int MonolingualModel::trainSentence(const string& sent, int sent_id) {
auto nodes = getNodes(sent); // same size as sent, OOV words are replaced by <UNK>
// counts the number of words that are in the vocabulary
int words = nodes.size() - count(nodes.begin(), nodes.end(), HuffmanNode::UNK);
if (config.subsampling > 0) {
subsample(nodes); // puts <UNK> tokens in place of the discarded tokens
}
if (nodes.empty()) {
return words;
}
// remove <UNK> tokens
nodes.erase(
remove(nodes.begin(), nodes.end(), HuffmanNode::UNK),
nodes.end());
// Monolingual training
for (int pos = 0; pos < nodes.size(); ++pos) {
trainWord(nodes, pos, sent_id);
}
return words; // returns the number of words processed, for progress estimation
}
QVector<QPoint>
CurveGroup::push(QVector<QPoint> c, QPoint cen, int rad, bool closed)
{
QVector<QPoint> newc;
newc = c;
int npts = c.count();
for(int i=0; i<npts; i++)
{
QPoint v = newc[i] - cen;
float len = qSqrt(QPoint::dotProduct(v,v));
if (len <= rad)
{
v /= qMax(0.0f, len);
for(int j=-rad; j<=rad; j++)
{
int idx = i+j;
if (idx < 0) idx = npts + idx;
else if (idx > npts-1) idx = idx - npts;
QPoint v0 = newc[idx] - cen;
int v0len = qSqrt(QPoint::dotProduct(v0,v0));
if (v0len <= rad)
{
float frc = (float)qAbs(qAbs(j)-rad)/(float)rad;
newc[idx] = newc[idx] + frc*(rad-len)*v;
}
}
}
}
QVector<QPoint> w;
w = subsample(newc, 1.2, closed);
return w;
}
void tracker<F>::subsample_input(const I& in)
{
subsample(in, input_);
fill_border_clamp(input_);
if (upper_tracker_)
upper_tracker_->subsample_input(input_);
}
void
CurveGroup::joinPolygonAt(int key, QVector<QPoint> pts)
{
int npts = pts.count();
int mc = getActiveMorphedCurve(key, pts[0].x(), pts[0].y());
if (mc >= 0)
{
Curve c = m_mcg[mc].value(key);
QVector<QPoint> w = c.pts;
int ncpts = w.count();
int start = -1;
QPoint startPt = pts[0];
QPoint endPt = pts[npts-1];
for(int j=0; j<ncpts; j++)
{
int ml = (startPt-w[j]).manhattanLength();
if (ml < 3)
{
start = j;
break;
}
}
int end = -1;
for(int j=0; j<ncpts; j++)
{
int ml = (endPt-w[j]).manhattanLength();
if (ml < 3)
{
end = j;
break;
}
}
if (start <0 || end < 0)
return;
// insert pts into the curve
QVector<QPoint> newc;
newc = pts;
int jend = ncpts;
if (start > end)
jend = start;
for(int j=end; j<jend; j++)
newc << w[j];
if (start < end)
{
for(int j=0; j<start; j++)
newc << w[j];
}
w = subsample(newc, 1.2, c.closed);
c.pts = w; // replace pts with the pushed version
m_mcg[mc].insert(key, c);
}
}
void inmo_oper(int nx, const float *trace, float *trace2, void* user_data)
/*< operator to invert by GMRES >*/
{
int it;
/* forward operator */
inmo(trace,dense2);
subsample(dense2,sparse2);
/* backward operator */
interpolate(sparse2,dense2);
nmostack(dense2,trace2);
/* I + S (BF - I) */
for (it=0; it < nt; it++) {
trace2[it] -= trace[it];
}
bandpass(trace2);
for (it=0; it < nt; it++) {
trace2[it] += trace[it];
}
}
void RGBDCamera::update(const RawFrame* this_frame) {
//Check the timestamp, and skip if we have already seen this frame
if (this_frame->timestamp <= latest_stamp_) {
return;
} else {
latest_stamp_ = this_frame->timestamp;
}
//Apply bilateral filter to incoming depth
uint16_t* filtered_depth;
cudaMalloc((void**)&filtered_depth, this_frame->width*this_frame->height*sizeof(uint16_t));
bilateralFilter(this_frame->depth, filtered_depth, this_frame->width, this_frame->height);
//Convert the input color data to intensity
float* temp_intensity;
cudaMalloc((void**)&temp_intensity, this_frame->width*this_frame->height*sizeof(float));
colorToIntensity(this_frame->color, temp_intensity, this_frame->width*this_frame->height);
//Create pyramids
for (int i = 0; i < PYRAMID_DEPTH; i++) {
//Fill in sizes the first two times through
if (pass_ < 2) {
current_icp_frame_[i] = new ICPFrame(this_frame->width/pow(2,i), this_frame->height/pow(2,i));
current_rgbd_frame_[i] = new RGBDFrame(this_frame->width/pow(2,i), this_frame->height/pow(2,i));
}
//Add ICP data
generateVertexMap(filtered_depth, current_icp_frame_[i]->vertex, current_icp_frame_[i]->width, current_icp_frame_[i]->height, focal_length_, make_int2(this_frame->width, this_frame->height));
generateNormalMap(current_icp_frame_[i]->vertex, current_icp_frame_[i]->normal, current_icp_frame_[i]->width, current_icp_frame_[i]->height);
//Add RGBD data
cudaMemcpy(current_rgbd_frame_[i]->vertex, current_icp_frame_[i]->vertex, current_rgbd_frame_[i]->width*current_rgbd_frame_[i]->height*sizeof(glm::vec3), cudaMemcpyDeviceToDevice);
cudaMemcpy(current_rgbd_frame_[i]->intensity, temp_intensity, current_rgbd_frame_[i]->width*current_rgbd_frame_[i]->height*sizeof(float), cudaMemcpyDeviceToDevice);
//Downsample depth and color if not the last iteration
if (i != (PYRAMID_DEPTH-1)) {
subsampleDepth(filtered_depth, current_icp_frame_[i]->width, current_icp_frame_[i]->height);
subsample(temp_intensity, current_rgbd_frame_[i]->width, current_rgbd_frame_[i]->height);
cudaDeviceSynchronize();
}
}
//Clear the filtered depth and temporary color since they are no longer needed
cudaFree(filtered_depth);
cudaFree(temp_intensity);
if (pass_ >= 1) {
glm::mat4 update_trans(1.0f);
//Loop through pyramids backwards (coarse first)
for (int i = PYRAMID_DEPTH - 1; i >= 0; i--) {
//Get a copy of the ICP frame for this pyramid level
ICPFrame icp_f(current_icp_frame_[i]->width, current_icp_frame_[i]->height);
cudaMemcpy(icp_f.vertex, current_icp_frame_[i]->vertex, icp_f.width*icp_f.height*sizeof(glm::vec3), cudaMemcpyDeviceToDevice);
cudaMemcpy(icp_f.normal, current_icp_frame_[i]->normal, icp_f.width*icp_f.height*sizeof(glm::vec3), cudaMemcpyDeviceToDevice);
//Get a copy of the RGBD frame for this pyramid level
//RGBDFrame rgbd_f(current_rgbd_frame_[i]->width, current_rgbd_frame_[i]->height);
//cudaMemcpy(rgbd_f.vertex, current_rgbd_frame_[i]->vertex, rgbd_f.width*rgbd_f.height*sizeof(glm::vec3), cudaMemcpyDeviceToDevice);
//cudaMemcpy(rgbd_f.intensity, current_rgbd_frame_[i]->intensity, rgbd_f.width*rgbd_f.height*sizeof(float), cudaMemcpyDeviceToDevice);
//Apply the most recent update to the points/normals
if (i < (PYRAMID_DEPTH-1)) {
transformVertexMap(icp_f.vertex, update_trans, icp_f.width*icp_f.height);
transformNormalMap(icp_f.normal, update_trans, icp_f.width*icp_f.height);
cudaDeviceSynchronize();
}
//Loop through iterations
for (int j = 0; j < PYRAMID_ITERS[i]; j++) {
//Get the Geometric ICP cost values
float A1[6 * 6];
float b1[6];
computeICPCost2(last_icp_frame_[i], icp_f, A1, b1);
//Get the Photometric RGB-D cost values
//float A2[6*6];
//float b2[6];
//compueRGBDCost(last_rgbd_frame_, rgbd_f, A2, b2);
//Combine the two
//for (size_t k = 0; k < 6; k++) {
//for (size_t l = 0; l < 6; l++) {
//A1[6 * k + l] += A2[6 * k + l];
//}
//b1[k] += b2[k];
//}
//Solve for the optimized camera transformation
float x[6];
solveCholesky(6, A1, b1, x);
//Check for NaN/divergence
if (isnan(x[0]) || isnan(x[1]) || isnan(x[2]) || isnan(x[3]) || isnan(x[4]) || isnan(x[5])) {
printf("Camera tracking is lost.\n");
break;
}
//Update position/orientation of the camera
glm::mat4 this_trans =
glm::rotate(glm::mat4(1.0f), -x[2] * 180.0f / 3.14159f, glm::vec3(0.0f, 0.0f, 1.0f))
* glm::rotate(glm::mat4(1.0f), -x[1] * 180.0f / 3.14159f, glm::vec3(0.0f, 1.0f, 0.0f))
* glm::rotate(glm::mat4(1.0f), -x[0] * 180.0f / 3.14159f, glm::vec3(1.0f, 0.0f, 0.0f))
* glm::translate(glm::mat4(1.0f), glm::vec3(x[3], x[4], x[5]));
update_trans = this_trans * update_trans;
//Apply the update to the points/normals
if (j < (PYRAMID_ITERS[i] - 1)) {
transformVertexMap(icp_f.vertex, this_trans, icp_f.width*icp_f.height);
transformNormalMap(icp_f.normal, this_trans, icp_f.width*icp_f.height);
cudaDeviceSynchronize();
}
}
}
//Update the global transform with the result
position_ = glm::vec3(glm::vec4(position_, 1.0f) * update_trans);
orientation_ = glm::mat3(glm::mat4(orientation_) * update_trans);
}
if (pass_ < 2) {
pass_++;
}
//Swap current and last frames
for (int i = 0; i < PYRAMID_DEPTH; i++) {
ICPFrame* temp = current_icp_frame_[i];
current_icp_frame_[i] = last_icp_frame_[i];
last_icp_frame_[i] = temp;
//TODO: Longterm, only RGBD should do this. ICP should not swap, as last_frame should be updated by a different function
RGBDFrame* temp2 = current_rgbd_frame_[i];
current_rgbd_frame_[i] = last_rgbd_frame_[i];
last_rgbd_frame_[i] = temp2;
}
}
typename EMSubpixelCorrelatorView<ImagePixelT>::prerasterize_type
EMSubpixelCorrelatorView<ImagePixelT>::prerasterize(BBox2i const& bbox) const {
vw_out(InfoMessage, "stereo") << "EMSubpixelCorrelatorView: rasterizing image block " << bbox << ".\n";
// Find the range of disparity values for this patch.
// int num_good; // not used
BBox2i search_range;
try {
search_range = get_disparity_range(crop(m_course_disparity, bbox));
}
catch (const std::exception& e) {
search_range = BBox2i();
}
#ifdef USE_GRAPHICS
ImageWindow window;
if(debug_level >= 0) {
window = vw_create_window("disparity");
}
#endif
// The area in the right image that we'll be searching is
// determined by the bbox of the left image plus the search
// range.
BBox2i left_crop_bbox(bbox);
BBox2i right_crop_bbox(bbox.min() + search_range.min(),
bbox.max() + search_range.max());
// The correlator requires the images to be the same size. The
// search bbox will always be larger than the given left image
// bbox, so we just make the left bbox the same size as the
// right bbox.
left_crop_bbox.max() = left_crop_bbox.min() + Vector2i(right_crop_bbox.width(), right_crop_bbox.height());
// Finally, we must adjust both bounding boxes to account for
// the size of the kernel itself.
right_crop_bbox.min() -= Vector2i(m_kernel_size[0], m_kernel_size[1]);
right_crop_bbox.max() += Vector2i(m_kernel_size[0], m_kernel_size[1]);
left_crop_bbox.min() -= Vector2i(m_kernel_size[0], m_kernel_size[1]);
left_crop_bbox.max() += Vector2i(m_kernel_size[0], m_kernel_size[1]);
// We crop the images to the expanded bounding box and edge
// extend in case the new bbox extends past the image bounds.
ImageView<ImagePixelT> left_image_patch, right_image_patch;
ImageView<disparity_pixel> disparity_map_patch_in;
ImageView<result_type> disparity_map_patch_out;
left_image_patch = crop(edge_extend(m_left_image, ZeroEdgeExtension()),
left_crop_bbox);
right_image_patch = crop(edge_extend(m_right_image, ZeroEdgeExtension()),
right_crop_bbox);
disparity_map_patch_in = crop(edge_extend(m_course_disparity, ZeroEdgeExtension()),
left_crop_bbox);
disparity_map_patch_out.set_size(disparity_map_patch_in.cols(), disparity_map_patch_in.rows());
// Adjust the disparities to be relative to the cropped
// image pixel locations
for (int v = 0; v < disparity_map_patch_in.rows(); ++v) {
for (int u = 0; u < disparity_map_patch_in.cols(); ++u) {
if (disparity_map_patch_in(u,v).valid()) {
disparity_map_patch_in(u,v).child().x() -= search_range.min().x();
disparity_map_patch_in(u,v).child().y() -= search_range.min().y();
}
}
}
double blur_sigma_progressive = .5; // 3*sigma = 1.5 pixels
// create the pyramid first
std::vector<ImageView<ImagePixelT> > left_pyramid(pyramid_levels), right_pyramid(pyramid_levels);
std::vector<BBox2i> regions_of_interest(pyramid_levels);
std::vector<ImageView<Matrix2x2> > warps(pyramid_levels);
std::vector<ImageView<disparity_pixel> > disparity_map_pyramid(pyramid_levels);
// initialize the pyramid at level 0
left_pyramid[0] = channels_to_planes(left_image_patch);
right_pyramid[0] = channels_to_planes(right_image_patch);
disparity_map_pyramid[0] = disparity_map_patch_in;
regions_of_interest[0] = BBox2i(m_kernel_size[0], m_kernel_size[1],
bbox.width(),bbox.height());
// downsample the disparity map and the image pair to initialize the intermediate levels
for(int i = 1; i < pyramid_levels; i++) {
left_pyramid[i] = subsample(gaussian_filter(left_pyramid[i-1], blur_sigma_progressive), 2);
right_pyramid[i] = subsample(gaussian_filter(right_pyramid[i-1], blur_sigma_progressive), 2);
disparity_map_pyramid[i] = detail::subsample_disp_map_by_two(disparity_map_pyramid[i-1]);
regions_of_interest[i] = BBox2i(regions_of_interest[i-1].min()/2, regions_of_interest[i-1].max()/2);
}
// initialize warps at the lowest resolution level
warps[pyramid_levels-1].set_size(left_pyramid[pyramid_levels-1].cols(),
left_pyramid[pyramid_levels-1].rows());
for(int y = 0; y < warps[pyramid_levels-1].rows(); y++) {
for(int x = 0; x < warps[pyramid_levels-1].cols(); x++) {
warps[pyramid_levels-1](x, y).set_identity();
}
}
#ifdef USE_GRAPHICS
vw_initialize_graphics(0, NULL);
if(debug_level >= 0) {
for(int i = 0; i < pyramid_levels; i++) {
vw_show_image(window, left_pyramid[i]);
usleep((int)(.2*1000*1000));
}
}
#endif
// go up the pyramid; first run refinement, then upsample result for the next level
for(int i = pyramid_levels-1; i >=0; i--) {
vw_out() << "processing pyramid level "
<< i << " of " << pyramid_levels-1 << std::endl;
if(debug_level >= 0) {
std::stringstream stream;
stream << "pyramid_level_" << i << ".tif";
write_image(stream.str(), disparity_map_pyramid[i]);
}
ImageView<ImagePixelT> process_left_image = left_pyramid[i];
ImageView<ImagePixelT> process_right_image = right_pyramid[i];
if(i > 0) { // in this case take refine the upsampled disparity map from the previous level,
// and upsample for the next level
m_subpixel_refine(edge_extend(process_left_image, ZeroEdgeExtension()), edge_extend(process_right_image, ZeroEdgeExtension()),
disparity_map_pyramid[i], disparity_map_pyramid[i], warps[i],
regions_of_interest[i], false, debug_level == i);
// upsample the warps and the refined map for the next level of processing
int up_width = left_pyramid[i-1].cols();
int up_height = left_pyramid[i-1].rows();
warps[i-1] = copy(resize(warps[i], up_width , up_height, ConstantEdgeExtension(), NearestPixelInterpolation())); //upsample affine transforms
disparity_map_pyramid[i-1] = copy(detail::upsample_disp_map_by_two(disparity_map_pyramid[i], up_width, up_height));
}
else { // here there is no next level so we refine directly to the output patch
m_subpixel_refine(edge_extend(process_left_image, ZeroEdgeExtension()), edge_extend(process_right_image, ZeroEdgeExtension()),
disparity_map_pyramid[i], disparity_map_patch_out, warps[i],
regions_of_interest[i], true, debug_level == i);
}
}
#ifdef USE_GRAPHICS
if(debug_level >= 0) {
vw_show_image(window, .5 + select_plane(channels_to_planes(disparity_map_patch_out)/6., 0));
usleep(10*1000*1000);
}
#endif
// Undo the above adjustment
for (int v = 0; v < disparity_map_patch_out.rows(); ++v) {
for (int u = 0; u < disparity_map_patch_out.cols(); ++u) {
if (disparity_map_patch_out(u,v).valid()) {
disparity_map_patch_out(u,v).child().x() += search_range.min().x();
disparity_map_patch_out(u,v).child().y() += search_range.min().y();
}
}
}
#ifdef USE_GRAPHICS
if(debug_level >= 0 ) {
vw_destroy_window(window);
}
#endif
return crop(disparity_map_patch_out, BBox2i(m_kernel_size[0]-bbox.min().x(),
m_kernel_size[1]-bbox.min().y(),
m_left_image.cols(),
m_left_image.rows()));
}
//---------------------------------------------------------------
// START FUNC DECL
int
parsort1(
char *tbl,
char *f1,
char *f2,
char *up_or_down /* not used right now */
)
// STOP FUNC DECL
{
int status = 0;
char *f1_X = NULL; size_t f1_nX = 0;
char *op_X = NULL; size_t op_nX = 0;
char *cnt_X = NULL; size_t cnt_nX = 0;
char *t2f2_X = NULL; size_t t2f2_nX = 0;
FLD_TYPE *f1_meta = NULL;
FLD_TYPE *f2_meta = NULL;
FLD_TYPE *t2f2_meta = NULL;
FLD_TYPE *cnt_meta = NULL;
long long nR, nR2;
int tbl_id = INT_MIN, f1_id = INT_MIN, f2_id = INT_MIN, cnt_id = INT_MIN;
int t2f2_id = INT_MIN;
char str_meta_data[1024];
FILE *ofp = NULL; char *opfile = NULL;
FILE *tfp = NULL; char *tempfile = NULL;
char str_rslt[32]; zero_string(str_rslt, 32);
char t2[MAX_LEN_TBL_NAME];
int itemp;
int *xxx = NULL, *f1lb = NULL, *f1ub = NULL;
long long *count = NULL, *chk_count = NULL;
int **offsets = NULL, **bak_offsets = NULL;
int *inptr = NULL;
// For multi-threading
int rc; // result code for thread create
pthread_t threads[MAX_NUM_THREADS];
pthread_attr_t attr;
void *thread_status;
// START: For timing
struct timeval Tps;
struct timezone Tpf;
void *Tzp = NULL;
long long t_before_sec = 0, t_before_usec = 0, t_before = 0;
long long t_after_sec, t_after_usec, t_after;
long long t_delta_usec;
// STOP : For timing
//----------------------------------------------------------------
if ( ( tbl == NULL ) || ( *tbl == '\0' ) ) { go_BYE(-1); }
if ( ( f1 == NULL ) || ( *f1 == '\0' ) ) { go_BYE(-1); }
if ( ( f2 == NULL ) || ( *f2 == '\0' ) ) { go_BYE(-1); }
zero_string(str_meta_data, 1024);
/* t2 isa temporary table */
zero_string(t2, MAX_LEN_TBL_NAME);
status = qd_uq_str(t2, MAX_LEN_TBL_NAME);
strcpy(t2, "t2"); // TODO DELETE THIS
g_offsets = NULL;
g_count = NULL;
//--------------------------------------------------------
status = is_tbl(tbl, &tbl_id); cBYE(status);
chk_range(tbl_id, 0, g_n_tbl);
nR = g_tbl[tbl_id].nR;
status = is_fld(NULL, tbl_id, f1, &f1_id); cBYE(status);
chk_range(f1_id, 0, g_n_fld);
f1_meta = &(g_fld[f1_id]);
status = rs_mmap(f1_meta->filename, &f1_X, &f1_nX, 0);
cBYE(status);
// Not implemented for following cases
if ( g_fld[f1_id].nn_fld_id >= 0 ) { go_BYE(-1); }
if ( strcmp(f1_meta->fldtype, "int") != 0 ) { go_BYE(-1); }
if ( nR <= 1048576 ) { go_BYE(-1); }
//---------------------------------------------
status = gettimeofday(&Tps, &Tpf); cBYE(status);
t_before_sec = (long long)Tps.tv_sec;
t_before_usec = (long long)Tps.tv_usec;
t_before = t_before_sec * 1000000 + t_before_usec;
int reduction_factor = (int)(sqrt((double)nR));
sprintf(str_rslt, "%d", reduction_factor);
status = subsample(tbl, f1, str_rslt, t2, "f2"); cBYE(status);
status = gettimeofday(&Tps, &Tpf); cBYE(status);
t_after_sec = (long long)Tps.tv_sec;
t_after_usec = (long long)Tps.tv_usec;
t_after = t_after_sec * 1000000 + t_after_usec;
fprintf(stderr, "TIME0 = %lld \n", t_after - t_before);
t_before = t_after;
// Must have sufficient diversity of values
status = f1opf2(t2, "f2", "op=shift:val=-1", "nextf2"); cBYE(status);
status = drop_nn_fld(t2, "nextf2"); cBYE(status);
status = f1f2opf3(t2, "f2", "nextf2", "==", "x"); cBYE(status);
status = f_to_s(t2, "x", "sum", str_rslt);
char *endptr;
long long lltemp = strtoll(str_rslt, &endptr, 10);
if ( lltemp != 0 ) { go_BYE(-1); }
//-------------------------------------------------
// Get range of values of f1
status = f_to_s(tbl, f1, "max", str_rslt);
int f1max = strtoll(str_rslt, &endptr, 10);
status = f_to_s(tbl, f1, "min", str_rslt);
int f1min = strtoll(str_rslt, &endptr, 10);
//-------------------------------------------------
// Now we sort the values that we sampled
status = fop(t2, "f2", "sortA"); cBYE(status);
// status = pr_fld(t2, "f2", "", stdout);
status = get_nR(t2, &nR2);
// Now each thread selects a range to work on
int nT;
for ( int i = 0; i < MAX_NUM_THREADS; i++ ) {
g_thread_id[i] = i;
}
status = get_num_threads(&nT);
cBYE(status);
//--------------------------------------------
#define MIN_ROWS_FOR_PARSORT1 1048576
if ( nR <= MIN_ROWS_FOR_PARSORT1 ) {
nT = 1;
}
/* Don't create more threads than you can use */
if ( nT > nR ) { nT = nR; }
//--------------------------------------------
double block_size = (double)nR2 / (double)nT;
status = is_fld(t2, -1, "f2", &t2f2_id); cBYE(status);
chk_range(t2f2_id, 0, g_n_fld);
t2f2_meta = &(g_fld[t2f2_id]);
status = rs_mmap(t2f2_meta->filename, &t2f2_X, &t2f2_nX, 0);
cBYE(status);
int *iptr = (int *)t2f2_X;
xxx = malloc(nT * sizeof(int)); return_if_malloc_failed(xxx);
f1lb = malloc(nT * sizeof(int)); return_if_malloc_failed(f1lb);
f1ub = malloc(nT * sizeof(int)); return_if_malloc_failed(f1ub);
/* FOR OLD_WAY
count = malloc(nT * sizeof(long long)); return_if_malloc_failed(count);
*/
chk_count = malloc(nT * sizeof(long long));
return_if_malloc_failed(chk_count);
g_count = malloc(nT * sizeof(long long)); return_if_malloc_failed(g_count);
for ( int i = 0; i < nT; i++ ) {
// FOR OLD_WAY count[i]= 0;
chk_count[i]= 0;
int j = i+1;
long long idx = j * block_size;
if ( idx >= nR2 ) { idx = nR2 -1 ; }
int y = iptr[idx];
xxx[i] = y;
// fprintf(stdout,"idx = %lld: j = %d: y = %d \n", idx, j, y);
}
for ( int i = 0; i < nT; i++ ) {
if ( ( i == 0 ) && ( i == (nT - 1 ) ) ) {
f1lb[i] = f1min;
f1ub[i] = f1max;
}
else if ( i == 0 ) {
f1lb[i] = f1min;
f1ub[i] = xxx[i];
}
else if ( i == (nT -1 ) ) {
f1lb[i] = xxx[i-1] + 1;
f1ub[i] = f1max;
}
else {
f1lb[i] = xxx[i-1] + 1;
f1ub[i] = xxx[i];
}
}
// STOP: Each thread has now a range to work on
// Create a temporary table t3 to store ranges
char t3[MAX_LEN_TBL_NAME]; int t3_id;
zero_string(t3, MAX_LEN_TBL_NAME);
status = qd_uq_str(t3, MAX_LEN_TBL_NAME);
strcpy(t3, "t3"); // TODO DELETE THIS
sprintf(str_rslt, "%d", nT);
status = add_tbl(t3, str_rslt, &t3_id);
// Add lower bound to t3
status = open_temp_file(&tfp, &tempfile, -1); cBYE(status);
fclose_if_non_null(tfp);
tfp = fopen(tempfile, "wb"); return_if_fopen_failed(tfp, tempfile, "wb");
fwrite(f1lb, sizeof(int), nT, tfp);
fclose_if_non_null(tfp);
sprintf(str_meta_data, "fldtype=%s:n_sizeof=%d:filename=%s",
f1_meta->fldtype, f1_meta->n_sizeof, tempfile);
status = add_fld(t3, "lb", str_meta_data, &itemp); cBYE(status);
free_if_non_null(tempfile);
// Add upper bound to t3
status = open_temp_file(&tfp, &tempfile, -1); cBYE(status);
fclose_if_non_null(tfp);
tfp = fopen(tempfile, "wb"); return_if_fopen_failed(tfp, tempfile, "wb");
fwrite(f1ub, sizeof(int), nT, tfp);
fclose_if_non_null(tfp);
sprintf(str_meta_data, "fldtype=%s:n_sizeof=%d:filename=%s",
f1_meta->fldtype, f1_meta->n_sizeof, tempfile);
status = add_fld(t3, "ub", str_meta_data, &itemp); cBYE(status);
free_if_non_null(tempfile);
#undef OLD_WAY
#ifdef OLD_WAY
// Now we count how much there is in each range
inptr = (int *)f1_X;
for ( long long i = 0; i < nR; i++ ) {
int ival = *inptr++;
int range_idx = INT_MIN;
// TODO: Improve sequential search
for ( int j = 0; j < nT; j++ ) {
if ( ival >= f1lb[j] && ( ival <= f1ub[j] ) ) {
range_idx = j;
break;
}
}
count[range_idx]++;
}
/*
for ( int i = 0; i < nT; i++ ) {
fprintf(stdout,"%d: (%d, %d) = %lld \n", i, f1lb[i], f1ub[i], count[i]);
}
*/
#else
status = num_in_range(tbl, f1, t3, "lb", "ub", "cnt"); cBYE(status);
// Get a pointer to the count field
status = is_tbl(t3, &t3_id);
chk_range(t3_id, 0, g_n_tbl);
status = is_fld(NULL, t3_id, "cnt", &cnt_id);
chk_range(cnt_id, 0, g_n_fld);
cnt_meta = &(g_fld[cnt_id]);
status = rs_mmap(cnt_meta->filename, &cnt_X, &cnt_nX, 0); cBYE(status);
count = (long long *)cnt_X;
#endif
status = gettimeofday(&Tps, &Tpf); cBYE(status);
t_after_sec = (long long)Tps.tv_sec;
t_after_usec = (long long)Tps.tv_usec;
t_after = t_after_sec * 1000000 + t_after_usec;
fprintf(stderr, "TIME1 = %lld \n", t_after - t_before);
t_before = t_after;
bak_offsets = malloc(nT * sizeof(int *)); return_if_malloc_failed(bak_offsets);
g_offsets = malloc(nT * sizeof(int *)); return_if_malloc_failed(g_offsets);
#ifdef OLD_WAY
// Make space for output
long long filesz = nR * f1_meta->n_sizeof;
status = open_temp_file(&ofp, &opfile, filesz); cBYE(status);
status = mk_file(opfile, filesz); cBYE(status);
status = rs_mmap(opfile, &op_X, &op_nX, 1); cBYE(status);
offsets = malloc(nT * sizeof(int *)); return_if_malloc_failed(offsets);
long long cum_count = 0;
for ( int i = 0; i < nT; i++ ) {
bak_offsets[i] = offsets[i] = (int *)op_X;
if ( i > 0 ) {
cum_count += count[i-1];
offsets[i] += cum_count;
bak_offsets[i] = offsets[i];
}
}
inptr = (int *)f1_X;
// Now we place each item into its thread bucket
for ( long long i = 0; i < nR; i++ ) {
int ival = *inptr++;
int range_idx = INT_MIN;
// TODO: Improve sequential search
for ( int j = 0; j < nT; j++ ) {
if ( ival >= f1lb[j] && ( ival <= f1ub[j] ) ) {
range_idx = j;
break;
}
}
int *xptr = offsets[range_idx];
*xptr = ival;
offsets[range_idx]++;
chk_count[range_idx]++;
if ( chk_count[range_idx] > count[range_idx] ) {
go_BYE(-1);
}
}
cum_count = 0;
for ( int i = 0; i < nT-1; i++ ) {
if ( offsets[i] != bak_offsets[i+1] ) {
go_BYE(-1);
}
}
#else
status = mv_range(tbl, f1, f2, t3, "lb", "ub", "cnt");
cBYE(status);
status = is_fld(NULL, tbl_id, f2, &f2_id);
chk_range(f2_id, 0, g_n_fld);
f2_meta = &(g_fld[f2_id]);
status = rs_mmap(f2_meta->filename, &op_X, &op_nX, 1); cBYE(status);
#endif
long long cum_count = 0;
for ( int i = 0; i < nT; i++ ) {
bak_offsets[i] = (int *)op_X;
if ( i > 0 ) {
cum_count += count[i-1];
bak_offsets[i] += cum_count;
}
}
status = gettimeofday(&Tps, &Tpf); cBYE(status);
t_after_sec = (long long)Tps.tv_sec;
t_after_usec = (long long)Tps.tv_usec;
t_after = t_after_sec * 1000000 + t_after_usec;
fprintf(stderr, "TIME2 = %lld \n", t_after - t_before);
t_before = t_after;
// Set up global variables
g_nT = nT;
for ( int i = 0; i < nT; i++ ) {
g_offsets[i] = bak_offsets[i];
g_count[i] = count[i];
}
if ( g_nT == 1 ) {
core_parsort1(&(g_thread_id[0]));
}
else {
pthread_attr_init(&attr);
pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_JOINABLE);
for ( int t = 0; t < g_nT; t++ ) {
rc = pthread_create(&threads[t], NULL, core_parsort1,
&(g_thread_id[t]));
if ( rc ) { go_BYE(-1); }
}
/* Free attribute and wait for the other threads */
pthread_attr_destroy(&attr);
for ( int t = 0; t < g_nT; t++ ) {
rc = pthread_join(threads[t], &thread_status);
if ( rc ) { go_BYE(-1); }
}
}
/* SEQUENTIAL CODE
for ( int i = 0; i < nT; i++ ) {
qsort_asc_int(bak_offsets[i], count[i], sizeof(int), NULL);
}
*/
status = gettimeofday(&Tps, &Tpf); cBYE(status);
t_after_sec = (long long)Tps.tv_sec;
t_after_usec = (long long)Tps.tv_usec;
t_after = t_after_sec * 1000000 + t_after_usec;
fprintf(stderr, "TIME3 = %lld \n", t_after - t_before);
// Indicate the dst_fld is sorted ascending
status = set_fld_info(tbl, f2, "sort=1");
rs_munmap(op_X, op_nX);
status = del_tbl(t2, -1); cBYE(status);
status = del_tbl(t3, -1); cBYE(status);
BYE:
rs_munmap(op_X, op_nX);
rs_munmap(cnt_X, cnt_nX);
free_if_non_null(xxx);
free_if_non_null(f1lb);
free_if_non_null(f1ub);
// Do not delete unless using OLD_WAY free_if_non_null(count);
free_if_non_null(g_count);
free_if_non_null(g_offsets);
free_if_non_null(offsets);
free_if_non_null(bak_offsets);
free_if_non_null(chk_count);
fclose_if_non_null(ofp);
g_write_to_temp_dir = false;
rs_munmap(f1_X, f1_nX);
rs_munmap(op_X, op_nX);
free_if_non_null(opfile);
return(status);
}
QVector<QPoint>
CurveGroup::smooth(QVector<QPoint> c, QPoint cen, int rad, bool closed)
{
QVector<QPoint> newc;
newc = c;
int npts = c.count();
int sz = rad;
// QMultiMap<int, int> inRad;
// for(int i=1; i<npts-1; i++)
// {
// QPoint v = c[i] - cen;
// if (v.manhattanLength() <= rad)
// inRad.insert(v.manhattanLength(), i);
// }
//
// QList<int> keys = inRad.keys();
// for(int k=0; k<keys.count(); k++)
// {
// QList<int> ipts = inRad.values(keys[k]);
// for(int p=0; p<ipts.count(); p++)
// {
// int i = ipts[p];
// QPoint v = c[i];
// for(int j=-sz; j<=sz; j++)
// {
// int idx = i+j;
// if (closed)
// {
// if (idx < 0) idx = npts + idx;
// else if (idx > npts-1) idx = idx - npts;
// }
// else
// idx = qBound(0, idx, npts-1);
// v += newc[idx];
// }
// v /= (2*sz+2);
// newc[i] = v;
// }
// }
for(int i=0; i<npts-1; i++)
{
QPoint v = c[i] - cen;
if (v.manhattanLength() <= rad)
{
//v = QPoint(0,0);
v = c[i];
for(int j=-sz; j<=sz; j++)
{
int idx = i+j;
if (closed)
{
if (idx < 0) idx = npts + idx;
else if (idx > npts-1) idx = idx - npts;
}
else
idx = qBound(0, idx, npts-1);
v += c[idx];
}
v /= (2*sz+2);
newc[i] = v;
}
}
QVector<QPoint> w;
w = subsample(newc, 1.2, closed);
return w;
}
int main( int argc, char *argv[] )
{
if ( (argc == 2) &&
( (GF2::console::find_switch(argc,argv,"--help"))
|| (GF2::console::find_switch(argc,argv,"-h" ))
)
)
{
std::cout << "[Usage]:\n"
<< "\t--generate\n"
<< "\t--generate3D\n"
<< "\t--formulate\n"
<< "\t--formulate3D\n"
<< "\t--solver mosek|bonmin|gurobi\n"
<< "\t--solver3D mosek|bonmin|gurobi\n"
<< "\t--merge\n"
<< "\t--merge3D\n"
<< "\t--datafit\n"
<< "\t--corresp\n"
//<< "\t--show\n"
<< std::endl;
return EXIT_SUCCESS;
}
else if ( GF2::console::find_switch(argc,argv,"--segment") || GF2::console::find_switch(argc,argv,"--segment3D") )
{
return segment( argc, argv );
}
else if ( GF2::console::find_switch(argc,argv,"--generate") || GF2::console::find_switch(argc,argv,"--generate3D") )
{
return generate(argc,argv);
}
else if ( GF2::console::find_switch(argc,argv,"--formulate") || GF2::console::find_switch(argc,argv,"--formulate3D"))
{
return formulate( argc, argv );
//return GF2::ProblemSetup::formulateCli<GF2::Solver::PrimitiveContainerT, GF2::Solver::PointContainerT>( argc, argv );
}
else if ( GF2::console::find_switch(argc,argv,"--solver") || GF2::console::find_switch(argc,argv,"--solver3D") ) // Note: "solver", not "solve" :-S
{
return solve( argc, argv );
//return GF2::Solver::solve( argc, argv );
}
else if ( GF2::console::find_switch(argc,argv,"--datafit") || GF2::console::find_switch(argc,argv,"--datafit3D") )
{
return datafit( argc, argv );
//return GF2::Solver::datafit( argc, argv );
}
else if ( GF2::console::find_switch(argc,argv,"--merge") || GF2::console::find_switch(argc,argv,"--merge3D") )
{
return merge(argc, argv);
}
else if ( GF2::console::find_switch(argc,argv,"--show") )
{
std::cerr << "[" << __func__ << "]: " << "the show option has been moved to a separate executable, please use thatt one" << std::endl;
return 1;
//return GF2::Solver::show( argc, argv );
}
else if ( GF2::console::find_switch(argc,argv,"--subsample") )
{
return subsample( argc, argv );
}
// else if ( GF2::console::find_switch(argc,argv,"--corresp") || GF2::console::find_switch(argc,argv,"--corresp3D") )
// {
// return corresp( argc, argv );
// }
std::cerr << "[" << __func__ << "]: " << "unrecognized option" << std::endl;
return 1;
// --show --dir . --cloud cloud.ply --scale 0.05f --assoc points_primitives.txt --use-tags --no-clusters --prims primitives.bonmin.txt
// std::string img_path( "input2.png" );
// pcl::console::parse_argument( argc, argv, "--img", img_path );
// float scale = 0.1f;
// pcl::console::parse_argument( argc, argv, "--scale", scale );
// return GF2::Solver::run( img_path, scale, {0, M_PI_2, M_PI}, argc, argv );
}
