QPixmap ImageFilter::operator ()(QPixmap sourcePixmap, Filter::FilterType filter, int delta)
{
QImage origin(sourcePixmap.toImage());
switch (filter)
{
case Filter::Gray_Scale:
return grayScale(origin);
break;
case Filter::Brightness:
return brightness(origin, delta);
break;
case Filter::Temperature:
return temperature(origin, delta);
break;
case Filter::Saturation:
return saturate(origin, delta);
break;
case Filter::Blur:
return blur(origin);
break;
case Filter::Sharpen:
return sharpen(origin);
break;
case Filter::Sepia:
return sepia(origin);
break;
}
}
int main( int argc, char* argv[] )
{
int i;
int resr, resg, resb;
int results_data_r[DATA_SIZE][DATA_SIZE];
int results_data_g[DATA_SIZE][DATA_SIZE];
int results_data_b[DATA_SIZE][DATA_SIZE];
int cycles, insts;
cycles = getTime();
insts = getInsts();
for (i = 0; i < DATA_SIZE; i++)
{
sharpen( input_data_r, input_data_g, input_data_b,
results_data_r, results_data_g, results_data_b);
}
cycles = getTime() - cycles;
insts = getInsts() - insts;
printStr("Cycles = "); printInt(cycles); printChar('\n');
printStr("Insts = "); printInt(insts); printChar('\n');
// Check the results
resr = verify(results_data_r, verify_data_r);
resg = verify(results_data_g, verify_data_g);
resb = verify(results_data_b, verify_data_b);
return (resr != 1 || resg != 1 || resb != 1);
}
void imageturn(Mat imagein,Mat &imageout)//将rgb转化hsv，然后改变hsv图像。
{
IplImage imgtemp=imagein;
IplImage* src =cvCloneImage(&imgtemp);
IplImage* floathsv = NULL;
IplImage* floatimgH = NULL;
IplImage* floatimgS = NULL;
IplImage* floatimgV = NULL;
IplImage* floatimgZ = NULL;
CvSize size = cvGetSize( src );
IplImage* imgout=cvCreateImage( size, 8, 3 );
floathsv = cvCreateImage( size, 8, 3 );
floatimgH = cvCreateImage( size, 8, 1 );
floatimgS = cvCreateImage( size,8, 1 );
floatimgV = cvCreateImage( size, 8, 1 );
floatimgZ = cvCreateImage( size, 8, 1 );
cvCvtColor(src,floathsv,CV_BGR2HSV);
cvSplit( floathsv, floatimgH, floatimgS, floatimgV, NULL);
Mat V(floatimgV,true);
Mat Vout;
sharpen(V,Vout);
imgtemp=Vout;
floatimgV=cvCloneImage(&imgtemp);
cvSmooth(floatimgV, floatimgZ, CV_MEDIAN);//中值滤波
cvEqualizeHist( floatimgZ, floatimgV ); //直方图均衡化
cvMerge( floatimgH, floatimgS, floatimgV,0,imgout);
Mat M(imgout,true);
imageout=M;
}
int main() {
Imagem* img;
int opcao = 1;
int i=0,j=0;
int limiar=-1;
char nome[255];
int grau=0;
while (opcao != 0) {
opcao = mostrar_menu();
if (opcao == 1) {
printf("Nome do arquivo: ");
scanf("%s", nome);
img = ler_imagem(nome);
} else if (opcao == 2) {
img = blur(img);
} else if (opcao == 3) {
img = sharpen(img);
} else if(opcao == 4){
img = borda(img);
}else if(opcao == 5){
printf("Digite o limiar: ");
scanf("%i", &limiar);
img = binarizacao_imagem(img, limiar);
}else if(opcao == 6){
printf("Grau de rotacao (90, 180 ou 270º): ");
scanf("%i", &grau);
if(grau == 90){
img = rotacionar90(img);
}else if(grau == 180){
img = rotacionar180(img);
}else if(grau == 270){
img = rotacionar270(img);
}else{
printf("O grau informado nao e permitido.");
}
}else if(opcao == 7){
img = zoom2x(img);
}else if(opcao == 8){
img = reduzir2x(img);
}else if(opcao == 9){
img = gaussianblur(img);
}else if (opcao == 10){
printf("Nome do arquivo: ");
scanf("%s", nome);
salvar_imagem(img, nome);
}else{
printf("Opção inválida.");
}
}
return 0;
}
static void _sharpen(QString sourceFile, QString destFile)
{
QImage image(sourceFile);
if(image.isNull())
{
qDebug() << "load " << sourceFile << " failed! ";
return;
}
int width = image.width();
int height = image.height();
int threshold = 80;
QImage sharpen(width, height, QImage::Format_ARGB32);
int r, g, b, gradientR, gradientG, gradientB;
QRgb rgb00, rgb01, rgb10;
for(int i = 0; i < width; i++)
{
for(int j= 0; j < height; j++)
{
if(image.valid(i, j) &&
image.valid(i+1, j) &&
image.valid(i, j+1))
{
rgb00 = image.pixel(i, j);
rgb01 = image.pixel(i, j+1);
rgb10 = image.pixel(i+1, j);
r = qRed(rgb00);
g = qGreen(rgb00);
b = qBlue(rgb00);
gradientR = abs(r - qRed(rgb01)) + abs(r - qRed(rgb10));
gradientG = abs(g - qGreen(rgb01)) + abs(g - qGreen(rgb10));
gradientB = abs(b - qBlue(rgb01)) + abs(b - qBlue(rgb10));
if(gradientR > threshold)
{
r = qMin(gradientR + 100, 255);
}
if(gradientG > threshold)
{
g = qMin( gradientG + 100, 255);
}
if(gradientB > threshold)
{
b = qMin( gradientB + 100, 255);
}
sharpen.setPixel(i, j, qRgb(r, g, b));
}
}
}
sharpen.save(destFile);
}
int main()
{
cv::Mat image= cv::imread("boldt.jpg");
if (!image.data)
return 0;
// image is resize for book printing
cv::resize(image, image, cv::Size(), 0.6, 0.6);
cv::Mat result;
double time= static_cast<double>(cv::getTickCount());
sharpen(image, result);
time= (static_cast<double>(cv::getTickCount())-time)/cv::getTickFrequency();
std::cout << "time= " << time << std::endl;
cv::namedWindow("Image");
cv::imshow("Image",result);
// open the image in gray-level
image= cv::imread("boldt.jpg",0);
// image is resize for book printing
cv::resize(image, image, cv::Size(), 0.6, 0.6);
time = static_cast<double>(cv::getTickCount());
sharpenIterator(image, result);
time= (static_cast<double>(cv::getTickCount())-time)/cv::getTickFrequency();
std::cout << "time 3= " << time << std::endl;
cv::namedWindow("Sharpened Image");
cv::imshow("Sharpened Image",result);
image= cv::imread("boldt.jpg");
// image is resize for book printing
cv::resize(image, image, cv::Size(), 0.6, 0.6);
time = static_cast<double>(cv::getTickCount());
sharpen2D(image, result);
time= (static_cast<double>(cv::getTickCount())-time)/cv::getTickFrequency();
std::cout << "time 2D= " << time << std::endl;
cv::namedWindow("Image 2D");
cv::imshow("Image 2D",result);
cv::waitKey();
return 0;
}
/* Generate pixel and capture into table */
static ntsc_rgb_t* gen_pixel( ntsc_to_rgb_t* ntsc, int ntsc_pos, int rescaled_pos, ntsc_rgb_t* out )
{
ntsc_to_rgb( ntsc, composite_border + ntsc_pos, ntsc->rgb [rgb_pad] );
rescale( ntsc->rgb [0], rescaled_size, ntsc->rescaled [1] );
sharpen( ntsc->rescaled [1], ntsc->sharpness, rescaled_size, ntsc->rescaled [0] );
{
short const* in = ntsc->rescaled [rescaled_pos];
int n = rgb_kernel_size;
while ( n-- )
{
*out++ = MAKE_KRGB( in [0], in [1], in [2] );
in += 3;
}
}
return out;
}
int main(int argc, char *argv[])
{
QCoreApplication a(argc, argv);
cv::Mat image = cv::imread("/Users/Haoyang/Downloads/boldtgray.jpg");
cv::Mat result;
sharpen(image,result);
cv::namedWindow("sharpen");
imshow("sharpen",result);
cv::namedWindow("2D");
sharpen2D(image,result);
imshow("2D",result);
return a.exec();
}
/*
水彩效果平滑图像的不规则部分，然后强调色彩边界
（grayscale or color image, 8- or 24-bit. ）
*/
BOOL VPicEx::WaterColor()
{
imgdes *srcimg=GetImgDes();
imgdes tmpsrc;
int cols, rows, rcode;
double gamma = 0.7;
cols = CALC_WIDTH(srcimg);
rows = CALC_HEIGHT(srcimg);
allocimage(&tmpsrc, cols, rows, srcimg->bmh->biBitCount);
copyimage(srcimg, &tmpsrc);
gammabrighten(gamma, &tmpsrc, &tmpsrc);
removenoise(&tmpsrc, &tmpsrc);
removenoise(&tmpsrc, &tmpsrc);
removenoise(&tmpsrc, &tmpsrc);
sharpen(&tmpsrc, &tmpsrc);
rcode = copyimage(&tmpsrc, srcimg);
freeimage(&tmpsrc);
return(rcode == NO_ERROR);
}
QImage ImgConvolutions::applyConvolution(convolutionList op, QImage *img1, int filterSize){
switch(op){
case CONV_PASABAJOS:
return pasaBajos(img1, filterSize);
case CONV_BARTLETT:
case CONV_GAUSSIANO:
case CONV_SHARPEN:
return sharpen(img1, filterSize);
case CONV_MOTIONBLUR:
return motionBlur(img1, filterSize);
case CONV_PASAALTOS:
return pasaAltos(img1, filterSize);
case CONV_SOBEL:
return sobel(img1);
case CONV_PA_LPv4:
return laplacianov4(img1);
case CONV_PA_LPv8:
return laplacianov8(img1);
}
return QImage();
}
int main()
{
cv::Mat image = cv::imread("../images/boldt.jpg", 0);
if (!image.data)
return 0;
cv::Mat result;
result.create(image.size(), image.type());
double time = static_cast<double>(cv::getTickCount());
sharpen(image, result);
time = (static_cast<double>(cv::getTickCount()) - time) / cv::getTickFrequency();
std::cout << "time= " << time << std::endl;
cv::namedWindow("Image");
cv::imshow("Image", result);
image = cv::imread("../images/boldt.jpg", 0);
time = static_cast<double>(cv::getTickCount());
sharpen3(image, result);
time = (static_cast<double>(cv::getTickCount()) - time) / cv::getTickFrequency();
std::cout << "time 3= " << time << std::endl;
cv::namedWindow("Image 3");
cv::imshow("Image 3", result);
image = cv::imread("../images/boldt.jpg", 0);
time = static_cast<double>(cv::getTickCount());
sharpen2D(image, result);
time = (static_cast<double>(cv::getTickCount()) - time) / cv::getTickFrequency();
std::cout << "time 2D= " << time << std::endl;
cv::namedWindow("Image 2D");
cv::imshow("Image 2D", result);
cv::waitKey();
return 0;
}
int main(int argc, char *argv[])
{
if (argc != 4)
{
cout << "Usage: " << argv[0] << " cpu|gpu out_func out_prefix" << endl;
return 1;
}
ImageParam input(UInt(8), 3, "input");
Func clamped("clamped");
Func convolved("convolved");
Func sharpen("sharpen");
Var c("c"), x("x"), y("y");
// Algorithm
clamped(x, y, c) = input(
clamp(x, 0, input.width()-1),
clamp(y, 0, input.height()-1),
c) / 255.f;
Image<int16_t> kernel(3, 3);
kernel(0, 0) = -1;
kernel(0, 1) = -1;
kernel(0, 2) = -1;
kernel(1, 0) = -1;
kernel(1, 1) = 8;
kernel(1, 2) = -1;
kernel(2, 0) = -1;
kernel(2, 1) = -1;
kernel(2, 2) = -1;
RDom r(kernel);
convolved(x, y, c) += kernel(r.x, r.y) * clamped(x + r.x - 1, y + r.y - 1, c);
sharpen(x, y, c) = u8(
clamp(convolved(x, y, c)/8 + clamped(x, y, c), 0, 1) * 255
);
// Channel order
input.set_stride(0, 4);
input.set_extent(2, 4);
sharpen.reorder_storage(c, x, y);
sharpen.output_buffer().set_stride(0, 4);
sharpen.output_buffer().set_extent(2, 4);
// Schedules
if (!strcmp(argv[1], "cpu"))
{
sharpen.parallel(y).vectorize(c, 4);
}
else if (!strcmp(argv[1], "gpu"))
{
sharpen.cuda_tile(x, y, 16, 4);
}
else
{
cout << "Invalid schedule type '" << argv[1] << "'" << endl;
return 1;
}
compile(sharpen, input, argv[2], argv[3]);
return 0;
}
static void
run (const gchar *name,
gint nparams,
const GimpParam *param,
gint *nreturn_vals,
GimpParam **return_vals)
{
static GimpParam values[1]; /* Return values */
GimpRunMode run_mode; /* Current run mode */
GimpPDBStatusType status; /* Return status */
GimpDrawable *drawable; /* Current image */
/*
* Initialize parameter data...
*/
status = GIMP_PDB_SUCCESS;
run_mode = param[0].data.d_int32;
INIT_I18N ();
*nreturn_vals = 1;
*return_vals = values;
values[0].type = GIMP_PDB_STATUS;
values[0].data.d_status = status;
/*
* Get drawable information...
*/
drawable = gimp_drawable_get (param[2].data.d_drawable);
gimp_tile_cache_ntiles (2 * drawable->ntile_cols);
/*
* See how we will run
*/
switch (run_mode)
{
case GIMP_RUN_INTERACTIVE:
/*
* Possibly retrieve data...
*/
gimp_get_data (PLUG_IN_PROC, &sharpen_params);
/*
* Get information from the dialog...
*/
if (!sharpen_dialog (drawable))
return;
break;
case GIMP_RUN_NONINTERACTIVE:
/*
* Make sure all the arguments are present...
*/
if (nparams != 4)
status = GIMP_PDB_CALLING_ERROR;
else
sharpen_params.sharpen_percent = param[3].data.d_int32;
break;
case GIMP_RUN_WITH_LAST_VALS:
/*
* Possibly retrieve data...
*/
gimp_get_data (PLUG_IN_PROC, &sharpen_params);
break;
default:
status = GIMP_PDB_CALLING_ERROR;
break;
}
/*
* Sharpen the image...
*/
if (status == GIMP_PDB_SUCCESS)
{
if ((gimp_drawable_is_rgb (drawable->drawable_id) ||
gimp_drawable_is_gray (drawable->drawable_id)))
{
/*
* Run!
*/
sharpen (drawable);
/*
* If run mode is interactive, flush displays...
*/
if (run_mode != GIMP_RUN_NONINTERACTIVE)
gimp_displays_flush ();
/*
* Store data...
*/
if (run_mode == GIMP_RUN_INTERACTIVE)
gimp_set_data (PLUG_IN_PROC,
&sharpen_params, sizeof (SharpenParams));
}
else
status = GIMP_PDB_EXECUTION_ERROR;
}
/*
* Reset the current run status...
*/
values[0].data.d_status = status;
/*
* Detach from the drawable...
*/
gimp_drawable_detach (drawable);
}
int main( int agrc, char** argv )
{
uint8_t *raw;
char *filename = argv[1];
image_width = atoi( argv[2] );
image_height = atoi( argv[3] );
printf( "%s %d %d\n", filename, image_width, image_height );
stride = image_width+2;
raw = read_raw( filename );
write_padded( "padded.raw", raw );
uint8_t *blurred = malloc( stride*(image_height+2)*4 );
clock_t start = clock();
/* Box Blur applied 3 times is extremely similar to Gaussian blur */
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x++ )
{
average_neighbors( raw, blurred, x, y );
}
}
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x++ )
{
average_neighbors( blurred, blurred, x, y );
}
}
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x++ )
{
average_neighbors( blurred, blurred, x, y );
}
}
clock_t end = clock();
float seconds = (float)(end - start) / CLOCKS_PER_SEC;
printf( "Regular box blur took %f seconds\n", seconds );
write_raw( "blurred.raw", blurred );
start = clock();
memset( blurred, 0, stride*(image_height+2)*4 );
/* Box Blur applied 3 times is extremely similar to Gaussian blur */
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x+=2 )
{
average_neighbors_simd( raw, blurred, x, y );
}
}
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x+=2 )
{
average_neighbors_simd( blurred, blurred, x, y );
}
}
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x+=2 )
{
average_neighbors_simd( blurred, blurred, x, y );
}
}
end = clock();
seconds = (float)(end - start) / CLOCKS_PER_SEC;
printf( "SIMD blur took %f seconds\n", seconds );
write_raw( "blurred_simd.raw", blurred );
start = clock();
memset( blurred, 0, stride*(image_height+2)*4 );
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x++ )
{
grayscale( raw, blurred, x, y );
}
}
end = clock();
seconds = (float)(end - start) / CLOCKS_PER_SEC;
printf( "grayscale took %f seconds\n", seconds );
write_raw( "grayscale.raw", blurred );
start = clock();
memset( blurred, 0, stride*(image_height+2)*4 );
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x+=8 )
{
grayscale_simd( raw, blurred, x, y );
}
}
end = clock();
seconds = (float)(end - start) / CLOCKS_PER_SEC;
printf( "grayscale SIMD took %f seconds\n", seconds );
write_raw( "grayscale_simd.raw", blurred );
start = clock();
memset( blurred, 0, stride*(image_height+2)*4 );
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x++ )
{
sharpen( raw, blurred, x, y );
}
}
end = clock();
seconds = (float)(end - start) / CLOCKS_PER_SEC;
printf( "sharpen took %f seconds\n", seconds );
write_raw( "sharpen.raw", blurred );
start = clock();
memset( blurred, 0, stride*(image_height+2)*4 );
for ( int y = 0; y < image_height+2; y++ )
{
for ( int x = 0; x < stride; x++ )
{
sharpen_simd( raw, blurred, x, y );
}
}
end = clock();
seconds = (float)(end - start) / CLOCKS_PER_SEC;
printf( "sharpen SIMD took %f seconds\n", seconds );
write_raw( "sharpen_simd.raw", blurred );
free( raw );
free( blurred );
return 0;
}
static void preview_alt_normal(gint32 image_ID) {
/*******************************************************************************
* Begin H and Normal
******************************************************************************/
gint32 mergedLayer_ID = -1;
gint32 normalmap_ID = -1;
gfloat wsize = (gfloat)gimp_image_width(image_ID);
gfloat hsize = (gfloat)gimp_image_width(image_ID);
/** Get active layer. */
gint32 drawable_temp_ID = gimp_image_get_active_layer(image_ID);
/** Copy active layer. */
/** LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL */
gint32 diffuse_ID = gimp_layer_copy (drawable_temp_ID);
/** Add new layer to image. */
gimp_image_add_layer(image_ID, diffuse_ID, -1);
/** Set new layer as active. */
gimp_image_set_active_layer(image_ID, diffuse_ID);
/** Here I should hide previous active layer, make not visible. */
gtk_label_set_text(GTK_LABEL(progress_label), "Smoothing");
/**
* Since copied, don't need this here.
* blur seems to not create an extra layer.
*/
blur(image_ID, diffuse_ID, wsize, hsize, local_vals.LargeDetails, 0, local_vals.ao);
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.15);
normalmap_ID = gimp_image_get_active_layer(image_ID);
if(local_vals.smoothstep)
{
gtk_label_set_text(GTK_LABEL(progress_label), "Smoothing");
/**
* Filter "Blur" applied
* Standard plug-in. Source code ships with GIMP.
*/
if (plug_in_blur_connector(image_ID, normalmap_ID) != 1) return;
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.20);
}
else
{
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.20);
}
if(local_vals.invh)
{
/**
* Colors Menu->Invert
* Standard plug-in. Source code ships with GIMP.
*/
if (plug_in_vinvert_connector(image_ID, normalmap_ID) != 1) return;
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.25);
}
else
{
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.25);
}
/** Here is _p Displacement drawable. */
pDrawables.drawable_p = gimp_drawable_get(normalmap_ID);
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.30);
/** Extra layer here. */
/** LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL */
gtk_label_set_text(GTK_LABEL(progress_label), "Base Mapping");
doBaseMap(image_ID, diffuse_ID, local_vals.Depth, local_vals.LargeDetails, local_vals.ao);
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.35);
normalmap_ID = gimp_image_get_active_layer(image_ID);
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.40);
/** Here is _ln low normal. l l l l l l l l l l l l l l l l */
if (gcNeedNormal == 'l') {
pDrawables.drawable_n = gimp_drawable_get(normalmap_ID);
}
/** Creates an extra layer. */
/** LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL */
shapeRecognise(image_ID, normalmap_ID, local_vals.ShapeRecog, local_vals.ao);
if(local_vals.smoothstep)
{
normalmap_ID = gimp_image_get_active_layer(image_ID);
gtk_label_set_text(GTK_LABEL(progress_label), "Smoothing");
/**
* Filter "Blur" applied
* Standard plug-in. Source code ships with GIMP.
*/
if (plug_in_blur_connector(image_ID, normalmap_ID) != 1) return;
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.45);
}
else
{
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.45);
}
/** Here is _sn super normal. s s s s s s s s s s s s s s s s */
if (gcNeedNormal == 's') {
pDrawables.drawable_n = gimp_drawable_get(normalmap_ID);
}
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.50);
gtk_label_set_text(GTK_LABEL(progress_label), "Sharpen");
/** Creates an extra layer. */
/** LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL */
sharpen(image_ID, diffuse_ID, local_vals.Depth, 0, local_vals.SmallDetails);
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.55);
normalmap_ID = gimp_image_get_active_layer(image_ID);
gtk_label_set_text(GTK_LABEL(progress_label), "Sharpen more");
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.65);
/**
* Filter Enhance "Sharpen" applied
* Standard plug-in. Source code ships with GIMP.
*/
if (plug_in_sharpen_connector(image_ID, normalmap_ID, 20) != 1) return;
/** Here is _hn high normal. h h h h h h h h h h h h h h h h */
if (gcNeedNormal == 'h') {
pDrawables.drawable_n = gimp_drawable_get(normalmap_ID);
}
gtk_label_set_text(GTK_LABEL(progress_label), "Sharpen again");
/** Creates an extra layer. */
/** LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL */
sharpen(image_ID, diffuse_ID, local_vals.Depth, 6, local_vals.MediumDetails);
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.70);
normalmap_ID = gimp_image_get_active_layer(image_ID);
gtk_label_set_text(GTK_LABEL(progress_label), "Smoothing");
/**
* Filter "Blur" applied
* Standard plug-in. Source code ships with GIMP.
*/
if (plug_in_blur_connector(image_ID, normalmap_ID) != 1) return;
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.75);
/** Here is _mn medium normal m m m m m m m m m m m m m m m m */
if (gcNeedNormal == 'm') {
pDrawables.drawable_n = gimp_drawable_get(normalmap_ID);
}
gtk_progress_bar_set_fraction (GTK_PROGRESS_BAR(progress), 0.78);
gimp_drawable_set_visible(diffuse_ID, 0);
/**
* Don't do the next line:
*
* gimp_image_merge_visible_layers(image_ID, 0);
*
* Do this instead for preview:
*/
mergedLayer_ID = gimp_layer_new_from_visible(image_ID, image_ID, "temp");
/** Add copied layer to image. */
gimp_image_add_layer(image_ID, mergedLayer_ID, -1);
}