// 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: strandmark@google.com (Petter Strandmark) // // Class for loading the data required for descibing a Fields of Experts (FoE) // model. #include "fields_of_experts.h" #include #include #include "pgm_image.h" namespace ceres { namespace examples { FieldsOfExpertsCost::FieldsOfExpertsCost(const std::vector& filter) : filter_(filter) { set_num_residuals(1); for (int i = 0; i < filter_.size(); ++i) { mutable_parameter_block_sizes()->push_back(1); } } // This is a dot product between a the scalar parameters and a vector of filter // coefficients. bool FieldsOfExpertsCost::Evaluate(double const* const* parameters, double* residuals, double** jacobians) const { int num_variables = filter_.size(); residuals[0] = 0; for (int i = 0; i < num_variables; ++i) { residuals[0] += filter_[i] * parameters[i][0]; } if (jacobians != NULL) { for (int i = 0; i < num_variables; ++i) { if (jacobians[i] != NULL) { jacobians[i][0] = filter_[i]; } } } return true; } // This loss function builds the FoE terms and is equal to // // f(x) = alpha_i * log(1 + (1/2)s) // void FieldsOfExpertsLoss::Evaluate(double sq_norm, double rho[3]) const { const double c = 0.5; const double sum = 1.0 + sq_norm * c; const double inv = 1.0 / sum; // 'sum' and 'inv' are always positive, assuming that 's' is. rho[0] = alpha_ * log(sum); rho[1] = alpha_ * c * inv; rho[2] = - alpha_ * c * c * inv * inv; } FieldsOfExperts::FieldsOfExperts() : size_(0), num_filters_(0) { } bool FieldsOfExperts::LoadFromFile(const std::string& filename) { std::ifstream foe_file(filename.c_str()); foe_file >> size_; foe_file >> num_filters_; if (size_ < 0 || num_filters_ < 0) { return false; } const int num_variables = NumVariables(); x_delta_indices_.resize(num_variables); for (int i = 0; i < num_variables; ++i) { foe_file >> x_delta_indices_[i]; } y_delta_indices_.resize(NumVariables()); for (int i = 0; i < num_variables; ++i) { foe_file >> y_delta_indices_[i]; } alpha_.resize(num_filters_); for (int i = 0; i < num_filters_; ++i) { foe_file >> alpha_[i]; } filters_.resize(num_filters_); for (int i = 0; i < num_filters_; ++i) { filters_[i].resize(num_variables); for (int j = 0; j < num_variables; ++j) { foe_file >> filters_[i][j]; } } // If any read failed, return failure. if (!foe_file) { size_ = 0; return false; } // There cannot be anything else in the file. Try reading another number and // return failure if that succeeded. double temp; foe_file >> temp; if (foe_file) { size_ = 0; return false; } return true; } ceres::CostFunction* FieldsOfExperts::NewCostFunction(int alpha_index) const { return new FieldsOfExpertsCost(filters_[alpha_index]); } ceres::LossFunction* FieldsOfExperts::NewLossFunction(int alpha_index) const { return new FieldsOfExpertsLoss(alpha_[alpha_index]); } } // namespace examples } // namespace ceres