146 lines
5.4 KiB
C++
146 lines
5.4 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: strandmark@google.com (Petter Strandmark)
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//
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// Class for loading the data required for descibing a Fields of Experts (FoE)
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// model. The Fields of Experts regularization consists of terms of the type
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//
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// alpha * log(1 + (1/2)*sum(F .* X)^2),
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//
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// where F is a d-by-d image patch and alpha is a constant. This is implemented
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// by a FieldsOfExpertsSum object which represents the dot product between the
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// image patches and a FieldsOfExpertsLoss which implements the log(1 + (1/2)s)
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// part.
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//
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// [1] S. Roth and M.J. Black. "Fields of Experts." International Journal of
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// Computer Vision, 82(2):205--229, 2009.
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#ifndef CERES_EXAMPLES_FIELDS_OF_EXPERTS_H_
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#define CERES_EXAMPLES_FIELDS_OF_EXPERTS_H_
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#include <iostream>
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#include <vector>
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#include "ceres/loss_function.h"
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#include "ceres/cost_function.h"
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#include "ceres/sized_cost_function.h"
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#include "pgm_image.h"
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namespace ceres {
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namespace examples {
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// One sum in the FoE regularizer. This is a dot product between a filter and an
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// image patch. It simply calculates the dot product between the filter
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// coefficients given in the constructor and the scalar parameters passed to it.
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class FieldsOfExpertsCost : public ceres::CostFunction {
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public:
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explicit FieldsOfExpertsCost(const std::vector<double>& filter);
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// The number of scalar parameters passed to Evaluate must equal the number of
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// filter coefficients passed to the constructor.
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const;
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private:
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const std::vector<double>& filter_;
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};
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// The loss function used to build the correct regularization. See above.
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//
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// f(x) = alpha_i * log(1 + (1/2)s)
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//
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class FieldsOfExpertsLoss : public ceres::LossFunction {
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public:
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explicit FieldsOfExpertsLoss(double alpha) : alpha_(alpha) { }
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virtual void Evaluate(double, double*) const;
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private:
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const double alpha_;
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};
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// This class loads a set of filters and coefficients from file. Then the users
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// obtains the correct loss and cost functions through NewCostFunction and
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// NewLossFunction.
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class FieldsOfExperts {
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public:
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// Creates an empty object with size() == 0.
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FieldsOfExperts();
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// Attempts to load filters from a file. If unsuccessful it returns false and
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// sets size() == 0.
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bool LoadFromFile(const std::string& filename);
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// Side length of a square filter in this FoE. They are all of the same size.
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int Size() const {
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return size_;
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}
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// Total number of pixels the filter covers.
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int NumVariables() const {
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return size_ * size_;
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}
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// Number of filters used by the FoE.
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int NumFilters() const {
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return num_filters_;
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}
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// Creates a new cost function. The caller is responsible for deallocating the
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// memory. alpha_index specifies which filter is used in the cost function.
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ceres::CostFunction* NewCostFunction(int alpha_index) const;
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// Creates a new loss function. The caller is responsible for deallocating the
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// memory. alpha_index specifies which filter this loss function is for.
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ceres::LossFunction* NewLossFunction(int alpha_index) const;
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// Gets the delta pixel indices for all pixels in a patch.
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const std::vector<int>& GetXDeltaIndices() const {
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return x_delta_indices_;
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}
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const std::vector<int>& GetYDeltaIndices() const {
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return y_delta_indices_;
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}
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private:
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// The side length of a square filter.
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int size_;
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// The number of different filters used.
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int num_filters_;
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// Pixel offsets for all variables.
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std::vector<int> x_delta_indices_, y_delta_indices_;
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// The coefficients in front of each term.
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std::vector<double> alpha_;
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// The filters used for the dot product with image patches.
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std::vector<std::vector<double> > filters_;
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};
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} // namespace examples
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} // namespace ceres
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#endif // CERES_EXAMPLES_FIELDS_OF_EXPERTS_H_
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