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#include "masked_image.h"
#include <algorithm>
#include <iostream>
const cv::Size MaskedImage::kDownsampleKernelSize = cv::Size(6, 6);
const int MaskedImage::kDownsampleKernel[6] = {1, 5, 10, 10, 5, 1};
bool MaskedImage::contains_mask(int y, int x, int patch_size) const {
auto mask_size = size();
for (int dy = -patch_size; dy <= patch_size; ++dy) {
for (int dx = -patch_size; dx <= patch_size; ++dx) {
int yy = y + dy, xx = x + dx;
if (yy >= 0 && yy < mask_size.height && xx >= 0 && xx < mask_size.width) {
if (is_masked(yy, xx) && !is_globally_masked(yy, xx)) return true;
}
}
}
return false;
}
MaskedImage MaskedImage::downsample() const {
const auto &kernel_size = MaskedImage::kDownsampleKernelSize;
const auto &kernel = MaskedImage::kDownsampleKernel;
const auto size = this->size();
const auto new_size = cv::Size(size.width / 2, size.height / 2);
auto ret = MaskedImage(new_size.width, new_size.height);
if (!m_global_mask.empty()) ret.init_global_mask_mat();
for (int y = 0; y < size.height - 1; y += 2) {
for (int x = 0; x < size.width - 1; x += 2) {
int r = 0, g = 0, b = 0, ksum = 0;
bool is_gmasked = true;
for (int dy = -kernel_size.height / 2 + 1; dy <= kernel_size.height / 2; ++dy) {
for (int dx = -kernel_size.width / 2 + 1; dx <= kernel_size.width / 2; ++dx) {
int yy = y + dy, xx = x + dx;
if (yy >= 0 && yy < size.height && xx >= 0 && xx < size.width) {
if (!is_globally_masked(yy, xx)) {
is_gmasked = false;
}
if (!is_masked(yy, xx)) {
auto source_ptr = get_image(yy, xx);
int k = kernel[kernel_size.height / 2 - 1 + dy] * kernel[kernel_size.width / 2 - 1 + dx];
r += source_ptr[0] * k, g += source_ptr[1] * k, b += source_ptr[2] * k;
ksum += k;
}
}
}
}
if (ksum > 0) r /= ksum, g /= ksum, b /= ksum;
if (!m_global_mask.empty()) {
ret.set_global_mask(y / 2, x / 2, is_gmasked);
}
if (ksum > 0) {
auto target_ptr = ret.get_mutable_image(y / 2, x / 2);
target_ptr[0] = r, target_ptr[1] = g, target_ptr[2] = b;
ret.set_mask(y / 2, x / 2, 0);
} else {
ret.set_mask(y / 2, x / 2, 1);
}
}
}
return ret;
}
MaskedImage MaskedImage::upsample(int new_w, int new_h) const {
const auto size = this->size();
auto ret = MaskedImage(new_w, new_h);
if (!m_global_mask.empty()) ret.init_global_mask_mat();
for (int y = 0; y < new_h; ++y) {
for (int x = 0; x < new_w; ++x) {
int yy = y * size.height / new_h;
int xx = x * size.width / new_w;
if (is_globally_masked(yy, xx)) {
ret.set_global_mask(y, x, 1);
ret.set_mask(y, x, 1);
} else {
if (!m_global_mask.empty()) ret.set_global_mask(y, x, 0);
if (is_masked(yy, xx)) {
ret.set_mask(y, x, 1);
} else {
auto source_ptr = get_image(yy, xx);
auto target_ptr = ret.get_mutable_image(y, x);
for (int c = 0; c < 3; ++c)
target_ptr[c] = source_ptr[c];
ret.set_mask(y, x, 0);
}
}
}
}
return ret;
}
MaskedImage MaskedImage::upsample(int new_w, int new_h, const cv::Mat &new_global_mask) const {
auto ret = upsample(new_w, new_h);
ret.set_global_mask_mat(new_global_mask);
return ret;
}
void MaskedImage::compute_image_gradients() {
if (m_image_grad_computed) {
return;
}
const auto size = m_image.size();
m_image_grady = cv::Mat(size, CV_8UC3);
m_image_gradx = cv::Mat(size, CV_8UC3);
m_image_grady = cv::Scalar::all(0);
m_image_gradx = cv::Scalar::all(0);
for (int i = 1; i < size.height - 1; ++i) {
const auto *ptr = m_image.ptr<unsigned char>(i, 0);
const auto *ptry1 = m_image.ptr<unsigned char>(i + 1, 0);
const auto *ptry2 = m_image.ptr<unsigned char>(i - 1, 0);
const auto *ptrx1 = m_image.ptr<unsigned char>(i, 0) + 3;
const auto *ptrx2 = m_image.ptr<unsigned char>(i, 0) - 3;
auto *mptry = m_image_grady.ptr<unsigned char>(i, 0);
auto *mptrx = m_image_gradx.ptr<unsigned char>(i, 0);
for (int j = 3; j < size.width * 3 - 3; ++j) {
mptry[j] = (ptry1[j] / 2 - ptry2[j] / 2) + 128;
mptrx[j] = (ptrx1[j] / 2 - ptrx2[j] / 2) + 128;
}
}
m_image_grad_computed = true;
}
void MaskedImage::compute_image_gradients() const {
const_cast<MaskedImage *>(this)->compute_image_gradients();
}
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