#include <memory>
#include "tpixel.h"
#include <stdio.h>
#include "tfxparam.h"
#include <stdlib.h>
#include <math.h>
#include <assert.h>
#include "tpixelutils.h"
#include "trop.h"
#include "stdfx.h"
#include "tgeometry.h"
#include "tfxattributes.h"
#include "tparamuiconcept.h"
// #include "timage_io.h"
/*---------------------------------------------------------------------------*/
namespace {
/*
template<class T>
void overlayPixels(const T& dw, const T& up, T& ris, double glob)
{
int value;
double aux;
int max = T::maxChannelValue;
if (up.m == 0)
ris = dw;
else if ((up.m == max)&&(glob==1))
ris = up;
else if (glob==1)
{
aux = (max-up.m)/max;
value = up.r + troundp(dw.r * aux);
ris.r = (value <max)?value:max;
value = up.g + troundp(dw.g * aux);
ris.g = (value <max)?value:max;
value = up.b + troundp(dw.b * aux);
ris.b = (value <max)?value:max;
value = up.m + dw.m;
ris.m = (value <max)?value:max;
}
else
{
aux = (max-up.m*glob)/max;
value = (int)(up.r*glob) + troundp(dw.r * aux);
ris.r = (value <max)?value:max;
value = (int)(up.g*glob) + troundp(dw.g * aux);
ris.g = (value <max)?value:max;
value = (int)(up.b*glob) + troundp(dw.b * aux);
ris.b = (value <max)?value:max;
value = (int)(up.m*glob) + dw.m;
ris.m = (value <max)?value:max;
}
}
*/
/*---------------------------------------------------------------------------*/
template <class T>
inline void blur_code(T *row1, T *row2, int length, double coeff, double coeffq,
int brad, double diff, double globmatte) {
int i;
double rsum, gsum, bsum, msum;
TPixelD sigma1, sigma2, sigma3, desigma;
T *pix1, *pix2, *pix3, *pix4;
int max = T::maxChannelValue;
pix1 = row1;
pix2 = row1 - 1;
sigma1.r = pix1->r;
sigma1.g = pix1->g;
sigma1.b = pix1->b;
sigma1.m = pix1->m;
pix1++;
sigma2.r = sigma2.g = sigma2.b = sigma2.m = 0.0;
sigma3.r = sigma3.g = sigma3.b = sigma3.m = 0.0;
for (i = 1; i < brad; i++) {
sigma1.r += pix1->r;
sigma1.g += pix1->g;
sigma1.b += pix1->b;
sigma1.m += pix1->m;
sigma2.r += pix2->r;
sigma2.g += pix2->g;
sigma2.b += pix2->b;
sigma2.m += pix2->m;
sigma3.r += i * (pix1->r + pix2->r);
sigma3.g += i * (pix1->g + pix2->g);
sigma3.b += i * (pix1->b + pix2->b);
sigma3.m += i * (pix1->m + pix2->m);
pix1++;
pix2--;
}
rsum = (sigma1.r + sigma2.r) * coeff - sigma3.r * coeffq + 0.5;
gsum = (sigma1.g + sigma2.g) * coeff - sigma3.g * coeffq + 0.5;
bsum = (sigma1.b + sigma2.b) * coeff - sigma3.b * coeffq + 0.5;
msum = (sigma1.m + sigma2.m) * coeff - sigma3.m * coeffq + 0.5;
row2->r = tcrop((int)rsum, 0, max);
row2->g = tcrop((int)gsum, 0, max);
row2->b = tcrop((int)bsum, 0, max);
row2->m = tcrop((int)msum, 0, max);
if (globmatte != 1.0) {
row2->r = (int)(row2->r * globmatte);
row2->g = (int)(row2->g * globmatte);
row2->b = (int)(row2->b * globmatte);
row2->m = (int)(row2->m * globmatte);
}
*row2 = overPix(*row1, *row2);
// overlayPixels<T>(*row1, *row2, *row2, globmatte);
// row2++;
sigma2.r += row1[-brad].r;
sigma2.g += row1[-brad].g;
sigma2.b += row1[-brad].b;
sigma2.m += row1[-brad].m;
pix1 = row1 + brad;
pix2 = row1;
pix3 = row1 - brad;
pix4 = row1 - brad + 1;
desigma.r = sigma1.r - sigma2.r;
desigma.g = sigma1.g - sigma2.g;
desigma.b = sigma1.b - sigma2.b;
desigma.m = sigma1.m - sigma2.m;
for (i = 1; i < length; i++) {
desigma.r += pix1->r - 2 * pix2->r + pix3->r;
desigma.g += pix1->g - 2 * pix2->g + pix3->g;
desigma.b += pix1->b - 2 * pix2->b + pix3->b;
desigma.m += pix1->m - 2 * pix2->m + pix3->m;
rsum += (desigma.r + diff * (pix1->r - pix4->r)) * coeffq;
gsum += (desigma.g + diff * (pix1->g - pix4->g)) * coeffq;
bsum += (desigma.b + diff * (pix1->b - pix4->b)) * coeffq;
msum += (desigma.m + diff * (pix1->m - pix4->m)) * coeffq;
row2->r = tcrop((int)rsum, 0, max);
row2->g = tcrop((int)gsum, 0, max);
row2->b = tcrop((int)bsum, 0, max);
row2->m = tcrop((int)msum, 0, max);
if (globmatte != 1.0) {
row2->r = (int)(row2->r * globmatte);
row2->g = (int)(row2->g * globmatte);
row2->b = (int)(row2->b * globmatte);
row2->m = (int)(row2->m * globmatte);
}
*row2 = overPix(*pix2, *row2);
// overlayPixels<T>(*pix2, *row2, *row2, 0.8);
row2++;
pix1++, pix2++, pix3++, pix4++;
}
}
template <>
inline void blur_code<TPixelF>(TPixelF *row1, TPixelF *row2, int length,
double coeff, double coeffq, int brad,
double diff, double globmatte) {
int i;
double rsum, gsum, bsum, msum;
TPixelD sigma1, sigma2, sigma3, desigma;
TPixelF *pix1, *pix2, *pix3, *pix4;
// int max = T::maxChannelValue;
pix1 = row1;
pix2 = row1 - 1;
sigma1.r = pix1->r;
sigma1.g = pix1->g;
sigma1.b = pix1->b;
sigma1.m = pix1->m;
pix1++;
sigma2.r = sigma2.g = sigma2.b = sigma2.m = 0.0;
sigma3.r = sigma3.g = sigma3.b = sigma3.m = 0.0;
for (i = 1; i < brad; i++) {
sigma1.r += pix1->r;
sigma1.g += pix1->g;
sigma1.b += pix1->b;
sigma1.m += pix1->m;
sigma2.r += pix2->r;
sigma2.g += pix2->g;
sigma2.b += pix2->b;
sigma2.m += pix2->m;
sigma3.r += i * (pix1->r + pix2->r);
sigma3.g += i * (pix1->g + pix2->g);
sigma3.b += i * (pix1->b + pix2->b);
sigma3.m += i * (pix1->m + pix2->m);
pix1++;
pix2--;
}
rsum = (sigma1.r + sigma2.r) * coeff - sigma3.r * coeffq;
gsum = (sigma1.g + sigma2.g) * coeff - sigma3.g * coeffq;
bsum = (sigma1.b + sigma2.b) * coeff - sigma3.b * coeffq;
msum = (sigma1.m + sigma2.m) * coeff - sigma3.m * coeffq;
row2->r = rsum;
row2->g = gsum;
row2->b = bsum;
row2->m = tcrop((float)msum, 0.f, 1.f);
if (globmatte != 1.0) {
row2->r = row2->r * globmatte;
row2->g = row2->g * globmatte;
row2->b = row2->b * globmatte;
row2->m = row2->m * globmatte;
}
*row2 = overPix(*row1, *row2);
// overlayPixels<T>(*row1, *row2, *row2, globmatte);
// row2++;
sigma2.r += row1[-brad].r;
sigma2.g += row1[-brad].g;
sigma2.b += row1[-brad].b;
sigma2.m += row1[-brad].m;
pix1 = row1 + brad;
pix2 = row1;
pix3 = row1 - brad;
pix4 = row1 - brad + 1;
desigma.r = sigma1.r - sigma2.r;
desigma.g = sigma1.g - sigma2.g;
desigma.b = sigma1.b - sigma2.b;
desigma.m = sigma1.m - sigma2.m;
for (i = 1; i < length; i++) {
desigma.r += pix1->r - 2 * pix2->r + pix3->r;
desigma.g += pix1->g - 2 * pix2->g + pix3->g;
desigma.b += pix1->b - 2 * pix2->b + pix3->b;
desigma.m += pix1->m - 2 * pix2->m + pix3->m;
rsum += (desigma.r + diff * (pix1->r - pix4->r)) * coeffq;
gsum += (desigma.g + diff * (pix1->g - pix4->g)) * coeffq;
bsum += (desigma.b + diff * (pix1->b - pix4->b)) * coeffq;
msum += (desigma.m + diff * (pix1->m - pix4->m)) * coeffq;
row2->r = rsum;
row2->g = gsum;
row2->b = bsum;
row2->m = tcrop((float)msum, 0.f, 1.f);
if (globmatte != 1.0) {
row2->r = row2->r * globmatte;
row2->g = row2->g * globmatte;
row2->b = row2->b * globmatte;
row2->m = row2->m * globmatte;
}
*row2 = overPix(*pix2, *row2);
// overlayPixels<T>(*pix2, *row2, *row2, 0.8);
row2++;
pix1++, pix2++, pix3++, pix4++;
}
}
/*---------------------------------------------------------------------------*/
template <class T>
void do_filtering(T *row1, T *row2, int length, double coeff, int brad,
double Mblur, double globmatte) {
int i;
double rsum, gsum, bsum, msum;
TPixelD sigma1, sigma2;
int max = T::maxChannelValue;
sigma1.r = sigma1.g = sigma1.b = sigma1.m = 0.0;
sigma2.r = sigma2.g = sigma2.b = sigma2.m = 0.0;
for (i = 0; i <= brad; i++) {
sigma1.r += row1[-i].r;
sigma1.g += row1[-i].g;
sigma1.b += row1[-i].b;
sigma1.m += row1[-i].m;
sigma2.r += -i * row1[-i].r;
sigma2.g += -i * row1[-i].g;
sigma2.b += -i * row1[-i].b;
sigma2.m += -i * row1[-i].m;
}
for (i = 0; i < length; i++) /* for the ith point the previous computing is
used, with the values */
{
/* stored in the auxiliary variables sigma1 and sigma2. */
rsum = ((Mblur - i) * sigma1.r + sigma2.r) / coeff;
gsum = ((Mblur - i) * sigma1.g + sigma2.g) / coeff;
bsum = ((Mblur - i) * sigma1.b + sigma2.b) / coeff;
msum = ((Mblur - i) * sigma1.m + sigma2.m) / coeff;
row2[i].r = (rsum < max) ? troundp(rsum) : max;
row2[i].g = (gsum < max) ? troundp(gsum) : max;
row2[i].b = (bsum < max) ? troundp(bsum) : max;
row2[i].m = (msum < max) ? troundp(msum) : max;
if (globmatte != 1.0) {
row2[i].r = (int)(row2[i].r * globmatte);
row2[i].g = (int)(row2[i].g * globmatte);
row2[i].b = (int)(row2[i].b * globmatte);
row2[i].m = (int)(row2[i].m * globmatte);
}
row2[i] = overPix(row1[i], row2[i]);
// overlayPixels<T>(row1[i], row2[i], row2[i], globmatte);
if (i < length - 1) {
sigma1.r += row1[i + 1].r - row1[i - brad].r;
sigma1.g += row1[i + 1].g - row1[i - brad].g;
sigma1.b += row1[i + 1].b - row1[i - brad].b;
sigma1.m += row1[i + 1].m - row1[i - brad].m;
sigma2.r += (i + 1) * row2[i + 1].r - (i - brad) * row1[i - brad].r;
sigma2.g += (i + 1) * row2[i + 1].g - (i - brad) * row1[i - brad].g;
sigma2.b += (i + 1) * row2[i + 1].b - (i - brad) * row1[i - brad].b;
sigma2.m += (i + 1) * row2[i + 1].m - (i - brad) * row1[i - brad].m;
}
}
}
template <>
void do_filtering<TPixelF>(TPixelF *row1, TPixelF *row2, int length,
double coeff, int brad, double Mblur,
double globmatte) {
int i;
double rsum, gsum, bsum, msum;
TPixelD sigma1, sigma2;
sigma1.r = sigma1.g = sigma1.b = sigma1.m = 0.0;
sigma2.r = sigma2.g = sigma2.b = sigma2.m = 0.0;
for (i = 0; i <= brad; i++) {
sigma1.r += row1[-i].r;
sigma1.g += row1[-i].g;
sigma1.b += row1[-i].b;
sigma1.m += row1[-i].m;
sigma2.r += -i * row1[-i].r;
sigma2.g += -i * row1[-i].g;
sigma2.b += -i * row1[-i].b;
sigma2.m += -i * row1[-i].m;
}
for (i = 0; i < length; i++) /* for the ith point the previous computing is
used, with the values */
{
/* stored in the auxiliary variables sigma1 and sigma2. */
rsum = ((Mblur - i) * sigma1.r + sigma2.r) / coeff;
gsum = ((Mblur - i) * sigma1.g + sigma2.g) / coeff;
bsum = ((Mblur - i) * sigma1.b + sigma2.b) / coeff;
msum = ((Mblur - i) * sigma1.m + sigma2.m) / coeff;
row2[i].r = rsum;
row2[i].g = gsum;
row2[i].b = bsum;
row2[i].m = std::min(msum, 1.0);
if (globmatte != 1.0) {
row2[i].r = row2[i].r * globmatte;
row2[i].g = row2[i].g * globmatte;
row2[i].b = row2[i].b * globmatte;
row2[i].m = row2[i].m * globmatte;
}
row2[i] = overPix(row1[i], row2[i]);
// overlayPixels<T>(row1[i], row2[i], row2[i], globmatte);
if (i < length - 1) {
sigma1.r += row1[i + 1].r - row1[i - brad].r;
sigma1.g += row1[i + 1].g - row1[i - brad].g;
sigma1.b += row1[i + 1].b - row1[i - brad].b;
sigma1.m += row1[i + 1].m - row1[i - brad].m;
sigma2.r += (double)(i + 1) * row2[i + 1].r -
(double)(i - brad) * row1[i - brad].r;
sigma2.g += (double)(i + 1) * row2[i + 1].g -
(double)(i - brad) * row1[i - brad].g;
sigma2.b += (double)(i + 1) * row2[i + 1].b -
(double)(i - brad) * row1[i - brad].b;
sigma2.m += (double)(i + 1) * row2[i + 1].m -
(double)(i - brad) * row1[i - brad].m;
}
}
}
/*---------------------------------------------------------------------------*/
template <class T>
void takeRow(T *rin, T *row, int lx, int brad, bool bidirectional) {
int i;
for (i = 0; i < lx; i++) row[i] = rin[i];
for (i = -1; i > -brad;
i--) /* pixels equal to the ones of border of image are added */
row[i] = row[0]; /* to avoid a black blur to get into the picture. */
if (bidirectional)
for (i = lx; i < lx + brad;
i++) /* pixels equal to the ones of border of image are added */
row[i] = row[lx - 1]; /* to avoid a black blur to get into the picture. */
}
/*---------------------------------------------------------------------------*/
template <class T>
void doDirectionalBlur(TRasterPT<T> r, double blur, bool bidirectional) {
int i, lx, ly, brad;
double coeff, coeffq, diff, globmatte;
brad = tfloor(blur); /* number of pixels involved in the filtering. */
if (bidirectional) {
coeff =
blur /
(brad - brad * brad +
blur * (2 * brad - 1)); // sum of the weights of triangolar filter.
coeffq = coeff / blur;
diff = blur - brad;
} else
coeff = (brad + 1) * (1 - brad / (2 * blur)) *
blur; /*sum of the weights of triangolar filter. */
lx = r->getLx();
ly = r->getLy();
if ((lx == 0) || (ly == 0)) return;
std::unique_ptr<T[]> row(new T[lx + 2 * brad + 2]);
if (!row) return;
memset(row.get(), 0, (lx + 2 * brad + 2) * sizeof(T));
globmatte = 0.8; /* a little bit of transparency is also added */
r->lock();
for (i = 0; i < ly; i++) {
T *buffer = (T *)r->pixels(i);
takeRow(buffer, row.get() + brad, lx, brad, bidirectional);
if (bidirectional)
blur_code<T>(row.get() + brad, buffer, lx, coeff, coeffq, brad, diff,
globmatte);
else
do_filtering<T>(row.get() + brad, buffer, lx, coeff, brad, blur,
globmatte);
}
r->unlock();
}
/*---------------------------------------------------------------------------*/
template <class T>
void directionalBlur(TRasterPT<T> rout, TRasterPT<T> rin, const TPointD &blur,
const TPoint &offset, bool bidirectional) {
double cs, sn, cx_aux, cy_aux;
int lx, ly, lx_aux, ly_aux;
double blurValue = tdistance(TPointD(), blur);
lx = rin->getLx();
ly = rin->getLy();
cs = blur.x / blurValue;
sn = blur.y / blurValue;
lx_aux = (int)tceil(lx * fabs(cs) + ly * fabs(sn));
ly_aux = (int)tceil(lx * fabs(sn) + ly * fabs(cs));
cx_aux = lx_aux * .5;
cy_aux = ly_aux * .5;
TRasterPT<T> raux = TRasterPT<T>(lx_aux, ly_aux);
TAffine rot(cs, sn, 0, -sn, cs, 0);
rot = rot.place(convert(rin->getCenter()), convert(raux->getCenter()));
TRop::resample(raux, rin, rot);
doDirectionalBlur<T>(raux, blurValue, bidirectional);
TAffine rotInv(cs, -sn, 0, sn, cs, 0);
rotInv = rotInv.place(convert(raux->getCenter()),
convert(rin->getCenter() + offset));
TRop::resample(rout, raux, rotInv);
}
} // namespace
static void enlargeDir(TRectD &r, TPointD p, bool bidirectional) {
if (bidirectional) {
r.x1 += fabs(p.x);
r.x0 -= fabs(p.x);
r.y1 += fabs(p.y);
r.y0 -= fabs(p.y);
} else {
if (p.x > 0)
r.x1 += p.x;
else
r.x0 -= -p.x;
if (p.y > 0)
r.y1 += p.y;
else
r.y0 -= -p.y;
}
}
static void reduceDir(TRectD &r, TPointD p, bool bidirectional) {
if (bidirectional) {
r.x1 -= fabs(p.x);
r.x0 += fabs(p.x);
r.y1 -= fabs(p.y);
r.y0 += fabs(p.y);
} else {
if (p.x > 0)
r.x1 -= p.x;
else
r.x0 += -p.x;
if (p.y > 0)
r.y1 -= p.y;
else
r.y0 += -p.y;
}
}
class DirectionalBlurBaseFx : public TStandardRasterFx {
// FX_PLUGIN_DECLARATION(DirectionalBlurBaseFx)
protected:
bool m_isMotionBlur;
TRasterFxPort m_input;
TDoubleParamP m_angle;
TDoubleParamP m_intensity;
TBoolParamP m_bidirectional;
TBoolParamP m_spread;
// TBoolParamP m_useSSE;
public:
bool doGetBBox(double frame, TRectD &bBox,
const TRenderSettings &info) override;
DirectionalBlurBaseFx(bool isMotionBLur)
: m_isMotionBlur(isMotionBLur)
, m_angle(0.0)
, m_intensity(10.0)
, m_bidirectional(false)
, m_spread(true) {
bindParam(this, "intensity", m_intensity);
bindParam(this, "bidirectional", m_bidirectional);
bindParam(this, "spread", m_spread);
addInputPort("Source", m_input);
m_intensity->setValueRange(0, (std::numeric_limits<double>::max)());
getAttributes()->setIsSpeedAware(true);
enableComputeInFloat(true);
}
TPointD getBlurVector(double frame) const {
TPointD speed = getAttributes()->getSpeed();
double value = m_intensity->getValue(frame);
return value * speed;
}
~DirectionalBlurBaseFx(){};
void doCompute(TTile &tile, double frame, const TRenderSettings &) override;
bool canHandle(const TRenderSettings &info, double frame) override {
return isAlmostIsotropic(info.m_affine) ||
m_intensity->getValue(frame) == 0;
}
int getMemoryRequirement(const TRectD &rect, double frame,
const TRenderSettings &info) override;
};
class DirectionalBlurFx final : public DirectionalBlurBaseFx
{
FX_PLUGIN_DECLARATION(DirectionalBlurFx)
public:
DirectionalBlurFx() : DirectionalBlurBaseFx(false) {
m_intensity->setMeasureName("fxLength");
m_angle->setMeasureName("angle");
bindParam(this, "angle", m_angle);
}
void getParamUIs(TParamUIConcept *&concepts, int &length) override {
concepts = new TParamUIConcept[length = 1];
concepts[0].m_type = TParamUIConcept::POLAR;
concepts[0].m_label = "Angle and Intensity";
concepts[0].m_params.push_back(m_angle);
concepts[0].m_params.push_back(m_intensity);
}
};
class MotionBlurFx final : public DirectionalBlurBaseFx
{
FX_PLUGIN_DECLARATION(MotionBlurFx)
public:
MotionBlurFx() : DirectionalBlurBaseFx(true) {}
std::string getAlias(double frame,
const TRenderSettings &info) const override {
std::string alias = getFxType();
alias += "[";
// alias of the effects related to the input ports separated by commas
// a port that is not connected to an alias blank (empty string)
int i;
for (i = 0; i < getInputPortCount(); i++) {
TFxPort *port = getInputPort(i);
if (port->isConnected()) {
TRasterFxP ifx = port->getFx();
assert(ifx);
alias += ifx->getAlias(frame, info);
}
alias += ",";
}
unsigned long id = getIdentifier();
double value = m_intensity->getValue(frame);
return alias + std::to_string(id) + "," + std::to_string(frame) + "," +
std::to_string(value) + "]";
}
};
//-------------------------------------------------------------------
bool DirectionalBlurBaseFx::doGetBBox(double frame, TRectD &bBox,
const TRenderSettings &info) {
if (m_input.isConnected()) {
bool ret = m_input->doGetBBox(frame, bBox, info);
if (m_spread->getValue()) {
TPointD blur;
if (m_isMotionBlur)
blur = getBlurVector(frame);
else {
double angle = m_angle->getValue(frame) * M_PI_180;
blur.x = m_intensity->getValue(frame) * cos(angle);
blur.y = m_intensity->getValue(frame) * sin(angle);
}
enlargeDir(bBox, blur, m_bidirectional->getValue());
}
return ret;
} else {
bBox = TRectD();
return false;
}
}
//-------------------------------------------------------------------
void DirectionalBlurBaseFx::doCompute(TTile &tile, double frame,
const TRenderSettings &ri) {
if (!m_input.isConnected()) return;
TPointD blurVector;
if (m_isMotionBlur) {
blurVector = getBlurVector(frame);
} else {
double angle = m_angle->getValue(frame) * M_PI_180;
blurVector.x = m_intensity->getValue(frame) * cos(angle);
blurVector.y = m_intensity->getValue(frame) * sin(angle);
}
const double limit = 900.0;
blurVector.x = tcrop(blurVector.x, -limit, limit);
blurVector.y = tcrop(blurVector.y, -limit, limit);
double shrink = (ri.m_shrinkX + ri.m_shrinkY) / 2.0;
TAffine aff = ri.m_affine;
aff.a13 = aff.a23 = 0;
TPointD blur = (1.0 / shrink) * (aff * blurVector);
double blurValue = norm(blur);
if (areAlmostEqual(blurValue, 0, 1e-3)) {
m_input->compute(tile, frame, ri);
return;
}
TRectD rectTile = TRectD(tile.m_pos, TDimensionD(tile.getRaster()->getLx(),
tile.getRaster()->getLy()));
if (!rectTile.isEmpty()) {
TRectD bboxIn;
m_input->getBBox(frame, bboxIn, ri);
if (bboxIn == TConsts::infiniteRectD) bboxIn = rectTile;
TPointD blur = (1.0 / shrink) * (aff * blurVector);
// enlarge must be bidirectional, because we need pixel on the other side of
// blur
enlargeDir(bboxIn, blur, true);
rectTile = bboxIn * rectTile.enlarge(fabs(blur.x), fabs(blur.y));
TRect rectIn;
rectIn.x0 = tfloor(rectTile.x0);
rectIn.y0 = tfloor(rectTile.y0);
rectIn.x1 = tceil(rectTile.x1);
rectIn.y1 = tceil(rectTile.y1);
int rasInLx = rectIn.getLx();
int rasInLy = rectIn.getLy();
TTile tileIn;
m_input->allocateAndCompute(tileIn, convert(rectIn.getP00()),
TDimension(rasInLx, rasInLy), tile.getRaster(),
frame, ri);
TRasterP rasIn = tileIn.getRaster();
TRect rectOut =
rasIn->getBounds() + (rectIn.getP00() - convert(tile.m_pos));
TRasterP rasOut = tile.getRaster()->extract(rectOut);
TPoint p;
if (rectIn.x0 < tile.m_pos.x) p.x = rectIn.x0 - tile.m_pos.x;
if (rectIn.y0 < tile.m_pos.y) p.y = rectIn.y0 - tile.m_pos.y;
if ((TRaster32P)rasIn && (TRaster32P)rasOut)
directionalBlur<TPixel32>(rasOut, rasIn, blur, p,
m_bidirectional->getValue());
else if ((TRaster64P)rasIn && (TRaster64P)rasOut)
directionalBlur<TPixel64>(rasOut, rasIn, blur, p,
m_bidirectional->getValue());
else if ((TRasterFP)rasIn && (TRasterFP)rasOut)
directionalBlur<TPixelF>(rasOut, rasIn, blur, p,
m_bidirectional->getValue());
}
}
//---------------------------------------------------------------------------
int DirectionalBlurBaseFx::getMemoryRequirement(const TRectD &rect,
double frame,
const TRenderSettings &info) {
TPointD blurVector;
if (m_isMotionBlur) {
blurVector = getBlurVector(frame);
} else {
double angle = m_angle->getValue(frame) * M_PI_180;
blurVector.x = m_intensity->getValue(frame) * cos(angle);
blurVector.y = m_intensity->getValue(frame) * sin(angle);
}
const double limit = 900.0;
blurVector.x = tcrop(blurVector.x, -limit, limit);
blurVector.y = tcrop(blurVector.y, -limit, limit);
double shrink = (info.m_shrinkX + info.m_shrinkY) / 2.0;
TAffine aff = info.m_affine;
aff.a13 = aff.a23 = 0;
TPointD blur = (1.0 / shrink) * (aff * blurVector);
return TRasterFx::memorySize(rect.enlarge(blur.x, blur.y), info.m_bpp);
}
//---------------------------------------------------------------------------
FX_PLUGIN_IDENTIFIER(DirectionalBlurFx, "directionalBlurFx");
FX_PLUGIN_IDENTIFIER(MotionBlurFx, "motionBlurFx");