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