| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2015 Google Inc. All rights reserved. |
| // http://ceres-solver.org/ |
| // |
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| // modification, are permitted provided that the following conditions are met: |
| // |
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| // this list of conditions and the following disclaimer. |
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| // specific prior written permission. |
| // |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
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| // |
| // Author: strandmark@google.com (Petter Strandmark) |
| // |
| // Class for loading the data required for describing a Fields of Experts (FoE) |
| // model. |
| |
| #include "fields_of_experts.h" |
| |
| #include <cmath> |
| #include <fstream> |
| |
| #include "pgm_image.h" |
| |
| namespace ceres::examples { |
| |
| FieldsOfExpertsCost::FieldsOfExpertsCost(const std::vector<double>& 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 != nullptr) { |
| for (int i = 0; i < num_variables; ++i) { |
| if (jacobians[i] != nullptr) { |
| 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 ceres::examples |