#endif
void dither::internal::recursive_apply_radius(
- std::size_t idx, std::size_t width, std::size_t height,
- std::size_t radius, const std::function<bool(std::size_t)>& fn) {
- std::unordered_set<std::size_t> visited;
+ int idx, int width, int height,
+ int radius, const std::function<bool(int)>& fn) {
+ std::unordered_set<int> visited;
#ifndef NDEBUG
if(recursive_apply_radius_impl(idx, width, height, radius, fn, visited)) {
puts("recursive_apply_radius_impl found result");
}
bool dither::internal::recursive_apply_radius_impl(
- std::size_t idx, std::size_t width, std::size_t height,
- std::size_t radius, const std::function<bool(std::size_t)>& fn,
- std::unordered_set<std::size_t>& visited) {
+ int idx, int width, int height,
+ int radius, const std::function<bool(int)>& fn,
+ std::unordered_set<int>& visited) {
if(fn(idx)) {
return true;
}
- std::size_t x, y, temp;
+ int x, y, temp;
std::tie(x, y) = oneToTwo(idx, width);
if(x + 1 < width) {
}
-std::vector<bool> dither::blue_noise(std::size_t width, std::size_t height, std::size_t threads) {
- std::size_t count = width * height;
- std::vector<double> filter_out;
+std::vector<bool> dither::blue_noise(int width, int height, int threads) {
+ int count = width * height;
+ std::vector<float> filter_out;
filter_out.resize(count);
std::vector<bool> pbp; // Prototype Binary Pattern
pbp.resize(count);
std::default_random_engine re(std::random_device{}());
- std::uniform_int_distribution<std::size_t> dist(0, count - 1);
+ std::uniform_int_distribution<int> dist(0, count - 1);
- const std::size_t pixel_count = count * 4 / 10;
+ const int pixel_count = count * 4 / 10;
// initialize pbp
- for(std::size_t i = 0; i < count; ++i) {
+ for(int i = 0; i < count; ++i) {
if(i < pixel_count) {
pbp[i] = true;
} else {
}
}
// randomize pbp
- for(std::size_t i = 0; i < count-1; ++i) {
+ for(int i = 0; i < count-1; ++i) {
decltype(dist)::param_type range{i+1, count-1};
- std::size_t ridx = dist(re, range);
+ int ridx = dist(re, range);
// probably can't use std::swap since using std::vector<bool>
bool temp = pbp[i];
pbp[i] = pbp[ridx];
pbp[ridx] = temp;
}
//#ifndef NDEBUG
- printf("Inserting %ld pixels into image of max count %ld\n", pixel_count, count);
+ printf("Inserting %d pixels into image of max count %d\n", pixel_count, count);
// generate image from randomized pbp
FILE *random_noise_image = fopen("random_noise.pbm", "w");
- fprintf(random_noise_image, "P1\n%ld %ld\n", width, height);
- for(std::size_t y = 0; y < height; ++y) {
- for(std::size_t x = 0; x < width; ++x) {
+ fprintf(random_noise_image, "P1\n%d %d\n", width, height);
+ for(int y = 0; y < height; ++y) {
+ for(int x = 0; x < width; ++x) {
fprintf(random_noise_image, "%d ", pbp[internal::twoToOne(x, y, width)] ? 1 : 0);
}
fputc('\n', random_noise_image);
//#endif
//#ifndef NDEBUG
- std::size_t iterations = 0;
+ int iterations = 0;
//#endif
- std::size_t filter_size = (width + height) / 2;
+ int filter_size = (width + height) / 2;
while(true) {
//#ifndef NDEBUG
// if(++iterations % 10 == 0) {
- printf("Iteration %ld\n", ++iterations);
+ printf("Iteration %d\n", ++iterations);
// }
//#endif
// get filter values
filter_out, threads);
#ifndef NDEBUG
-// for(std::size_t i = 0; i < count; ++i) {
-// std::size_t x, y;
+// for(int i = 0; i < count; ++i) {
+// int x, y;
// std::tie(x, y) = internal::oneToTwo(i, width);
-// printf("%ld (%ld, %ld): %f\n", i, x, y, filter_out[i]);
+// printf("%d (%d, %d): %f\n", i, x, y, filter_out[i]);
// }
#endif
- std::size_t min, max, min_zero, max_one;
+ 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);
filter_out, threads);
// get second buffer's min
- std::size_t second_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);
//#ifndef NDEBUG
// generate blue_noise image from pbp
FILE *blue_noise_image = fopen("blue_noise.pbm", "w");
- fprintf(blue_noise_image, "P1\n%ld %ld\n", width, height);
- for(std::size_t y = 0; y < height; ++y) {
- for(std::size_t x = 0; x < width; ++x) {
+ fprintf(blue_noise_image, "P1\n%d %d\n", width, height);
+ for(int y = 0; y < height; ++y) {
+ for(int x = 0; x < width; ++x) {
fprintf(blue_noise_image, "%d ", pbp[internal::twoToOne(x, y, width)] ? 1 : 0);
}
fputc('\n', blue_noise_image);
namespace dither {
-std::vector<bool> blue_noise(std::size_t width, std::size_t height, std::size_t threads = 1);
+std::vector<bool> blue_noise(int width, int height, int threads = 1);
namespace internal {
- inline std::size_t twoToOne(std::size_t x, std::size_t y, std::size_t width) {
+ inline int twoToOne(int x, int y, int width) {
return x + y * width;
}
- inline std::tuple<std::size_t, std::size_t> oneToTwo(std::size_t i, std::size_t width) {
+ inline std::tuple<int, int> oneToTwo(int i, int width) {
return {i % width, i / width};
}
- constexpr double mu_squared = 1.5 * 1.5;
+ constexpr float mu_squared = 1.5 * 1.5;
- inline double gaussian(double x, double y) {
+ inline float gaussian(float x, float y) {
return std::exp(-(x*x + y*y)/(2*mu_squared));
}
- inline double filter(
+ inline float filter(
const std::vector<bool>& pbp,
- std::size_t x, std::size_t y,
- std::size_t width, std::size_t height, std::size_t filter_size) {
- double sum = 0.0;
+ int x, int y,
+ int width, int height, int filter_size) {
+ float sum = 0.0;
// Should be range -M/2 to M/2, but size_t cannot be negative, so range
// is 0 to M.
// 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(std::size_t q = 0; q < filter_size; ++q) {
- std::size_t q_prime = (height + filter_size / 2 + y - q) % height;
- for(std::size_t p = 0; p < filter_size; ++p) {
- std::size_t p_prime = (width + filter_size / 2 + x - p) % width;
+ 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;
bool pbp_value = pbp[twoToOne(p_prime, q_prime, width)];
if(pbp_value) {
- sum += gaussian((double)p - filter_size/2.0, (double)q - filter_size/2.0);
+ sum += gaussian((float)p - filter_size/2.0, (float)q - filter_size/2.0);
}
}
}
}
inline void compute_filter(
- const std::vector<bool> &pbp, std::size_t width, std::size_t height,
- std::size_t count, std::size_t filter_size, std::vector<double> &filter_out,
- std::size_t threads = 1) {
+ const std::vector<bool> &pbp, int width, int height,
+ int count, int filter_size, std::vector<float> &filter_out,
+ int threads = 1) {
if(threads == 1) {
- for(std::size_t y = 0; y < height; ++y) {
- for(std::size_t x = 0; x < width; ++x) {
+ for(int y = 0; y < height; ++y) {
+ for(int x = 0; x < width; ++x) {
filter_out[internal::twoToOne(x, y, width)] =
internal::filter(pbp, x, y, width, height, filter_size);
}
if(threads == 0) {
threads = 10;
}
- std::size_t active_count = 0;
+ int active_count = 0;
std::mutex cv_mutex;
std::condition_variable cv;
- for(std::size_t i = 0; i < count; ++i) {
+ for(int i = 0; i < count; ++i) {
{
std::unique_lock lock(cv_mutex);
active_count += 1;
}
- std::thread t([] (std::size_t *ac, std::mutex *cvm,
- std::condition_variable *cv, std::size_t i,
- const std::vector<bool> *pbp, std::size_t width,
- std::size_t height, std::size_t filter_size,
- std::vector<double> *fout) {
- std::size_t x, y;
+ std::thread t([] (int *ac, std::mutex *cvm,
+ std::condition_variable *cv, int i,
+ const std::vector<bool> *pbp, int width,
+ int height, int filter_size,
+ std::vector<float> *fout) {
+ int x, y;
std::tie(x, y) = internal::oneToTwo(i, width);
(*fout)[i] = internal::filter(
*pbp, x, y, width, height, filter_size);
}
- inline std::tuple<std::size_t, std::size_t> filter_minmax(const std::vector<double>& filter) {
- double min = std::numeric_limits<double>::infinity();
- double max = 0.0;
- std::size_t min_index = 0;
- std::size_t max_index = 0;
+ inline std::tuple<int, int> filter_minmax(const std::vector<float>& filter) {
+ float min = std::numeric_limits<float>::infinity();
+ float max = 0.0;
+ int min_index = 0;
+ int max_index = 0;
- for(std::vector<double>::size_type i = 0; i < filter.size(); ++i) {
+ for(std::vector<float>::size_type i = 0; i < filter.size(); ++i) {
if(filter[i] < min) {
min_index = i;
min = filter[i];
}
void recursive_apply_radius(
- std::size_t idx, std::size_t width,
- std::size_t height, std::size_t radius,
- const std::function<bool(std::size_t)>& fn);
+ int idx, int width,
+ int height, int radius,
+ const std::function<bool(int)>& fn);
bool recursive_apply_radius_impl(
- std::size_t idx, std::size_t width,
- std::size_t height, std::size_t radius,
- const std::function<bool(std::size_t)>& fn,
- std::unordered_set<std::size_t>& visited);
+ int idx, int width,
+ int height, int radius,
+ const std::function<bool(int)>& fn,
+ std::unordered_set<int>& visited);
- inline std::size_t get_one_or_zero(
+ inline int get_one_or_zero(
const std::vector<bool>& pbp, bool get_one,
- std::size_t idx, std::size_t width, std::size_t height) {
- std::size_t found_idx;
+ int idx, int width, int height) {
+ int found_idx;
bool found = false;
- for(std::size_t radius = 1; radius <= 12; ++radius) {
+ for(int radius = 1; radius <= 12; ++radius) {
recursive_apply_radius(
idx, width, height, radius,
- [&found_idx, &found, &pbp, &get_one] (std::size_t idx) {
+ [&found_idx, &found, &pbp, &get_one] (int idx) {
if((get_one && pbp[idx]) || (!get_one && !pbp[idx])) {
found_idx = idx;
found = true;