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#include "image.h"
// #include <format>
#include <QElapsedTimer>
#include <libcamera/formats.h>
#include "macro.h"
#include "pixels.h"
uint64_t sum_elapsed_ns = 0;
uint64_t corr_elapsed_ns = 0;
uint64_t max_elapsed_ns = 0;
uint64_t value_elapsed_ns = 0;
float process_column(const uint8_t (&column)[])
{
start_timer(process_column);
QElapsedTimer t;
t.start();
float result = std::numeric_limits<float>::quiet_NaN();
constexpr uint32_t signalThreshold = 900; // = SKO * sqrt(patternSize)
static constexpr uint32_t patternOffset = patternSize -
((patternSize % 2 == 1) ? 1 : 0);
const uint32_t correlationSize = img_height - patternSize +
((patternSize % 2 == 1) ? 1 : 0);
uint32_t correlation[img_height];
uint32_t integralSum[img_height];
uint32_t maxSum = signalThreshold * 50;
uint32_t x1 = 0;
int32_t y1 = 0;
int32_t y2 = 0;
memset(correlation, 0, img_height * sizeof(correlation[0]));
integralSum[0] = 0;
for (uint32_t i = 1; i < img_height; ++i) {
integralSum[i] = column[i] + integralSum[i - 1];
}
sum_elapsed_ns += t.nsecsElapsed();
t.restart();
for (uint32_t i = 0; i < correlationSize; ++i)
correlation[i + patternSize / 2] = column[i + patternSize / 2]
* (integralSum[i + patternOffset] - integralSum[i]);
corr_elapsed_ns += t.nsecsElapsed();
t.restart();
for (uint32_t i = 3; i < img_height - 2; ++i) {
const auto sum = correlation[i - 1] + correlation[i] +
correlation[i + 1];
if (sum > maxSum)
{
const int32_t rioux0 = int32_t(correlation[i - 2 - 1] +
correlation[i - 1 - 1]) -
int32_t(correlation[i + 1 - 1] +
correlation[i + 2 - 1]);
if (rioux0 < 0)
{
const int32_t rioux1 = int32_t(correlation[i - 2] +
correlation[i - 1]) -
int32_t(correlation[i + 1] +
correlation[i + 2]);
if (rioux1 >= 0)
{
x1 = i - 1;
y1 = rioux0;
y2 = rioux1;
maxSum = sum;
}
}
}
}
value_elapsed_ns += t.nsecsElapsed();
t.restart();
result = (y2 != y1) ? (float(x1) - (float(y1) / (y2 - y1)))
: std::numeric_limits<float>::quiet_NaN();
return result;
}
void Image::rotate()
{
start_timer(rotate);
using namespace std;
#pragma omp parallel
#pragma omp for
for (size_t i = 0; i < img_height; ++i)
{
for (size_t j = 0; j < img_width; ++j)
{
rotated_cw[j][i] = data[img_height - i][j];
}
}
stop_timer(rotate);
}
std::shared_ptr<Pixels> Image::pixels() const
{
auto result = std::make_shared<Pixels>();
result->counters = counters;
start_timer(process_columns);
#pragma omp chunk
#pragma omp parallel for
for (size_t i = 0; i < img_width; i++) {
result->pixels[i] = process_column(rotated_cw[i]);
}
// for (size_t i = 640 - 5; i < 640 + 5; ++i) {
// std::cout << result->pixels[i] << ' ';
// }
// std::cout << std::endl;
stop_timer(process_columns);
return result;
}
void Image::copyFromData(const void *src, size_t size)
{
if (Q_UNLIKELY(size % sizeof(data) != 0 || size < sizeof(data))) {
throw std::logic_error(__func__ + std::string(": wrong data size"));
}
switch (pixelFormat) {
case libcamera::formats::R8: {
// std::cout << "R8" << std::endl;
memcpy(data, src, size);
break;
}
case libcamera::formats::R16: {
// std::cout << "R16" << std::endl;
#pragma omp parallel
#pragma omp for
for (size_t i = 0; i < img_size; i++) {
data[i / img_width][i % img_width] = (((uint16_t *) src)[i] & 0xff00) >> 8;
}
break;
}
default:
throw std::logic_error(__func__ + std::string(": unsupported pixel format"));
break;
}
}
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