pmlpp/convolutions/convolutions.h

103 lines
4.6 KiB
C++

#ifndef MLPP_CONVOLUTIONS_H
#define MLPP_CONVOLUTIONS_H
/*************************************************************************/
/* convolutions.h */
/*************************************************************************/
/* This file is part of: */
/* PMLPP Machine Learning Library */
/* https://github.com/Relintai/pmlpp */
/*************************************************************************/
/* Copyright (c) 2023-present Péter Magyar. */
/* Copyright (c) 2022-2023 Marc Melikyan */
/* */
/* Permission is hereby granted, free of charge, to any person obtaining */
/* a copy of this software and associated documentation files (the */
/* "Software"), to deal in the Software without restriction, including */
/* without limitation the rights to use, copy, modify, merge, publish, */
/* distribute, sublicense, and/or sell copies of the Software, and to */
/* permit persons to whom the Software is furnished to do so, subject to */
/* the following conditions: */
/* */
/* The above copyright notice and this permission notice shall be */
/* included in all copies or substantial portions of the Software. */
/* */
/* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, */
/* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF */
/* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.*/
/* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY */
/* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, */
/* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE */
/* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */
/*************************************************************************/
#include "core/containers/vector.h"
#include "core/string/ustring.h"
#include "core/math/math_defs.h"
#include "../lin_alg/mlpp_matrix.h"
#include "../lin_alg/mlpp_tensor3.h"
#include "../lin_alg/mlpp_vector.h"
#include "core/object/reference.h"
class MLPPConvolutions : public Reference {
GDCLASS(MLPPConvolutions, Reference);
public:
enum PoolType {
POOL_TYPE_AVERAGE = 0,
POOL_TYPE_MIN,
POOL_TYPE_MAX,
};
Ref<MLPPMatrix> convolve_2d(const Ref<MLPPMatrix> &input, const Ref<MLPPMatrix> &filter, const int S, const int P = 0);
Ref<MLPPTensor3> convolve_3d(const Ref<MLPPTensor3> &input, const Ref<MLPPTensor3> &filter, const int S, const int P = 0);
Ref<MLPPMatrix> pool_2d(const Ref<MLPPMatrix> &input, const int F, const int S, const PoolType type);
Ref<MLPPTensor3> pool_3d(const Ref<MLPPTensor3> &input, const int F, const int S, const PoolType type);
real_t global_pool_2d(const Ref<MLPPMatrix> &input, const PoolType type);
Ref<MLPPVector> global_pool_3d(const Ref<MLPPTensor3> &input, const PoolType type);
real_t gaussian_2d(const real_t x, const real_t y, const real_t std);
Ref<MLPPMatrix> gaussian_filter_2d(const int size, const real_t std);
Ref<MLPPMatrix> dx(const Ref<MLPPMatrix> &input);
Ref<MLPPMatrix> dy(const Ref<MLPPMatrix> &input);
Ref<MLPPMatrix> grad_magnitude(const Ref<MLPPMatrix> &input);
Ref<MLPPMatrix> grad_orientation(const Ref<MLPPMatrix> &input);
Ref<MLPPTensor3> compute_m(const Ref<MLPPMatrix> &input);
Vector<Ref<MLPPMatrix>> compute_mv(const Ref<MLPPMatrix> &input);
//TODO better data srtucture for this. Maybe IntMatrix?
Vector<Vector<CharType>> harris_corner_detection(const Ref<MLPPMatrix> &input);
Ref<MLPPMatrix> get_prewitt_horizontal() const;
Ref<MLPPMatrix> get_prewitt_vertical() const;
Ref<MLPPMatrix> get_sobel_horizontal() const;
Ref<MLPPMatrix> get_sobel_vertical() const;
Ref<MLPPMatrix> get_scharr_horizontal() const;
Ref<MLPPMatrix> get_scharr_vertical() const;
Ref<MLPPMatrix> get_roberts_horizontal() const;
Ref<MLPPMatrix> get_roberts_vertical() const;
MLPPConvolutions();
protected:
static void _bind_methods();
Ref<MLPPMatrix> _prewitt_horizontal;
Ref<MLPPMatrix> _prewitt_vertical;
Ref<MLPPMatrix> _sobel_horizontal;
Ref<MLPPMatrix> _sobel_vertical;
Ref<MLPPMatrix> _scharr_horizontal;
Ref<MLPPMatrix> _scharr_vertical;
Ref<MLPPMatrix> _roberts_horizontal;
Ref<MLPPMatrix> _roberts_vertical;
};
#endif // Convolutions_hpp