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image-gp-6
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image-gp-6/include/image_operations.h

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#pragma once
/*
* Copyright (C) 2024 Brett Terpstra
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
#include <blt/math/vectors.h>
#include <blt/gp/program.h>
#include <functional>
#include <helper.h>
#include <stb_perlin.h>
#include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp"
#ifndef IMAGE_GP_6_IMAGE_OPERATIONS_H
#define IMAGE_GP_6_IMAGE_OPERATIONS_H
inline blt::gp::operation_t add(make_double(std::plus()), "add");
inline blt::gp::operation_t sub(make_double(std::minus()), "sub");
inline blt::gp::operation_t mul(make_double(std::multiplies()), "mul");
inline blt::gp::operation_t pro_div([](const full_image_t& a, const full_image_t& b) {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
img.rgb_data[i] = b.rgb_data[i] == 0 ? 0 : (a.rgb_data[i] / b.rgb_data[i]);
return img;
}, "div");
inline blt::gp::operation_t op_sin(make_single([](float a) {
return (std::sin(a) + 1.0f) / 2.0f;
}), "sin");
inline blt::gp::operation_t op_cos(make_single([](float a) {
return (std::cos(a) + 1.0f) / 2.0f;
}), "cos");
inline blt::gp::operation_t op_atan(make_single((float (*)(float)) &std::atan), "atan");
inline blt::gp::operation_t op_exp(make_single((float (*)(float)) &std::exp), "exp");
inline blt::gp::operation_t op_abs(make_single((float (*)(float)) &std::abs), "abs");
inline blt::gp::operation_t op_log(make_single((float (*)(float)) &std::log), "log");
inline blt::gp::operation_t op_round(make_single([](float f) { return std::round(f * 255.0f) / 255.0f; }), "round");
inline blt::gp::operation_t op_v_mod([](const full_image_t& a, const full_image_t& b) {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
img.rgb_data[i] = b.rgb_data[i] <= 0 ? 0 : static_cast<float>(blt::mem::type_cast<unsigned int>(a.rgb_data[i]) %
blt::mem::type_cast<unsigned int>(b.rgb_data[i]));
return img;
}, "v_mod");
inline blt::gp::operation_t bitwise_and([](const full_image_t& a, const full_image_t& b) {
using blt::mem::type_cast;
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
img.rgb_data[i] = static_cast<float>(type_cast<unsigned int>(a.rgb_data[i]) & type_cast<unsigned int>(b.rgb_data[i]));
return img;
}, "and");
inline blt::gp::operation_t bitwise_or([](const full_image_t& a, const full_image_t& b) {
using blt::mem::type_cast;
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
img.rgb_data[i] = static_cast<float>(type_cast<unsigned int>(a.rgb_data[i]) | type_cast<unsigned int>(b.rgb_data[i]));
return img;
}, "or");
inline blt::gp::operation_t bitwise_invert([](const full_image_t& a) {
using blt::mem::type_cast;
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
img.rgb_data[i] = static_cast<float>(~type_cast<unsigned int>(a.rgb_data[i]));
return img;
}, "invert");
inline blt::gp::operation_t bitwise_xor([](const full_image_t& a, const full_image_t& b) {
using blt::mem::type_cast;
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
{
auto in_a = type_cast<unsigned int>(a.rgb_data[i]);
auto in_b = type_cast<unsigned int>(b.rgb_data[i]);
img.rgb_data[i] = static_cast<float>(in_a ^ in_b);
}
return img;
}, "xor");
inline blt::gp::operation_t dissolve([](const full_image_t& a, const full_image_t& b) {
using blt::mem::type_cast;
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
{
auto diff = (a.rgb_data[i] - b.rgb_data[i]) / 2.0f;
img.rgb_data[i] = a.rgb_data[i] + diff;
}
return img;
}, "dissolve");
//inline blt::gp::operation_t band_pass([](const full_image_t& a, blt::u64 lp, blt::u64 hp) {
inline blt::gp::operation_t band_pass([](const full_image_t& a, float fa, float fb, blt::u64 size) {
cv::Mat src(IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, const_cast<float*>(a.rgb_data));
full_image_t img{};
std::memcpy(img.rgb_data, a.rgb_data, DATA_CHANNELS_SIZE * sizeof(float));
cv::Mat dst{IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, img.rgb_data};
if (size % 2 == 0)
size++;
auto min = fa < fb ? fa : fb;
auto max = fa > fb ? fa : fb;
auto low = cv::getGaussianKernel(static_cast<int>(size), min * ((static_cast<int>(size) - 1) * 0.5 - 1) + 0.8, CV_32F);
auto high = cv::getGaussianKernel(static_cast<int>(size), max * ((static_cast<int>(size) - 1) * 0.5 - 1) + 0.8, CV_32F);
auto func = high - low;
cv::Mat funcY;
cv::transpose(func, funcY);
cv::sepFilter2D(src, dst, 3, func, funcY);
return img;
}, "band_pass");
inline blt::gp::operation_t high_pass([](const full_image_t& a, blt::u64 size) {
full_image_t blur{};
full_image_t base{};
full_image_t ret{};
std::memcpy(blur.rgb_data, a.rgb_data, DATA_CHANNELS_SIZE * sizeof(float));
std::memcpy(base.rgb_data, a.rgb_data, DATA_CHANNELS_SIZE * sizeof(float));
cv::Mat blur_mat{IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, blur.rgb_data};
cv::Mat base_mat{IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, base.rgb_data};
cv::Mat ret_mat{IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, ret.rgb_data};
if (size % 2 == 0)
size++;
for (blt::u64 i = 1; i < size; i += 2)
cv::GaussianBlur(blur_mat, blur_mat, cv::Size(static_cast<int>(i), static_cast<int>(i)), 0, 0);
const static cv::Mat half{IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, 0.5f};
cv::subtract(base_mat, blur_mat, ret_mat);
cv::add(ret_mat, half, ret_mat);
return ret;
}, "high_pass");
inline blt::gp::operation_t gaussian_blur([](const full_image_t& a, blt::u64 size) {
full_image_t img{};
std::memcpy(img.rgb_data, a.rgb_data, DATA_CHANNELS_SIZE * sizeof(float));
cv::Mat dst{IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, img.rgb_data};
if (size % 2 == 0)
size++;
for (blt::u64 i = 1; i < size; i += 2)
cv::GaussianBlur(dst, dst, cv::Size(static_cast<int>(i), static_cast<int>(i)), 0, 0);
return img;
}, "gaussian_blur");
inline blt::gp::operation_t median_blur([](const full_image_t& a, blt::u64 size) {
cv::Mat src(IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, const_cast<float*>(a.rgb_data));
full_image_t img{};
cv::Mat dst{IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, img.rgb_data};
if (size % 2 == 0)
size++;
if (size > 5)
size = 5;
cv::medianBlur(src, dst, static_cast<int>(size));
return img;
}, "median_blur");
inline blt::gp::operation_t bilateral_filter([](const full_image_t& a, blt::u64 size, float color, float space) {
full_image_t img{};
cv::Mat src(IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, const_cast<float*>(a.rgb_data));
cv::Mat dst{IMAGE_SIZE, IMAGE_SIZE, CV_32FC3, img.rgb_data};
if (size % 2 == 0)
size++;
cv::bilateralFilter(src, dst, static_cast<int>(size), color * static_cast<double>(size) * 2.0, space * static_cast<double>(size) * 2.0);
return img;
}, "bilateral_filter");
inline blt::gp::operation_t hsv_to_rgb([](const full_image_t& a) {
using blt::mem::type_cast;
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto h = static_cast<blt::i32>(a.rgb_data[i * CHANNELS + 0]) % 360;
auto s = a.rgb_data[i * CHANNELS + 1];
auto v = a.rgb_data[i * CHANNELS + 2];
auto c = v * s;
auto x = c * static_cast<float>(1 - std::abs(((h / 60) % 2) - 1));
auto m = v - c;
blt::vec3 rgb;
if (h >= 0 && h < 60)
rgb = {c, x, 0.0f};
else if (h >= 60 && h < 120)
rgb = {x, c, 0.0f};
else if (h >= 120 && h < 180)
rgb = {0.0f, c, x};
else if (h >= 180 && h < 240)
rgb = {0.0f, x, c};
else if (h >= 240 && h < 300)
rgb = {x, 0.0f, c};
else if (h >= 300 && h < 360)
rgb = {c, 0.0f, x};
img.rgb_data[i * CHANNELS] = rgb.x() + m;
img.rgb_data[i * CHANNELS + 1] = rgb.y() + m;
img.rgb_data[i * CHANNELS + 2] = rgb.z() + m;
}
return img;
}, "hsv");
inline blt::gp::operation_t lit([]() {
full_image_t img{};
auto bw = program.get_random().get_float(0.0f, 1.0f);
for (auto& i : img.rgb_data)
i = bw;
return img;
}, "lit");
inline blt::gp::operation_t vec([]() {
full_image_t img{};
auto r = program.get_random().get_float(0.0f, 1.0f);
auto g = program.get_random().get_float(0.0f, 1.0f);
auto b = program.get_random().get_float(0.0f, 1.0f);
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
img.rgb_data[i * CHANNELS] = r;
img.rgb_data[i * CHANNELS + 1] = g;
img.rgb_data[i * CHANNELS + 2] = b;
}
return img;
}, "vec");
inline blt::gp::operation_t random_val([]() {
full_image_t img{};
for (auto& i : img.rgb_data)
i = program.get_random().get_float(0.0f, 1.0f);
return img;
}, "color_noise");
inline blt::gp::operation_t perlin([](const full_image_t& x, const full_image_t& y, const full_image_t& z, const full_image_t& scale) {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
{
auto s = scale.rgb_data[i];
img.rgb_data[i] = perlin_noise(x.rgb_data[i] / s, y.rgb_data[i] / s, z.rgb_data[i] / s);
}
return img;
}, "perlin");
inline blt::gp::operation_t perlin_terminal([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
{
auto ctx = get_ctx(i);
img.rgb_data[i] = perlin_noise(ctx.x / IMAGE_SIZE, ctx.y / IMAGE_SIZE, static_cast<float>(i % CHANNELS) / CHANNELS);
}
return img;
}, "perlin_term");
inline blt::gp::operation_t perlin_warped([](const full_image_t& u, const full_image_t& v) {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_CHANNELS_SIZE; i++)
{
auto ctx = get_ctx(i);
img.rgb_data[i] = perlin_noise((ctx.x + +u.rgb_data[i]) / IMAGE_SIZE, (ctx.y + v.rgb_data[i]) / IMAGE_SIZE,
static_cast<float>(i % CHANNELS) / CHANNELS);
}
return img;
}, "perlin_warped");
inline blt::gp::operation_t op_img_size([]() {
full_image_t img{};
for (float& i : img.rgb_data)
{
i = IMAGE_SIZE;
}
return img;
}, "img_size");
inline blt::gp::operation_t op_x_r([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto ctx = get_ctx(i).x;
img.rgb_data[i * CHANNELS] = ctx;
img.rgb_data[i * CHANNELS + 1] = 0;
img.rgb_data[i * CHANNELS + 2] = 0;
}
return img;
}, "x_r");
inline blt::gp::operation_t op_x_g([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto ctx = get_ctx(i).x;
img.rgb_data[i * CHANNELS] = 0;
img.rgb_data[i * CHANNELS + 1] = ctx;
img.rgb_data[i * CHANNELS + 2] = 0;
}
return img;
}, "x_g");
inline blt::gp::operation_t op_x_b([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto ctx = get_ctx(i).x;
img.rgb_data[i * CHANNELS] = 0;
img.rgb_data[i * CHANNELS + 1] = 0;
img.rgb_data[i * CHANNELS + 2] = ctx;
}
return img;
}, "x_b");
inline blt::gp::operation_t op_x_rgb([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto ctx = get_ctx(i).x;
img.rgb_data[i * CHANNELS] = ctx;
img.rgb_data[i * CHANNELS + 1] = ctx;
img.rgb_data[i * CHANNELS + 2] = ctx;
}
return img;
}, "x_rgb");
inline blt::gp::operation_t op_y_r([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto ctx = get_ctx(i).y;
img.rgb_data[i * CHANNELS] = ctx;
img.rgb_data[i * CHANNELS + 1] = 0;
img.rgb_data[i * CHANNELS + 2] = 0;
}
return img;
}, "y_r");
inline blt::gp::operation_t op_y_g([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto ctx = get_ctx(i).y;
img.rgb_data[i * CHANNELS] = 0;
img.rgb_data[i * CHANNELS + 1] = ctx;
img.rgb_data[i * CHANNELS + 2] = 0;
}
return img;
}, "y_g");
inline blt::gp::operation_t op_y_b([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto ctx = get_ctx(i).y;
img.rgb_data[i * CHANNELS] = 0;
img.rgb_data[i * CHANNELS + 1] = 0;
img.rgb_data[i * CHANNELS + 2] = ctx;
}
return img;
}, "y_b");
inline blt::gp::operation_t op_y_rgb([]() {
full_image_t img{};
for (blt::size_t i = 0; i < DATA_SIZE; i++)
{
auto ctx = get_ctx(i).y;
img.rgb_data[i * CHANNELS] = ctx;
img.rgb_data[i * CHANNELS + 1] = ctx;
img.rgb_data[i * CHANNELS + 2] = ctx;
}
return img;
}, "y_rgb");
template<typename context>
void create_image_operations(blt::gp::operator_builder<context>& builder)
{
builder.add_operator(perlin);
builder.add_operator(perlin_terminal);
builder.add_operator(perlin_warped);
builder.add_operator(add);
builder.add_operator(sub);
builder.add_operator(mul);
builder.add_operator(pro_div);
builder.add_operator(op_sin);
builder.add_operator(op_cos);
builder.add_operator(op_atan);
builder.add_operator(op_exp);
builder.add_operator(op_log);
builder.add_operator(op_abs);
builder.add_operator(op_round);
builder.add_operator(op_v_mod);
builder.add_operator(bitwise_and);
builder.add_operator(bitwise_or);
builder.add_operator(bitwise_invert);
builder.add_operator(bitwise_xor);
builder.add_operator(dissolve);
builder.add_operator(band_pass);
builder.add_operator(hsv_to_rgb);
builder.add_operator(gaussian_blur);
builder.add_operator(median_blur);
// idk when it got enabled but this works on 4.10
#if CV_VERSION_MAJOR >= 4 && CV_VERSION_MINOR >= 10
builder.add_operator(bilateral_filter);
#endif
builder.add_operator(high_pass);
bool state = false;
builder.add_operator(lit, true);
builder.add_operator(vec, true);
builder.add_operator(random_val);
builder.add_operator(op_x_r, state);
builder.add_operator(op_x_g, state);
builder.add_operator(op_x_b, state);
builder.add_operator(op_x_rgb, state);
builder.add_operator(op_y_r, state);
builder.add_operator(op_y_g, state);
builder.add_operator(op_y_b, state);
builder.add_operator(op_y_rgb, state);
}
#endif //IMAGE_GP_6_IMAGE_OPERATIONS_H
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