Bunch* SMPBunchConstructor::ConstructBunch (int) const
{
SMPBunch* bunch = new SMPBunch(beamdat.p0,beamdat.charge);
// First, store the dispersion correlations and set them to
// zero.
BeamData bd = beamdat;
bd.Dx=bd.Dxp=bd.Dy=bd.Dyp=0.0;
double dx = beamdat.Dx;
double dxp = beamdat.Dxp;
double dy = beamdat.Dy;
double dyp = beamdat.Dyp;
PSmoments S = BeamDataToSigmaMtrx(bd);
// the macroparticles are constructed to represent the
// total charge in a bin of width 6sigma/ns
double q0 = beamdat.charge;
double qt = 0;
vector<double> zdist(ns);
vector<double> dpdist(np);
MakeDistribution(nSigZ,zdist);
MakeDistribution(nSigDP,dpdist);
double dz = 2*nSigZ*beamdat.sig_z/ns;
double ddp = 2*nSigDP*beamdat.sig_dp/np;
double z =-nSigZ*beamdat.sig_z+dz/2;
for(size_t nSlice = 0; nSlice<ns; nSlice++, z+=dz)
{
double dp = -nSigDP*beamdat.sig_dp+ddp/2.0;
for(size_t nPart = 0; nPart<np; nPart++,dp+=ddp)
{
double q = q0*zdist[nSlice]*dpdist[nPart];
SliceMacroParticle m(S,z,dp,q);
// Add dispersion correlations to centroid
m.x() += dx*dp;
m.xp()+= dxp*dp;
m.y() += dy*dp;
m.yp()+= dyp*dp;
bunch->AddParticle(m);
qt+=q;
}
}
//cout<<"total generated charge = "<<qt<<endl;
PSvector x0;
bunch->GetCentroid(x0);
return bunch;
}
/**
* Program entry-point.
*
*/
int main(int argc, char **argv) {
// parse arguments
while (true) {
int index = -1;
getopt_long(argc, argv, "", options, &index);
if (index == -1) {
if (argc != optind + 2) {
usage();
return 1;
}
input_file = argv[optind++];
if (access(input_file, R_OK)) {
fprintf(stderr, "Error: input file not readable: %s\n", input_file);
return 2;
}
output_file = argv[optind++];
if (access(output_file, W_OK) && errno == EACCES) {
fprintf(stderr, "Error: output file not writable: %s\n", output_file);
return 2;
}
break;
}
switch (index) {
case OPTION_WIDTH:
sample_width = atoi(optarg);
break;
case OPTION_HEIGHT:
sample_height = atoi(optarg);
break;
case OPTION_COUNT:
sample_count = atoi(optarg);
break;
case OPTION_ROTATE_STDDEV_X:
rotate_stddev_x = atof(optarg) / 180.0 * M_PI;
break;
case OPTION_ROTATE_STDDEV_Y:
rotate_stddev_y = atof(optarg) / 180.0 * M_PI;
break;
case OPTION_ROTATE_STDDEV_Z:
rotate_stddev_z = atof(optarg) / 180.0 * M_PI;
break;
case OPTION_LUMINOSITY_STDDEV:
luminosity_stddev = atof(optarg);
break;
case OPTION_BACKGROUNDS:
backgrounds_file = optarg;
if (access(backgrounds_file, R_OK)) {
fprintf(stderr, "Error: backgrounds file not readable: %s\n", backgrounds_file);
return 2;
}
break;
default:
usage();
return 1;
}
}
// read input files
std::vector<std::string> samples;
if (!parseFiles(input_file, samples)) {
fprintf(stderr, "Error: cannot parse file listing: %s\n", input_file);
return 2;
}
// read background files
std::vector<std::string> backgrounds;
if (backgrounds_file != NULL && !parseFiles(backgrounds_file, backgrounds)) {
fprintf(stderr, "Error: cannot parse file listing: %s\n", backgrounds_file);
return 2;
}
// create output file
FILE *fp = fopen(output_file, "wb");
if (fp == NULL) {
fprintf(stderr, "Error: cannot open output file for writing: %s\n", output_file);
return 2;
}
icvWriteVecHeader(fp, sample_count, sample_width, sample_height);
// generate distortions
std::default_random_engine generator(time(NULL));
std::normal_distribution<double> xdist(0.0, rotate_stddev_x / 3.0);
std::normal_distribution<double> ydist(0.0, rotate_stddev_y / 3.0);
std::normal_distribution<double> zdist(0.0, rotate_stddev_z / 3.0);
std::normal_distribution<double> ldist(0.0, luminosity_stddev / 3.0);
cv::Mat el = cv::getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(5, 5));
int variations = MAX(1, (int)floor((double)sample_count / (double)samples.size()));
int idx = 0;
int i = 0;
while (i < sample_count) {
// suffle the input lists
if (idx % samples.size() == 0) {
std::shuffle(samples.begin(), samples.end(), generator);
std::shuffle(backgrounds.begin(), backgrounds.end(), generator);
}
// read sample image
auto const &sample_file(samples[idx % samples.size()]);
cv::Mat sample = cv::imread(sample_file);
double sampleRatio = (double)sample.cols / (double)sample.rows;
double outputRatio = (double)sample_width / (double)sample_height;
// normalize sample
cv::Mat greySample = sample;
double min, max;
if (sample.channels() != 1) {
cv::cvtColor(sample, greySample, cv::COLOR_RGB2GRAY);
}
cv::minMaxIdx(greySample, &min, &max);
greySample -= min;
greySample /= (max - min) / 255.0;
// generate mask
cv::Mat mask(cv::Mat::ones(greySample.rows, greySample.cols, greySample.type()));
// enlarge canvas to fit output ratio
cv::Mat resizedSample, resizedMask;
if (backgrounds.size() > 0 && sampleRatio < outputRatio) {
int width = (int)((double)greySample.rows * outputRatio);
cv::Rect area(
(width - greySample.cols) / 2,
0,
greySample.cols,
greySample.rows
);
resizedSample = cv::Mat::zeros(greySample.rows, width, greySample.type());
resizedMask = cv::Mat::zeros(greySample.rows, width, greySample.type());
greySample.copyTo(resizedSample(area));
mask.copyTo(resizedMask(area));
} else if (backgrounds.size() > 0 && sampleRatio > outputRatio) {
int height = (int)((double)greySample.cols / outputRatio);
cv::Rect area(
0,
(height - greySample.rows) / 2,
greySample.cols,
greySample.rows
);
resizedSample = cv::Mat::zeros(height, greySample.cols, greySample.type());
resizedMask = cv::Mat::zeros(height, greySample.cols, greySample.type());
greySample.copyTo(resizedSample(area));
mask.copyTo(resizedMask(area));
} else {
resizedSample = greySample;
resizedMask = mask;
}
// apply distortions
cv::Mat target(resizedSample.rows, resizedSample.cols, resizedSample.type());
cv::Mat targetMask(resizedSample.rows, resizedSample.cols, resizedSample.type());
double halfWidth = resizedSample.cols / 2.0;
double halfHeight = resizedSample.rows / 2.0;
cv::Mat rotationVector(3, 1, CV_64FC1);
cv::Mat rotation4(cv::Mat::eye(4, 4, CV_64FC1));
cv::Mat translate4(cv::Mat::eye(4, 4, CV_64FC1));
cv::Mat translate3(cv::Mat::eye(3, 3, CV_64FC1));
cv::Mat scale3(cv::Mat::eye(3, 3, CV_64FC1));
int dx = (resizedSample.cols - greySample.cols) / 2;
int dy = (resizedSample.rows - greySample.rows) / 2;
cv::Point2f points1[4] = {
cv::Point2f(dx, dy),
cv::Point2f(dx, greySample.rows),
cv::Point2f(greySample.cols, greySample.rows),
cv::Point2f(greySample.cols, dy)
};
cv::Point2f points2[4];
translate4.at<double>(0, 3) = -halfWidth;
translate4.at<double>(1, 3) = -halfHeight;
for (int k = 0; k < variations; k++) {
double rx = k > 0 && rotate_stddev_x > 0.0 ? xdist(generator) : 0.0;
double ry = k > 0 && rotate_stddev_y > 0.0 ? ydist(generator) : 0.0;
double rz = k > 0 && rotate_stddev_z > 0.0 ? zdist(generator) : 0.0;
double rl = k > 0 && luminosity_stddev > 0.0 ? ldist(generator) : 0.0;
// compute rotation in 3d
rotationVector.at<double>(0) = rx;
rotationVector.at<double>(1) = ry;
rotationVector.at<double>(2) = rz;
cv::Rodrigues(rotationVector, cv::Mat(rotation4, cv::Rect(0, 0, 3, 3)));
// compute transformation in 3d
cv::Mat transform4(rotation4 * translate4);
double minx = DBL_MAX, miny = DBL_MAX;
double maxx = DBL_MIN, maxy = DBL_MIN;
for (int j = 0; j < 4; j++) {
cv::Mat point(4, 1, CV_64FC1);
point.at<double>(0) = points1[j].x;
point.at<double>(1) = points1[j].y;
point.at<double>(2) = 0.0;
point.at<double>(3) = 1.0;
point = transform4 * point;
points2[j].x = point.at<double>(0);
points2[j].y = point.at<double>(1);
if (points2[j].x < minx) {
minx = points2[j].x;
}
if (points2[j].x > maxx) {
maxx = points2[j].x;
}
if (points2[j].y < miny) {
miny = points2[j].y;
}
if (points2[j].y > maxy) {
maxy = points2[j].y;
}
}
// compute transformation in 2d
cv::Mat projection3(cv::getPerspectiveTransform(points1, points2));
double scalex = (resizedSample.cols - dx) / (maxx - minx);
double scaley = (resizedSample.rows - dy) / (maxy - miny);
translate3.at<double>(0, 2) = halfWidth;
translate3.at<double>(1, 2) = halfHeight;
scale3.at<double>(0, 0) = scalex; //MIN(scalex, scaley);
scale3.at<double>(1, 1) = scaley; //MIN(scalex, scaley);
// transform sample and mask in 2d
cv::Mat transform3(translate3 * scale3 * projection3);
cv::warpPerspective(resizedSample, target, transform3, target.size());
cv::warpPerspective(resizedMask, targetMask, transform3, targetMask.size());
// apply luminosity change
if (rl != 0.0) {
rl += 1.0;
target *= rl;
}
// read background image
cv::Mat greyBackground;
if (backgrounds.size() > 0) {
auto const &background_file(backgrounds[i % backgrounds.size()]);
cv::Mat background = cv::imread(background_file);
// normalize background image
if (background.channels() != 1) {
cv::cvtColor(background, greyBackground, cv::COLOR_RGB2GRAY);
} else {
greyBackground = background;
}
cv::minMaxIdx(greyBackground, &min, &max);
greyBackground -= min;
greyBackground /= (max - min) / 255.0;
// reshape background to fit output ratio
double backgroundRatio = (double)greyBackground.cols / (double)greyBackground.rows;
cv::Mat tmp;
if (backgroundRatio < outputRatio) {
int height = (int)((double)greyBackground.cols / outputRatio);
std::uniform_int_distribution<int> hdist(0, greyBackground.rows - height);
tmp = greyBackground(
cv::Rect(
0,
hdist(generator),
greyBackground.cols,
height
)
);
} else if (backgroundRatio > outputRatio) {
int width = (int)((double)greyBackground.rows * outputRatio);
std::uniform_int_distribution<int> wdist(0, greyBackground.cols - width);
tmp = greyBackground(
cv::Rect(
wdist(generator),
0,
width,
greyBackground.rows
)
);
} else {
tmp = greyBackground;
}
cv::resize(tmp, greyBackground, resizedSample.size(), 0, 0, cv::INTER_CUBIC);
} else {
// random noise background
greyBackground = cv::Mat(target.rows, target.cols, CV_8UC1);
cv::randn(greyBackground, 255.0 / 2, 255.0 / 2 / 3);
cv::GaussianBlur(greyBackground, greyBackground, cv::Size(5, 5), 10);
}
// blend background
cv::Mat sampleMask, backgroundMask, tmp;
cv::threshold(targetMask, sampleMask, 0.1, 255.0, cv::THRESH_BINARY);
cv::erode(sampleMask, tmp, el);
cv::blur(tmp, sampleMask, cv::Size(5, 5));
cv::threshold(targetMask, backgroundMask, 0.1, 255.0, cv::THRESH_BINARY_INV);
cv::dilate(backgroundMask, tmp, el);
cv::blur(tmp, backgroundMask, cv::Size(5, 5));
cv::multiply(target, sampleMask, target, 1.0 / 255.0);
cv::multiply(greyBackground, backgroundMask, greyBackground, 1.0 / 255.0);
target += greyBackground;
// cv::namedWindow("preview", cv::WINDOW_NORMAL);
// cv::imshow("preview", target);
// while ((cv::waitKey(0) & 0xff) != '\n');
// cv::namedWindow("preview", cv::WINDOW_NORMAL);
// cv::imshow("preview", greyBackground);
// while ((cv::waitKey(0) & 0xff) != '\n');
// sample resize
cv::Mat finalSample;
cv::resize(target, finalSample, cv::Size(sample_width, sample_height), 0, 0, cv::INTER_CUBIC);
// cv::namedWindow("preview", cv::WINDOW_NORMAL);
// cv::imshow("preview", finalSample);
// while ((cv::waitKey(0) & 0xff) != '\n');
// sample save
CvMat targetfinal_ = finalSample;
icvWriteVecSample(fp, &targetfinal_);
i++;
if (i % 100 == 0) {
fprintf(stdout, "processed %d images, %d samples\n", idx, i);
fflush(stdout);
}
}
idx++;
}
// close output file
fclose(fp);
return 0;
}
