are rare.
|
||
|
|
FixedArray<const double*, 8> parameters(num_parameter_blocks);
|
||
|
|
for (int i = 0; i < num_parameter_blocks; ++i) {
|
||
|
|
parameters[i] = parameter_blocks_[i]->state();
|
||
|
|
}
|
||
|
|
|
||
|
|
// Put pointers into the scratch space into global_jacobians as appropriate.
|
||
|
|
FixedArray<double*, 8> global_jacobians(num_parameter_blocks);
|
||
|
|
if (jacobians != NULL) {
|
||
|
|
for (int i = 0; i < num_parameter_blocks; ++i) {
|
||
|
|
const ParameterBlock* parameter_block = parameter_blocks_[i];
|
||
|
|
if (jacobians[i] != NULL &&
|
||
|
|
parameter_block->LocalParameterizationJacobian() != NULL) {
|
||
|
|
global_jacobians[i] = scratch;
|
||
|
|
scratch += num_residuals * parameter_block->Size();
|
||
|
|
} else {
|
||
|
|
global_jacobians[i] = jacobians[i];
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
// If the caller didn't request residuals, use the scratch space for them.
|
||
|
|
bool outputting_residuals = (residuals != NULL);
|
||
|
|
if (!outputting_residuals) {
|
||
|
|
residuals = scratch;
|
||
|
|
}
|
||
|
|
|
||
|
|
// Invalidate the evaluation buffers so that we can check them after
|
||
|
|
// the CostFunction::Evaluate call, to see if all the return values
|
||
|
|
// that were required were written to and that they are finite.
|
||
|
|
double** eval_jacobians = (jacobians != NULL) ? global_jacobians.get() : NULL;
|
||
|
|
|
||
|
|
InvalidateEvaluation(*this, cost, residuals, eval_jacobians);
|
||
|
|
|
||
|
|
if (!cost_function_->Evaluate(parameters.get(), residuals, eval_jacobians)) {
|
||
|
|
return false;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (!IsEvaluationValid(*this,
|
||
|
|
parameters.get(),
|
||
|
|
cost,
|
||
|
|
residuals,
|
||
|
|
eval_jacobians)) {
|
||
|
|
std::string message =
|
||
|
|
"\n\n"
|
||
|
|
"Error in evaluating the ResidualBlock.\n\n"
|
||
|
|
"There are two possible reasons. Either the CostFunction did not evaluate and fill all \n" // NOLINT
|
||
|
|
"residual and jacobians that were requested or there was a non-finite value (nan/infinite)\n" // NOLINT
|
||
|
|
"generated during the or jacobian computation. \n\n" +
|
||
|
|
EvaluationToString(*this,
|
||
|
|
parameters.get(),
|
||
|
|
cost,
|
||
|
|
residuals,
|
||
|
|
eval_jacobians);
|
||
|
|
LOG(WARNING) << message;
|
||
|
|
return false;
|
||
|
|
}
|
||
|
|
|
||
|
|
double squared_norm = VectorRef(residuals, num_residuals).squaredNorm();
|
||
|
|
|
||
|
|
// Update the jacobians with the local parameterizations.
|
||
|
|
if (jacobians != NULL) {
|
||
|
|
for (int i = 0; i < num_parameter_blocks; ++i) {
|
||
|
|
if (jacobians[i] != NULL) {
|
||
|
|
const ParameterBlock* parameter_block = parameter_blocks_[i];
|
||
|
|
|
||
|
|
// Apply local reparameterization to the jacobians.
|
||
|
|
if (parameter_block->LocalParameterizationJacobian() != NULL) {
|
||
|
|
// jacobians[i] = global_jacobians[i] * global_to_local_jacobian.
|
||
|
|
MatrixMatrixMultiply<Dynamic, Dynamic, Dynamic, Dynamic, 0>(
|
||
|
|
global_jacobians[i],
|
||
|
|
num_residuals,
|
||
|
|
parameter_block->Size(),
|
||
|
|
parameter_block->LocalParameterizationJacobian(),
|
||
|
|
parameter_block->Size(),
|
||
|
|
parameter_block->LocalSize(),
|
||
|
|
jacobians[i], 0, 0, num_residuals, parameter_block->LocalSize());
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (loss_function_ == NULL || !apply_loss_function) {
|
||
|
|
*cost = 0.5 * squared_norm;
|
||
|
|
return true;
|
||
|
|
}
|
||
|
|
|
||
|
|
double rho[3];
|
||
|
|
loss_function_->Evaluate(squared_norm, rho);
|
||
|
|
*cost = 0.5 * rho[0];
|
||
|
|
|
||
|
|
// No jacobians and not outputting residuals? All done. Doing an early exit
|
||
|
|
// here avoids constructing the "Corrector" object below in a common case.
|
||
|
|
if (jacobians == NULL && !outputting_residuals) {
|
||
|
|
return true;
|
||
|
|
}
|
||
|
|
|
||
|
|
// Correct for the effects of the loss function. The jacobians need to be
|
||
|
|
// corrected before the residuals, since they use the uncorrected residuals.
|
||
|
|
Corrector correct(squared_norm, rho);
|
||
|
|
if (jacobians != NULL) {
|
||
|
|
for (int i = 0; i < num_parameter_blocks; ++i) {
|
||
|
|
if (jacobians[i] != NULL) {
|
||
|
|
const ParameterBlock* parameter_block = parameter_blocks_[i];
|
||
|
|
|
||
|
|
// Correct the jacobians for the loss function.
|
||
|
|
correct.CorrectJacobian(num_residuals,
|
||
|
|
parameter_block->LocalSize(),
|
||
|
|
residuals,
|
||
|
|
jacobians[i]);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
// Correct the residuals with the loss function.
|
||
|
|
if (outputting_residuals) {
|
||
|
|
correct.CorrectResiduals(num_residuals, residuals);
|
||
|
|
}
|
||
|
|
return true;
|
||
|
|
}
|
||
|
|
|
||
|
|
int ResidualBlock::NumScratchDoublesForEvaluate() const {
|
||
|
|
// Compute the amount of scratch space needed to store the full-sized
|
||
|
|
// jacobians. For parameters that have no local parameterization no storage
|
||
|
|
// is needed and the passed-in jacobian array is used directly. Also include
|
||
|
|
// space to store the residuals, which is needed for cost-only evaluations.
|
||
|
|
// This is slightly pessimistic, since both won't be needed all the time, but
|
||
|
|
// the amount of excess should not cause problems for the caller.
|
||
|
|
int num_parameters = NumParameterBlocks();
|
||
|
|
int scratch_doubles = 1;
|
||
|
|
for (int i = 0; i < num_parameters; ++i) {
|
||
|
|
const ParameterBlock* parameter_block = parameter_blocks_[i];
|
||
|
|
if (!parameter_block->IsConstant() &&
|
||
|
|
parameter_block->LocalParameterizationJacobian() != NULL) {
|
||
|
|
scratch_doubles += parameter_block->Size();
|
||
|
|
}
|
||
|
|
}
|
||
|
|
scratch_doubles *= NumResiduals();
|
||
|
|
return scratch_doubles;
|
||
|
|
}
|
||
|
|
|
||
|
|
} // namespace internal
|
||
|
|
} // namespace ceres
|