| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2019 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: | |
| // | |
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| // * 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. | |
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| // specific prior written permission. | |
| // | |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
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| // POSSIBILITY OF SUCH DAMAGE. | |
| // | |
| // Author: sameeragarwal@google.com (Sameer Agarwal) | |
| // | |
| // CostFunctionToFunctor is an adapter class that allows users to use | |
| // SizedCostFunction objects in templated functors which are to be used for | |
| // automatic differentiation. This allows the user to seamlessly mix | |
| // analytic, numeric and automatic differentiation. | |
| // | |
| // For example, let us assume that | |
| // | |
| // class IntrinsicProjection : public SizedCostFunction<2, 5, 3> { | |
| // public: | |
| // IntrinsicProjection(const double* observation); | |
| // bool Evaluate(double const* const* parameters, | |
| // double* residuals, | |
| // double** jacobians) const override; | |
| // }; | |
| // | |
| // is a cost function that implements the projection of a point in its | |
| // local coordinate system onto its image plane and subtracts it from | |
| // the observed point projection. It can compute its residual and | |
| // jacobians either via analytic or numerical differentiation. | |
| // | |
| // Now we would like to compose the action of this CostFunction with | |
| // the action of camera extrinsics, i.e., rotation and | |
| // translation. Say we have a templated function | |
| // | |
| // template<typename T> | |
| // void RotateAndTranslatePoint(const T* rotation, | |
| // const T* translation, | |
| // const T* point, | |
| // T* result); | |
| // | |
| // Then we can now do the following, | |
| // | |
| // struct CameraProjection { | |
| // CameraProjection(const double* observation) | |
| // : intrinsic_projection_(new IntrinsicProjection(observation)) { | |
| // } | |
| // template <typename T> | |
| // bool operator()(const T* rotation, | |
| // const T* translation, | |
| // const T* intrinsics, | |
| // const T* point, | |
| // T* residual) const { | |
| // T transformed_point[3]; | |
| // RotateAndTranslatePoint(rotation, translation, point, transformed_point); | |
| // | |
| // // Note that we call intrinsic_projection_, just like it was | |
| // // any other templated functor. | |
| // | |
| // return intrinsic_projection_(intrinsics, transformed_point, residual); | |
| // } | |
| // | |
| // private: | |
| // CostFunctionToFunctor<2,5,3> intrinsic_projection_; | |
| // }; | |
| namespace ceres { | |
| template <int kNumResiduals, int... Ns> | |
| class CostFunctionToFunctor { | |
| public: | |
| // Takes ownership of cost_function. | |
| explicit CostFunctionToFunctor(CostFunction* cost_function) | |
| : cost_functor_(cost_function) { | |
| CHECK(cost_function != nullptr); | |
| CHECK(kNumResiduals > 0 || kNumResiduals == DYNAMIC); | |
| const std::vector<int32_t>& parameter_block_sizes = | |
| cost_function->parameter_block_sizes(); | |
| const int num_parameter_blocks = ParameterDims::kNumParameterBlocks; | |
| CHECK_EQ(static_cast<int>(parameter_block_sizes.size()), | |
| num_parameter_blocks); | |
| if (parameter_block_sizes.size() == num_parameter_blocks) { | |
| for (int block = 0; block < num_parameter_blocks; ++block) { | |
| CHECK_EQ(ParameterDims::GetDim(block), parameter_block_sizes[block]) | |
| << "Parameter block size missmatch. The specified static parameter " | |
| "block dimension does not match the one from the cost function."; | |
| } | |
| } | |
| CHECK_EQ(accumulate( | |
| parameter_block_sizes.begin(), parameter_block_sizes.end(), 0), | |
| ParameterDims::kNumParameters); | |
| } | |
| template <typename T, typename... Ts> | |
| bool operator()(const T* p1, Ts*... ps) const { | |
| // Add one because of residual block. | |
| static_assert(sizeof...(Ts) + 1 == ParameterDims::kNumParameterBlocks + 1, | |
| "Invalid number of parameter blocks specified."); | |
| auto params = std::make_tuple(p1, ps...); | |
| // Extract residual pointer from params. The residual pointer is the | |
| // last pointer. | |
| constexpr int kResidualIndex = ParameterDims::kNumParameterBlocks; | |
| T* residuals = std::get<kResidualIndex>(params); | |
| // Extract parameter block pointers from params. | |
| using Indices = | |
| std::make_integer_sequence<int, ParameterDims::kNumParameterBlocks>; | |
| std::array<const T*, ParameterDims::kNumParameterBlocks> parameter_blocks = | |
| GetParameterPointers<T>(params, Indices()); | |
| return cost_functor_(parameter_blocks.data(), residuals); | |
| } | |
| private: | |
| using ParameterDims = internal::StaticParameterDims<Ns...>; | |
| template <typename T, typename Tuple, int... Indices> | |
| static std::array<const T*, ParameterDims::kNumParameterBlocks> | |
| GetParameterPointers(const Tuple& paramPointers, | |
| std::integer_sequence<int, Indices...>) { | |
| return std::array<const T*, ParameterDims::kNumParameterBlocks>{ | |
| {std::get<Indices>(paramPointers)...}}; | |
| } | |
| DynamicCostFunctionToFunctor cost_functor_; | |
| }; | |
| } // namespace ceres | |