File size: 10,992 Bytes
e4545e2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 |
#include <algorithm>
#include <iostream>
#include <cmath>
#include "masked_image.h"
#include "nnf.h"
/**
* Nearest-Neighbor Field (see PatchMatch algorithm).
* This algorithme uses a version proposed by Xavier Philippeau.
*
*/
template <typename T>
T clamp(T value, T min_value, T max_value) {
return std::min(std::max(value, min_value), max_value);
}
void NearestNeighborField::_randomize_field(int max_retry, bool reset) {
auto this_size = source_size();
for (int i = 0; i < this_size.height; ++i) {
for (int j = 0; j < this_size.width; ++j) {
if (m_source.is_globally_masked(i, j)) continue;
auto this_ptr = mutable_ptr(i, j);
int distance = reset ? PatchDistanceMetric::kDistanceScale : this_ptr[2];
if (distance < PatchDistanceMetric::kDistanceScale) {
continue;
}
int i_target = 0, j_target = 0;
for (int t = 0; t < max_retry; ++t) {
i_target = rand() % this_size.height;
j_target = rand() % this_size.width;
if (m_target.is_globally_masked(i_target, j_target)) continue;
distance = _distance(i, j, i_target, j_target);
if (distance < PatchDistanceMetric::kDistanceScale)
break;
}
this_ptr[0] = i_target, this_ptr[1] = j_target, this_ptr[2] = distance;
}
}
}
void NearestNeighborField::_initialize_field_from(const NearestNeighborField &other, int max_retry) {
const auto &this_size = source_size();
const auto &other_size = other.source_size();
double fi = static_cast<double>(this_size.height) / other_size.height;
double fj = static_cast<double>(this_size.width) / other_size.width;
for (int i = 0; i < this_size.height; ++i) {
for (int j = 0; j < this_size.width; ++j) {
if (m_source.is_globally_masked(i, j)) continue;
int ilow = static_cast<int>(std::min(i / fi, static_cast<double>(other_size.height - 1)));
int jlow = static_cast<int>(std::min(j / fj, static_cast<double>(other_size.width - 1)));
auto this_value = mutable_ptr(i, j);
auto other_value = other.ptr(ilow, jlow);
this_value[0] = static_cast<int>(other_value[0] * fi);
this_value[1] = static_cast<int>(other_value[1] * fj);
this_value[2] = _distance(i, j, this_value[0], this_value[1]);
}
}
_randomize_field(max_retry, false);
}
void NearestNeighborField::minimize(int nr_pass) {
const auto &this_size = source_size();
while (nr_pass--) {
for (int i = 0; i < this_size.height; ++i)
for (int j = 0; j < this_size.width; ++j) {
if (m_source.is_globally_masked(i, j)) continue;
if (at(i, j, 2) > 0) _minimize_link(i, j, +1);
}
for (int i = this_size.height - 1; i >= 0; --i)
for (int j = this_size.width - 1; j >= 0; --j) {
if (m_source.is_globally_masked(i, j)) continue;
if (at(i, j, 2) > 0) _minimize_link(i, j, -1);
}
}
}
void NearestNeighborField::_minimize_link(int y, int x, int direction) {
const auto &this_size = source_size();
const auto &this_target_size = target_size();
auto this_ptr = mutable_ptr(y, x);
// propagation along the y direction.
if (y - direction >= 0 && y - direction < this_size.height && !m_source.is_globally_masked(y - direction, x)) {
int yp = at(y - direction, x, 0) + direction;
int xp = at(y - direction, x, 1);
int dp = _distance(y, x, yp, xp);
if (dp < at(y, x, 2)) {
this_ptr[0] = yp, this_ptr[1] = xp, this_ptr[2] = dp;
}
}
// propagation along the x direction.
if (x - direction >= 0 && x - direction < this_size.width && !m_source.is_globally_masked(y, x - direction)) {
int yp = at(y, x - direction, 0);
int xp = at(y, x - direction, 1) + direction;
int dp = _distance(y, x, yp, xp);
if (dp < at(y, x, 2)) {
this_ptr[0] = yp, this_ptr[1] = xp, this_ptr[2] = dp;
}
}
// random search with a progressive step size.
int random_scale = (std::min(this_target_size.height, this_target_size.width) - 1) / 2;
while (random_scale > 0) {
int yp = this_ptr[0] + (rand() % (2 * random_scale + 1) - random_scale);
int xp = this_ptr[1] + (rand() % (2 * random_scale + 1) - random_scale);
yp = clamp(yp, 0, target_size().height - 1);
xp = clamp(xp, 0, target_size().width - 1);
if (m_target.is_globally_masked(yp, xp)) {
random_scale /= 2;
}
int dp = _distance(y, x, yp, xp);
if (dp < at(y, x, 2)) {
this_ptr[0] = yp, this_ptr[1] = xp, this_ptr[2] = dp;
}
random_scale /= 2;
}
}
const int PatchDistanceMetric::kDistanceScale = 65535;
const int PatchSSDDistanceMetric::kSSDScale = 9 * 255 * 255;
namespace {
inline int pow2(int i) {
return i * i;
}
int distance_masked_images(
const MaskedImage &source, int ys, int xs,
const MaskedImage &target, int yt, int xt,
int patch_size
) {
long double distance = 0;
long double wsum = 0;
source.compute_image_gradients();
target.compute_image_gradients();
auto source_size = source.size();
auto target_size = target.size();
for (int dy = -patch_size; dy <= patch_size; ++dy) {
const int yys = ys + dy, yyt = yt + dy;
if (yys <= 0 || yys >= source_size.height - 1 || yyt <= 0 || yyt >= target_size.height - 1) {
distance += (long double)(PatchSSDDistanceMetric::kSSDScale) * (2 * patch_size + 1);
wsum += 2 * patch_size + 1;
continue;
}
const auto *p_si = source.image().ptr<unsigned char>(yys, 0);
const auto *p_ti = target.image().ptr<unsigned char>(yyt, 0);
const auto *p_sm = source.mask().ptr<unsigned char>(yys, 0);
const auto *p_tm = target.mask().ptr<unsigned char>(yyt, 0);
const unsigned char *p_sgm = nullptr;
const unsigned char *p_tgm = nullptr;
if (!source.global_mask().empty()) {
p_sgm = source.global_mask().ptr<unsigned char>(yys, 0);
p_tgm = target.global_mask().ptr<unsigned char>(yyt, 0);
}
const auto *p_sgy = source.grady().ptr<unsigned char>(yys, 0);
const auto *p_tgy = target.grady().ptr<unsigned char>(yyt, 0);
const auto *p_sgx = source.gradx().ptr<unsigned char>(yys, 0);
const auto *p_tgx = target.gradx().ptr<unsigned char>(yyt, 0);
for (int dx = -patch_size; dx <= patch_size; ++dx) {
int xxs = xs + dx, xxt = xt + dx;
wsum += 1;
if (xxs <= 0 || xxs >= source_size.width - 1 || xxt <= 0 || xxt >= source_size.width - 1) {
distance += PatchSSDDistanceMetric::kSSDScale;
continue;
}
if (p_sm[xxs] || p_tm[xxt] || (p_sgm && p_sgm[xxs]) || (p_tgm && p_tgm[xxt]) ) {
distance += PatchSSDDistanceMetric::kSSDScale;
continue;
}
int ssd = 0;
for (int c = 0; c < 3; ++c) {
int s_value = p_si[xxs * 3 + c];
int t_value = p_ti[xxt * 3 + c];
int s_gy = p_sgy[xxs * 3 + c];
int t_gy = p_tgy[xxt * 3 + c];
int s_gx = p_sgx[xxs * 3 + c];
int t_gx = p_tgx[xxt * 3 + c];
ssd += pow2(static_cast<int>(s_value) - t_value);
ssd += pow2(static_cast<int>(s_gx) - t_gx);
ssd += pow2(static_cast<int>(s_gy) - t_gy);
}
distance += ssd;
}
}
distance /= (long double)(PatchSSDDistanceMetric::kSSDScale);
int res = int(PatchDistanceMetric::kDistanceScale * distance / wsum);
if (res < 0 || res > PatchDistanceMetric::kDistanceScale) return PatchDistanceMetric::kDistanceScale;
return res;
}
}
int PatchSSDDistanceMetric::operator ()(const MaskedImage &source, int source_y, int source_x, const MaskedImage &target, int target_y, int target_x) const {
return distance_masked_images(source, source_y, source_x, target, target_y, target_x, m_patch_size);
}
int DebugPatchSSDDistanceMetric::operator ()(const MaskedImage &source, int source_y, int source_x, const MaskedImage &target, int target_y, int target_x) const {
fprintf(stderr, "DebugPatchSSDDistanceMetric: %d %d %d %d\n", source.size().width, source.size().height, m_width, m_height);
return distance_masked_images(source, source_y, source_x, target, target_y, target_x, m_patch_size);
}
int RegularityGuidedPatchDistanceMetricV1::operator ()(const MaskedImage &source, int source_y, int source_x, const MaskedImage &target, int target_y, int target_x) const {
double dx = remainder(double(source_x - target_x) / source.size().width, m_dx1);
double dy = remainder(double(source_y - target_y) / source.size().height, m_dy2);
double score1 = sqrt(dx * dx + dy *dy) / m_scale;
if (score1 < 0 || score1 > 1) score1 = 1;
score1 *= PatchDistanceMetric::kDistanceScale;
double score2 = distance_masked_images(source, source_y, source_x, target, target_y, target_x, m_patch_size);
double score = score1 * m_weight + score2 / (1 + m_weight);
return static_cast<int>(score / (1 + m_weight));
}
int RegularityGuidedPatchDistanceMetricV2::operator ()(const MaskedImage &source, int source_y, int source_x, const MaskedImage &target, int target_y, int target_x) const {
if (target_y < 0 || target_y >= target.size().height || target_x < 0 || target_x >= target.size().width)
return PatchDistanceMetric::kDistanceScale;
int source_scale = m_ijmap.size().height / source.size().height;
int target_scale = m_ijmap.size().height / target.size().height;
// fprintf(stderr, "RegularityGuidedPatchDistanceMetricV2 %d %d %d %d\n", source_y * source_scale, m_ijmap.size().height, source_x * source_scale, m_ijmap.size().width);
double score1 = PatchDistanceMetric::kDistanceScale;
if (!source.is_globally_masked(source_y, source_x) && !target.is_globally_masked(target_y, target_x)) {
auto source_ij = m_ijmap.ptr<float>(source_y * source_scale, source_x * source_scale);
auto target_ij = m_ijmap.ptr<float>(target_y * target_scale, target_x * target_scale);
float di = fabs(source_ij[0] - target_ij[0]); if (di > 0.5) di = 1 - di;
float dj = fabs(source_ij[1] - target_ij[1]); if (dj > 0.5) dj = 1 - dj;
score1 = sqrt(di * di + dj *dj) / 0.707;
if (score1 < 0 || score1 > 1) score1 = 1;
score1 *= PatchDistanceMetric::kDistanceScale;
}
double score2 = distance_masked_images(source, source_y, source_x, target, target_y, target_x, m_patch_size);
double score = score1 * m_weight + score2;
return int(score / (1 + m_weight));
}
|