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WIP work on generating blue-noise

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This commit is contained in:
Stephen Seo 2021-11-08 20:04:58 +09:00
parent 73aa21e92a
commit e90834dc0a
7 changed files with 318 additions and 411 deletions
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7
CMakeLists.txt
View file

@ -18,12 +18,15 @@ endif()
find_package(Threads REQUIRED)
find_package(OpenCL REQUIRED)
find_package(PNG REQUIRED)
add_executable(Dithering ${Dithering_SOURCES})
target_compile_features(Dithering PUBLIC cxx_std_17)
target_include_directories(Dithering PUBLIC
Threads::Threads
${OpenCL_INCLUDE_DIRS})
${OpenCL_INCLUDE_DIRS}
${PNG_INCLUDE_DIRS})
target_link_libraries(Dithering PUBLIC
Threads::Threads
${OpenCL_LIBRARIES})
${OpenCL_LIBRARIES}
${PNG_LIBRARIES})

30
src/blue_noise.cl
View file

@ -1,6 +1,23 @@
int twoToOne(x, y, width, height) {
while(x < 0) {
x += width;
}
while(y < 0) {
y += height;
}
x = x % width;
y = y % height;
return x + y * width;
}
//float gaussian(float x, float y) {
// return exp(-(x*x + y*y) / (1.5F * 1.5F * 2.0F));
//}
__kernel void do_filter(
__global float *filter_out, __global float *precomputed,
__global int *pbp, int width, int height, int filter_size) {
__global float *filter_out, __global const float *precomputed,
__global const int *pbp, const int width, const int height,
const int filter_size) {
int i = get_global_id(0);
if(i < 0 || i >= width * height) {
return;
@ -10,11 +27,12 @@ __kernel void do_filter(
float sum = 0.0f;
for(int q = 0; q < filter_size; ++q) {
int q_prime = (height + filter_size / 2 + y - q) % height;
int q_prime = height - filter_size / 2 + y + q;
for(int p = 0; p < filter_size; ++p) {
int p_prime = (width + filter_size / 2 + x - p) % width;
if(pbp[p_prime + q_prime * width] != 0) {
sum += precomputed[p + q * filter_size];
int p_prime = width - filter_size / 2 + x + p;
if(pbp[twoToOne(p_prime, q_prime, width, height)] != 0) {
sum += precomputed[twoToOne(p, q, filter_size, filter_size)];
//sum += gaussian(p - filter_size / 2.0F + 0.5F, q - filter_size / 2.0F + 0.5F);
}
}
}

368
src/blue_noise.cpp
View file

@ -6,6 +6,7 @@
#include <fstream>
#include <memory>
#include <string>
#include <unordered_set>
#include <CL/opencl.h>
@ -81,14 +82,14 @@ image::Bl dither::blue_noise(int width, int height, int threads, bool use_opencl
}
std::cout << "OpenCL: Initialized, trying cl_impl..." << std::endl;
std::vector<bool> result = internal::blue_noise_cl_impl(
std::vector<unsigned int> result = internal::blue_noise_cl_impl(
width, height, filter_size, context, device, program);
clReleaseProgram(program);
clReleaseContext(context);
if(!result.empty()) {
return internal::toBl(result, width);
return internal::rangeToBl(result, width);
}
} while (false);
}
@ -96,160 +97,13 @@ image::Bl dither::blue_noise(int width, int height, int threads, bool use_opencl
if(!using_opencl) {
std::cout << "OpenCL: Failed to setup/use or is not enabled, using regular impl..."
<< std::endl;
return internal::toBl(internal::blue_noise_impl(width, height, threads), width);
return internal::rangeToBl(internal::blue_noise_impl(width, height, threads), width);
}
return {};
}
image::Bl dither::blue_noise_grayscale(int width, int height, int threads) {
int count = width * height;
std::vector<float> filter_out;
filter_out.resize(count);
std::vector<float> image = internal::random_noise_grayscale(count);
int iterations = 0;
int filter_size = (width + height) / 2;
std::vector<float> precomputed(internal::precompute_gaussian(filter_size));
// TODO DEBUG
//float pmax = 0.01F;
//for(float value : precomputed) {
// if(value > pmax) {
// pmax = value;
// }
//}
//for(float &value: precomputed) {
// value /= pmax;
//}
//return image::Bl(precomputed, filter_size);
int min, max, min2, max2;
int prevmax = -1;
int prevmax2 = -1;
float tempPixel;
while(true) {
printf("Iteration %d\n", iterations);
internal::compute_filter_grayscale(image,
width, height, count,
filter_size, filter_out,
&precomputed, 0);
std::tie(min, max) = internal::filter_minmax(filter_out);
//std::tie(std::ignore, max) = internal::filter_minmax_in_range(max,
// width,
// height,
// 7,
// filter_out);
printf("min == %4d, max == %4d", min, max);
tempPixel = image[max];
image[max] = 0.0F;
internal::compute_filter_grayscale(image,
width, height, count,
filter_size, filter_out,
&precomputed, 0);
std::tie(min2, max2) = internal::filter_minmax(filter_out);
//std::tie(min2, std::ignore) = internal::filter_minmax_in_range(min2,
// width,
// height,
// 7,
// filter_out);
printf(", min2 == %4d, max2 == %4d\n", min2, max2);
if(min2 != min) {
image[max] = tempPixel;
break;
} else {
image[max] = image[min];
image[min] = tempPixel;
}
//if(prevmax == max && prevmax2 == max2) {
// image[max] = tempPixel;
// break;
//} else {
// image[max] = image[min2];
// image[min2] = tempPixel;
//}
prevmax = max;
prevmax2 = max2;
//#ifndef NDEBUG
if(iterations % 20 == 0) {
std::string name;
name.append("tempGrayscale");
if(iterations < 10) {
name.append("00");
} else if(iterations < 100) {
name.append("0");
}
name.append(std::to_string(iterations));
name.append(".pgm");
image::Bl(image, width).writeToFile(image::file_type::PGM, true, name);
name.clear();
name.append("tempFilter");
if(iterations < 10) {
name.append("00");
} else if(iterations < 100) {
name.append("0");
}
name.append(std::to_string(iterations));
name.append(".pgm");
internal::compute_filter_grayscale(image,
width, height, count,
filter_size, filter_out,
&precomputed, 0);
std::vector<float> normalizedFilter(filter_out);
float fmax = -std::numeric_limits<float>::infinity();
float fmin = std::numeric_limits<float>::infinity();
for(float value : normalizedFilter) {
if(value > fmax) {
fmax = value;
}
if(value < fmin) {
fmin = value;
}
}
fmax -= fmin;
for(float &value : normalizedFilter) {
value = (value - fmin) / fmax;
}
image::Bl(normalizedFilter, width).writeToFile(image::file_type::PGM, true, name);
}
//#endif
++iterations;
}
internal::compute_filter_grayscale(image,
width, height, count,
filter_size, filter_out,
&precomputed, 0);
std::vector<float> normalizedFilter(filter_out);
float fmax = -std::numeric_limits<float>::infinity();
float fmin = std::numeric_limits<float>::infinity();
for(float value : normalizedFilter) {
if(value > fmax) {
fmax = value;
}
if(value < fmin) {
fmin = value;
}
}
fmax -= fmin;
for(float &value : normalizedFilter) {
value = (value - fmin) / fmax;
}
image::Bl(normalizedFilter, width).writeToFile(image::file_type::PGM, true, "filterOut.pgm");
return image::Bl(image, width);
}
std::vector<bool> dither::internal::blue_noise_impl(int width, int height, int threads) {
std::vector<unsigned int> dither::internal::blue_noise_impl(int width, int height, int threads) {
int count = width * height;
std::vector<float> filter_out;
filter_out.resize(count);
@ -301,36 +155,11 @@ std::vector<bool> dither::internal::blue_noise_impl(int width, int height, int t
// }
#endif
int min, max, min_zero, max_one;
std::tie(min, max) = internal::filter_minmax(filter_out);
if(!pbp[max]) {
max_one = internal::get_one_or_zero(pbp, true, max, width, height);
#ifndef NDEBUG
std::cout << "Post get_one(...)" << std::endl;
#endif
} else {
max_one = max;
}
if(!pbp[max_one]) {
std::cerr << "ERROR: Failed to find pbp[max] one" << std::endl;
break;
}
if(pbp[min]) {
min_zero = internal::get_one_or_zero(pbp, false, min, width, height);
#ifndef NDEBUG
std::cout << "Post get_zero(...)" << std::endl;
#endif
} else {
min_zero = min;
}
if(pbp[min_zero]) {
std::cerr << "ERROR: Failed to find pbp[min] zero" << std::endl;
break;
}
int min, max;
std::tie(min, max) = internal::filter_minmax(filter_out, pbp);
// remove 1
pbp[max_one] = false;
pbp[max] = false;
// get filter values again
internal::compute_filter(pbp, width, height, count, filter_size,
@ -338,20 +167,13 @@ std::vector<bool> dither::internal::blue_noise_impl(int width, int height, int t
// get second buffer's min
int second_min;
std::tie(second_min, std::ignore) = internal::filter_minmax(filter_out);
if(pbp[second_min]) {
second_min = internal::get_one_or_zero(pbp, false, second_min, width, height);
if(pbp[second_min]) {
std::cerr << "ERROR: Failed to find pbp[second_min] zero" << std::endl;
break;
}
}
std::tie(second_min, std::ignore) = internal::filter_minmax(filter_out, pbp);
if(utility::dist(max_one, second_min, width) < 1.5f) {
pbp[max_one] = true;
if(second_min == max) {
pbp[max] = true;
break;
} else {
pbp[min_zero] = true;
pbp[second_min] = true;
}
if(iterations % 100 == 0) {
@ -384,10 +206,45 @@ std::vector<bool> dither::internal::blue_noise_impl(int width, int height, int t
fclose(blue_noise_image);
//#endif
return pbp;
std::cout << "Generating dither_array...\n";
std::vector<unsigned int> dither_array(count);
int min, max;
{
std::vector<bool> pbp_copy(pbp);
std::cout << "Ranking minority pixels...\n";
for (unsigned int i = pixel_count; i-- > 0;) {
std::cout << i << ' ';
internal::compute_filter(pbp, width, height, count, filter_size,
filter_out, precomputed.get(), threads);
std::tie(std::ignore, max) = internal::filter_minmax(filter_out, pbp);
pbp[max] = false;
dither_array[max] = i;
}
pbp = pbp_copy;
}
std::cout << "\nRanking remainder of first half of pixels...\n";
for (unsigned int i = pixel_count; i < (unsigned int)((count + 1) / 2); ++i) {
std::cout << i << ' ';
internal::compute_filter(pbp, width, height, count, filter_size,
filter_out, precomputed.get(), threads);
std::tie(min, std::ignore) = internal::filter_minmax(filter_out, pbp);
pbp[min] = true;
dither_array[min] = i;
}
std::cout << "\nRanking last half of pixels...\n";
for (unsigned int i = (count + 1) / 2; i < (unsigned int)count; ++i) {
std::cout << i << ' ';
internal::compute_filter(pbp, width, height, count, filter_size,
filter_out, precomputed.get(), threads);
std::tie(std::ignore, max) = internal::filter_minmax(filter_out, pbp);
pbp[max] = true;
dither_array[max] = i;
}
return dither_array;
}
std::vector<bool> dither::internal::blue_noise_cl_impl(
std::vector<unsigned int> dither::internal::blue_noise_cl_impl(
int width, int height, int filter_size, cl_context context, cl_device_id device, cl_program program) {
cl_int err;
cl_kernel kernel;
@ -418,18 +275,6 @@ std::vector<bool> dither::internal::blue_noise_cl_impl(
return {};
}
/*
err = clEnqueueWriteBuffer(queue, d_pbp, CL_TRUE, 0, count * sizeof(int), &pbp_i[0], 0, nullptr, nullptr);
if(err != CL_SUCCESS) {
std::cerr << "OpenCL: Failed to write to d_pbp buffer\n";
clReleaseMemObject(d_pbp);
clReleaseMemObject(d_precomputed);
clReleaseMemObject(d_filter_out);
clReleaseCommandQueue(queue);
return {};
}
*/
kernel = clCreateKernel(program, "do_filter", &err);
if(err != CL_SUCCESS) {
std::cerr << "OpenCL: Failed to create kernel: ";
@ -635,29 +480,10 @@ std::vector<bool> dither::internal::blue_noise_cl_impl(
break;
}
int min, max, min_zero, max_one;
std::tie(min, max) = internal::filter_minmax(filter);
if(!pbp[max]) {
max_one = internal::get_one_or_zero(pbp, true, max, width, height);
} else {
max_one = max;
}
if(!pbp[max_one]) {
std::cerr << "ERROR: Failed to find pbp[max] one" << std::endl;
break;
}
int min, max;
std::tie(min, max) = internal::filter_minmax(filter, pbp);
if(pbp[min]) {
min_zero = internal::get_one_or_zero(pbp, false, min, width, height);
} else {
min_zero = min;
}
if(pbp[min_zero]) {
std::cerr << "ERROR: Failed to find pbp[min] zero" << std::endl;
break;
}
pbp[max_one] = false;
pbp[max] = false;
if(!get_filter()) {
std::cerr << "OpenCL: Failed to execute do_filter\n";
@ -666,20 +492,13 @@ std::vector<bool> dither::internal::blue_noise_cl_impl(
// get second buffer's min
int second_min;
std::tie(second_min, std::ignore) = internal::filter_minmax(filter);
if(pbp[second_min]) {
second_min = internal::get_one_or_zero(pbp, false, second_min, width, height);
if(pbp[second_min]) {
std::cerr << "ERROR: Failed to find pbp[second_min] zero" << std::endl;
break;
}
}
std::tie(second_min, std::ignore) = internal::filter_minmax(filter, pbp);
if(utility::dist(max_one, second_min, width) < 1.5f) {
pbp[max_one] = true;
if(second_min == max) {
pbp[max] = true;
break;
} else {
pbp[min_zero] = true;
pbp[second_min] = true;
}
if(iterations % 100 == 0) {
@ -711,10 +530,83 @@ std::vector<bool> dither::internal::blue_noise_cl_impl(
fclose(blue_noise_image);
}
#ifndef NDEBUG
{
image::Bl pbp_image = toBl(pbp, width);
pbp_image.writeToFile(image::file_type::PNG, true, "debug_pbp_before.png");
}
#endif
std::cout << "Generating dither_array...\n";
std::unordered_set<unsigned int> set;
std::vector<unsigned int> dither_array(count);
int min, max;
{
std::vector<bool> pbp_copy(pbp);
std::cout << "Ranking minority pixels...\n";
for (unsigned int i = pixel_count; i-- > 0;) {
std::cout << i << ' ';
get_filter();
std::tie(std::ignore, max) = internal::filter_minmax(filter, pbp);
pbp.at(max) = false;
dither_array.at(max) = i;
if (set.find(max) != set.end()) {
std::cout << "\nWARNING: Reusing index " << max << '\n';
} else {
set.insert(max);
}
}
pbp = pbp_copy;
}
std::cout << "\nRanking remainder of first half of pixels...\n";
for (unsigned int i = pixel_count; i < (unsigned int)((count + 1) / 2); ++i) {
std::cout << i << ' ';
get_filter();
std::tie(min, std::ignore) = internal::filter_minmax(filter, pbp);
pbp.at(min) = true;
dither_array.at(min) = i;
if (set.find(min) != set.end()) {
std::cout << "\nWARNING: Reusing index " << min << '\n';
} else {
set.insert(min);
}
}
#ifndef NDEBUG
{
get_filter();
internal::write_filter(filter, width, "filter_mid.pgm");
image::Bl pbp_image = toBl(pbp, width);
pbp_image.writeToFile(image::file_type::PNG, true, "debug_pbp_mid.png");
}
#endif
std::cout << "\nRanking last half of pixels...\n";
for (unsigned int i = (count + 1) / 2; i < (unsigned int)count; ++i) {
std::cout << i << ' ';
get_filter();
std::tie(std::ignore, max) = internal::filter_minmax(filter, pbp);
pbp.at(max) = true;
dither_array.at(max) = i;
if (set.find(max) != set.end()) {
std::cout << "\nWARNING: Reusing index " << max << '\n';
} else {
set.insert(max);
}
}
std::cout << std::endl;
#ifndef NDEBUG
{
get_filter();
internal::write_filter(filter, width, "filter_after.pgm");
image::Bl pbp_image = toBl(pbp, width);
pbp_image.writeToFile(image::file_type::PNG, true, "debug_pbp_after.png");
}
#endif
clReleaseKernel(kernel);
clReleaseMemObject(d_pbp);
clReleaseMemObject(d_precomputed);
clReleaseMemObject(d_filter_out);
clReleaseCommandQueue(queue);
return pbp;
return dither_array;
}

245
src/blue_noise.hpp
View file

@ -1,6 +1,7 @@
#ifndef BLUE_NOISE_HPP
#define BLUE_NOISE_HPP
#include <limits>
#include <vector>
#include <functional>
#include <unordered_set>
@ -13,6 +14,7 @@
#include <random>
#include <cassert>
#include <stdexcept>
#include <iostream>
#include <sys/sysinfo.h>
@ -25,11 +27,9 @@ namespace dither {
image::Bl blue_noise(int width, int height, int threads = 1, bool use_opencl = true);
image::Bl blue_noise_grayscale(int width, int height, int threads = 1);
namespace internal {
std::vector<bool> blue_noise_impl(int width, int height, int threads = 1);
std::vector<bool> blue_noise_cl_impl(
std::vector<unsigned int> blue_noise_impl(int width, int height, int threads = 1);
std::vector<unsigned int> blue_noise_cl_impl(
int width, int height, int filter_size,
cl_context context, cl_device_id device, cl_program program);
@ -59,27 +59,6 @@ namespace internal {
return pbp;
}
inline std::vector<float> random_noise_grayscale(unsigned int size) {
std::vector<float> graynoise;
graynoise.reserve(size);
std::default_random_engine re(std::random_device{}());
std::uniform_real_distribution<float> dist(0.0F, 1.0F);
for(unsigned int i = 0; i < size; ++i) {
graynoise.push_back(static_cast<float>(i) / static_cast<float>(size - 1));
//graynoise.push_back(dist(re));
}
for(unsigned int i = 0; i < size - 1; ++i) {
std::uniform_int_distribution<unsigned int> range(i + 1, size - 1);
unsigned int ridx = range(re);
float temp = graynoise[i];
graynoise[i] = graynoise[ridx];
graynoise[ridx] = temp;
}
return graynoise;
}
constexpr float mu = 1.5F;
constexpr float mu_squared = mu * mu;
constexpr float double_mu_squared = 2.0F * mu * mu;
@ -95,8 +74,8 @@ namespace internal {
for(int i = 0; i < size * size; ++i) {
auto xy = utility::oneToTwo(i, size);
precomputed.push_back(gaussian(
(float)xy.first - (float)size / 2.0f,
(float)xy.second - (float)size / 2.0f));
(float)xy.first - (float)size / 2.0F + 0.5F,
(float)xy.second - (float)size / 2.0F + 0.5F));
}
return precomputed;
@ -113,12 +92,12 @@ namespace internal {
// p' = (M + x - (p - M/2)) % M = (3M/2 + x - p) % M
// q' = (N + y - (q - M/2)) % N = (N + M/2 + y - q) % N
for(int q = 0; q < filter_size; ++q) {
int q_prime = (height + filter_size / 2 + y - q) % height;
int q_prime = (height - filter_size / 2 + y + q) % height;
for(int p = 0; p < filter_size; ++p) {
int p_prime = (width + filter_size / 2 + x - p) % width;
int p_prime = (width - filter_size / 2 + x + p) % width;
if(pbp[utility::twoToOne(p_prime, q_prime, width, height)]) {
sum += gaussian((float)p - filter_size/2.0f,
(float)q - filter_size/2.0f);
sum += gaussian((float)p - filter_size/2.0F + 0.5F,
(float)q - filter_size/2.0F + 0.5F);
}
}
}
@ -126,24 +105,6 @@ namespace internal {
return sum;
}
inline float filter_grayscale(
const std::vector<float> &image,
int x, int y,
int width, int height, int filter_size) {
float sum = 0.0F;
for(int q = 0; q < filter_size; ++q) {
int q_prime = (height + filter_size / 2 + y - q) % height;
for(int p = 0; p < filter_size; ++p) {
int p_prime = (width + filter_size / 2 + x - p) % width;
sum += image[utility::twoToOne(p_prime, q_prime, width, height)]
* gaussian((float)p - filter_size/2.0F,
(float)q - filter_size/2.0F);
}
}
return sum;
}
inline float filter_with_precomputed(
const std::vector<bool>& pbp,
int x, int y,
@ -151,35 +112,13 @@ namespace internal {
const std::vector<float> &precomputed) {
float sum = 0.0f;
for(int q = 0; q < filter_size; ++q) {
int q_prime = (height + filter_size / 2 + y - q) % height;
for(int p = 0; p < filter_size; ++p) {
int p_prime = (width + filter_size / 2 + x - p) % width;
if(pbp[utility::twoToOne(p_prime, q_prime, width, height)]) {
sum += precomputed[utility::twoToOne(p, q, filter_size, filter_size)];
}
}
}
return sum;
}
inline float filter_with_precomputed_grayscale(
const std::vector<float>& image,
int x, int y,
int width, int height, int filter_size,
const std::vector<float> &precomputed) {
float sum = 0.0F;
for(int q = 0; q < filter_size; ++q) {
int q_prime = (height - filter_size / 2 + y + q) % height;
for(int p = 0; p < filter_size; ++p) {
int p_prime = (width - filter_size / 2 + x + p) % width;
sum += image[utility::twoToOne(p_prime, q_prime, width, height)]
* precomputed[utility::twoToOne(p,
q,
filter_size,
filter_size)];
if(pbp[utility::twoToOne(p_prime, q_prime, width, height)]) {
sum += precomputed[utility::twoToOne(p, q, filter_size, filter_size)];
}
}
}
@ -281,95 +220,61 @@ namespace internal {
}
inline void compute_filter_grayscale(
const std::vector<float> &image, int width, int height,
int count, int filter_size, std::vector<float> &filter_out,
const std::vector<float> *precomputed = nullptr,
int threads = 1) {
if(threads == 1) {
if(precomputed) {
for(int y = 0; y < height; ++y) {
for(int x = 0; x < width; ++x) {
filter_out[utility::twoToOne(x, y, width, height)] =
internal::filter_with_precomputed_grayscale(
image,
x, y,
width, height,
filter_size,
*precomputed);
inline std::pair<int, int> filter_minmax(const std::vector<float> &filter,
std::vector<bool> pbp) {
// ensure minority pixel is "true"
unsigned int count = 0;
for (bool value : pbp) {
if(value) {
++count;
}
}
} else {
for(int y = 0; y < height; ++y) {
for(int x = 0; x < width; ++x) {
filter_out[utility::twoToOne(x, y, width, height)] =
internal::filter_grayscale(image,
x, y,
width, height,
filter_size);
}
}
}
} else {
if(threads == 0) {
threads = get_nprocs();
if(threads == 0) {
throw std::runtime_error("0 threads detected, "
"should be impossible");
if (count * 2 >= pbp.size()) {
for (unsigned int i = 0; i < pbp.size(); ++i) {
pbp[i] = !pbp[i];
}
}
if(precomputed) {
const auto tfn = [] (unsigned int ymin, unsigned int ymax,
unsigned int width, unsigned int height,
unsigned int filter_size,
const std::vector<float> *const image,
std::vector<float> *const filter_out,
const std::vector<float> *const precomputed) {
for(unsigned int y = ymin; y < ymax; ++y) {
for(unsigned int x = 0; x < width; ++x) {
(*filter_out)[utility::twoToOne(x, y, width, height)] =
internal::filter_with_precomputed_grayscale(
*image,
x, y,
width, height,
filter_size,
*precomputed);
}
}
};
unsigned int step = height / threads;
std::vector<std::thread> threadHandles;
for(int i = 0; i < threads; ++i) {
unsigned int starty = i * step;
unsigned int endy = (i + 1) * step;
if(i + 1 == threads) {
endy = height;
}
threadHandles.emplace_back(tfn, starty, endy,
width, height,
filter_size,
&image,
&filter_out,
precomputed);
}
for(int i = 0; i < threads; ++i) {
threadHandles[i].join();
}
} else {
// TODO unimplemented
throw std::runtime_error("Unimplemented");
}
}
}
inline std::pair<int, int> filter_minmax(const std::vector<float>& filter) {
float min = std::numeric_limits<float>::infinity();
float max = -std::numeric_limits<float>::infinity();
int min_index = 0;
int max_index = 0;
int min_index = -1;
int max_index = -1;
for(std::vector<float>::size_type i = 0; i < filter.size(); ++i) {
if(!pbp[i] && filter[i] < min) {
min_index = i;
min = filter[i];
}
if(pbp[i] && filter[i] > max) {
max_index = i;
max = filter[i];
}
}
return {min_index, max_index};
}
inline std::pair<int, int> filter_abs_minmax(
const std::vector<float> &filter) {
float min = std::numeric_limits<float>::infinity();
float max = -std::numeric_limits<float>::infinity();
int min_index = -1;
int max_index = -1;
std::default_random_engine re(std::random_device{}());
std::size_t startIdx = std::uniform_int_distribution<std::size_t>(0, filter.size() - 1)(re);
for(std::vector<float>::size_type i = startIdx; i < filter.size(); ++i) {
if(filter[i] < min) {
min_index = i;
min = filter[i];
}
if(filter[i] > max) {
max_index = i;
max = filter[i];
}
}
for(std::vector<float>::size_type i = 0; i < startIdx; ++i) {
if(filter[i] < min) {
min_index = i;
min = filter[i];
@ -449,7 +354,7 @@ namespace internal {
inline void write_filter(const std::vector<float> &filter, int width, const char *filename) {
int min, max;
std::tie(min, max) = filter_minmax(filter);
std::tie(min, max) = filter_abs_minmax(filter);
printf("Writing to %s, min is %.3f, max is %.3f\n", filename, filter[min], filter[max]);
FILE *filter_image = fopen(filename, "w");
@ -472,12 +377,40 @@ namespace internal {
&& "New image::Bl size too small (pbp's size is not a multiple of width)");
for(unsigned int i = 0; i < pbp.size(); ++i) {
bwImage.getData()[i] = pbp[i] ? 1 : 0;
bwImage.getData()[i] = pbp[i] ? 255 : 0;
}
return bwImage;
}
inline image::Bl rangeToBl(const std::vector<unsigned int> &values, int width) {
int min = std::numeric_limits<int>::max();
int max = std::numeric_limits<int>::min();
for (int value : values) {
if (value < min) {
min = value;
}
if (value > max) {
max = value;
}
}
std::cout << "rangeToBl: Got min == " << min << " and max == " << max << std::endl;
max -= min;
image::Bl grImage(width, values.size() / width);
assert((unsigned long)grImage.getSize() >= values.size()
&& "New image::Bl size too small (values' size is not a multiple of width)");
for(unsigned int i = 0; i < values.size(); ++i) {
grImage.getData()[i] = ((float)((int)(values[i]) - min) / (float)max) * 255.0F;
}
return grImage;
}
inline std::pair<int, int> filter_minmax_in_range(int start, int width,
int height,
int range,

64
src/image.cpp
View file

@ -2,6 +2,9 @@
#include <cstdio>
#include <random>
#include <iostream>
#include <png.h>
image::Bl::Bl() :
data(),
@ -83,6 +86,7 @@ bool image::Bl::canWriteFile(file_type type) {
case file_type::PBM:
case file_type::PGM:
case file_type::PPM:
case file_type::PNG:
return true;
default:
return false;
@ -104,6 +108,66 @@ bool image::Bl::writeToFile(file_type type, bool canOverwrite, const char *filen
fclose(file);
}
if(type == file_type::PNG) {
FILE *outfile = fopen(filename, "wb");
if (outfile == nullptr) {
return false;
}
const static auto pngErrorLFn = [] (png_structp /* unused */,
png_const_charp message) {
std::cerr << "WARNING [libpng]: " << message << std::endl;
};
const static auto pngWarnLFn = [] (png_structp /* unused */,
png_const_charp message) {
std::cerr << "ERROR [libpng]: " << message << std::endl;
};
png_structp png_ptr = png_create_write_struct(PNG_LIBPNG_VER_STRING,
nullptr,
pngErrorLFn,
pngWarnLFn);
if (png_ptr == nullptr) {
fclose(outfile);
return false;
}
png_infop info_ptr = png_create_info_struct(png_ptr);
if (info_ptr == nullptr) {
png_destroy_write_struct(&png_ptr, nullptr);
fclose(outfile);
return false;
}
if (setjmp(png_jmpbuf(png_ptr))) {
png_destroy_write_struct(&png_ptr, &info_ptr);
fclose(outfile);
return false;
}
png_init_io(png_ptr, outfile);
png_set_IHDR(png_ptr, info_ptr, width, height, 8, PNG_COLOR_TYPE_GRAY,
PNG_INTERLACE_NONE, PNG_COMPRESSION_TYPE_DEFAULT,
PNG_FILTER_TYPE_DEFAULT);
png_write_info(png_ptr, info_ptr);
//png_set_filler(png_ptr, 0, PNG_FILLER_AFTER);
for (unsigned int j = 0; j < this->data.size() / this->width; ++j) {
unsigned char *dataPtr = &this->data.at(j * this->width);
png_write_rows(png_ptr, &dataPtr, 1);
}
png_write_end(png_ptr, nullptr);
png_destroy_write_struct(&png_ptr, &info_ptr);
fclose(outfile);
return true;
}
switch(type) {
case file_type::PBM:
file = fopen(filename, "w");

2
src/image.hpp
View file

@ -18,7 +18,7 @@ namespace image {
PBM,
PGM,
PPM,
// TODO PNG support
PNG,
};
class Base {

9
src/main.cpp
View file

@ -4,13 +4,10 @@
int main(int argc, char **argv) {
//#ifndef NDEBUG
// std::cout << "Trying blue_noise..." << std::endl;
// image::Bl bl = dither::blue_noise(100, 100, 8, true);
// bl.writeToFile(image::file_type::PBM, true, "blueNoiseOut.pbm");
std::cout << "Trying blue_noise..." << std::endl;
image::Bl bl = dither::blue_noise(32, 32, 15, true);
bl.writeToFile(image::file_type::PNG, true, "blueNoiseOut.png");
//#endif
image::Bl bl = dither::blue_noise_grayscale(64, 64);
bl.writeToFile(image::file_type::PGM, true, "blueNoiseGrayscaleOut.pgm");
return 0;
}