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Use precomputed gaussian for filter function

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This commit is contained in:
Stephen Seo 2021-01-23 13:50:43 +09:00
parent 50dfa98f51
commit 26df83affc
2 changed files with 111 additions and 42 deletions
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11
src/blue_noise.cpp
View file

@ -3,6 +3,7 @@
#include <random>
#include <cassert>
#include <iostream>
#include <memory>
#ifndef NDEBUG
# include <cstdio>
@ -58,8 +59,10 @@ std::vector<bool> dither::blue_noise(int width, int height, int threads) {
int filter_size = (width + height) / 2;
std::unique_ptr<std::vector<float>> precomputed = std::make_unique<std::vector<float>>(internal::precompute_gaussian(filter_size));
internal::compute_filter(pbp, width, height, count, filter_size,
filter_out, threads);
filter_out, precomputed.get(), threads);
internal::write_filter(filter_out, width, "filter_out_start.pgm");
while(true) {
//#ifndef NDEBUG
@ -69,7 +72,7 @@ std::vector<bool> dither::blue_noise(int width, int height, int threads) {
//#endif
// get filter values
internal::compute_filter(pbp, width, height, count, filter_size,
filter_out, threads);
filter_out, precomputed.get(), threads);
#ifndef NDEBUG
// for(int i = 0; i < count; ++i) {
@ -112,7 +115,7 @@ std::vector<bool> dither::blue_noise(int width, int height, int threads) {
// get filter values again
internal::compute_filter(pbp, width, height, count, filter_size,
filter_out, threads);
filter_out, precomputed.get(), threads);
// get second buffer's min
int second_min;
@ -146,7 +149,7 @@ std::vector<bool> dither::blue_noise(int width, int height, int threads) {
}
}
internal::compute_filter(pbp, width, height, count, filter_size,
filter_out, threads);
filter_out, precomputed.get(), threads);
internal::write_filter(filter_out, width, "filter_out_final.pgm");
//#ifndef NDEBUG

86
src/blue_noise.hpp
View file

@ -32,6 +32,19 @@ namespace internal {
return std::exp(-(x*x + y*y)/(2*mu_squared));
}
inline std::vector<float> precompute_gaussian(int size) {
std::vector<float> precomputed;
precomputed.reserve(size * size);
for(int i = 0; i < size * size; ++i) {
auto xy = oneToTwo(i, size);
precomputed.push_back(gaussian(
(float)xy.first - size / 2.0f, (float)xy.second - size / 2.0f));
}
return precomputed;
}
inline float filter(
const std::vector<bool>& pbp,
int x, int y,
@ -46,8 +59,7 @@ namespace internal {
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) {
if(pbp[twoToOne(p_prime, q_prime, width)]) {
sum += gaussian((float)p - filter_size/2.0f, (float)q - filter_size/2.0f);
}
}
@ -56,17 +68,48 @@ namespace internal {
return sum;
}
inline float filter_with_precomputed(
const std::vector<bool>& pbp,
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;
if(pbp[twoToOne(p_prime, q_prime, width)]) {
sum += precomputed[twoToOne(p, q, filter_size)];
}
}
}
return sum;
}
inline void compute_filter(
const std::vector<bool> &pbp, 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[internal::twoToOne(x, y, width)] =
internal::filter_with_precomputed(
pbp, x, y, width, height, filter_size, *precomputed);
}
}
} else {
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);
}
}
}
} else {
if(threads == 0) {
threads = 10;
@ -74,6 +117,36 @@ namespace internal {
int active_count = 0;
std::mutex cv_mutex;
std::condition_variable cv;
if(precomputed) {
for(int i = 0; i < count; ++i) {
{
std::unique_lock lock(cv_mutex);
active_count += 1;
}
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,
const std::vector<float> *precomputed) {
int x, y;
std::tie(x, y) = internal::oneToTwo(i, width);
(*fout)[i] = internal::filter_with_precomputed(
*pbp, x, y, width, height, filter_size, *precomputed);
std::unique_lock lock(*cvm);
*ac -= 1;
cv->notify_all();
},
&active_count, &cv_mutex, &cv, i, &pbp, width, height,
filter_size, &filter_out, precomputed);
t.detach();
std::unique_lock lock(cv_mutex);
while(active_count >= threads) {
cv.wait_for(lock, std::chrono::seconds(1));
}
}
} else {
for(int i = 0; i < count; ++i) {
{
std::unique_lock lock(cv_mutex);
@ -98,15 +171,8 @@ namespace internal {
std::unique_lock lock(cv_mutex);
while(active_count >= threads) {
#ifndef NDEBUG
// std::cout << "0, active_count = " << active_count
// << ", pre wait_for" << std::endl;
#endif
cv.wait_for(lock, std::chrono::seconds(1));
#ifndef NDEBUG
// std::cout << "0, active_count = " << active_count
// << ", post wait_for" << std::endl;
#endif
}
}
}
std::unique_lock lock(cv_mutex);