mirror of
https://github.com/Relintai/pmlpp.git
synced 2024-11-08 13:12:09 +01:00
83 lines
3.3 KiB
C++
83 lines
3.3 KiB
C++
/*************************************************************************/
|
|
/* transforms.cpp */
|
|
/*************************************************************************/
|
|
/* 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 "transforms.h"
|
|
#include "../lin_alg/lin_alg.h"
|
|
|
|
#include "core/math/math_funcs.h"
|
|
|
|
// DCT ii.
|
|
// https://www.mathworks.com/help/images/discrete-cosine-transform.html
|
|
Ref<MLPPMatrix> MLPPTransforms::discrete_cosine_transform(const Ref<MLPPMatrix> &p_A) {
|
|
Ref<MLPPMatrix> A = p_A->scalar_addn(-128); // Center around 0.
|
|
|
|
Size2i size = A->size();
|
|
|
|
Ref<MLPPMatrix> B;
|
|
B.instance();
|
|
B->resize(size);
|
|
|
|
real_t M = size.y;
|
|
real_t inv_sqrt_M = 1 / Math::sqrt(M);
|
|
real_t s2M = Math::sqrt(real_t(2) / real_t(M));
|
|
|
|
for (int i = 0; i < size.y; i++) {
|
|
for (int j = 0; j < size.x; j++) {
|
|
real_t sum = 0;
|
|
|
|
real_t alphaI;
|
|
if (i == 0) {
|
|
alphaI = inv_sqrt_M;
|
|
} else {
|
|
alphaI = s2M;
|
|
}
|
|
|
|
real_t alphaJ;
|
|
if (j == 0) {
|
|
alphaJ = inv_sqrt_M;
|
|
} else {
|
|
alphaJ = s2M;
|
|
}
|
|
|
|
for (int k = 0; k < size.y; k++) {
|
|
for (int f = 0; f < size.x; f++) {
|
|
sum += A->element_get(k, f) * Math::cos((Math_PI * i * (2 * k + 1)) / (2 * M)) * Math::cos((Math_PI * j * (2 * f + 1)) / (2 * M));
|
|
}
|
|
}
|
|
|
|
B->element_set(i, j, sum * alphaI * alphaJ);
|
|
}
|
|
}
|
|
return B;
|
|
}
|
|
|
|
void MLPPTransforms::_bind_methods() {
|
|
}
|