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bitdance_pcqa.cpp
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bitdance_pcqa.cpp
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/*
* Copyright (C) 2019-2021 Rafael Diniz <[email protected]>
*
* This is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3, or (at your option)
* any later version.
*
* This software is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this software; see the file COPYING. If not, write to
* the Free Software Foundation, Inc., 51 Franklin Street,
* Boston, MA 02110-1301, USA.
*
*/
#include <unistd.h>
#include <cstdint>
#include <sstream>
#include <iostream>
#include <memory>
#include <thread>
#include <Open3D.h>
#include <inttypes.h>
#include <stdlib.h>
#include "bitdance_pcqa.h"
#include "ColorSpace/ColorSpace.h"
#include "ColorSpace/Comparison.h"
#define USE_OPENMP__ 1
using namespace open3d;
using namespace std;
int main(int argc, char *argv[])
{
bool create_histogram = false;
bool divide_color_by_255 = false;
bool voxelize = false;
bool split_files = false;
double voxel_size = 0;
int neiborhood_list_size = 0;
int max_neiborhood_size = 0;
int neiborhood_size[MAX_NN_LIST_SIZE];
uint8_t metric_enabled[MAX_NR_METRICS];
char metrics_enabled_list[MAX_FILENAME] = {0};
char neiborhood_sizes_list[MAX_FILENAME] = {0};
char input_filename[MAX_FILENAME] = {0};
char histogram_filename[MAX_FILENAME] = {0};
if (argc < 3){
usage_info:
fprintf(stderr, "Usage: %s [OPTIONS]\n", argv[0]);
fprintf(stderr, "Usage example: %s -i input_pc.ply -n 12,11,10,9,8 -h fv_file_prot.csv -m 1,1,1,1,1\n", argv[0]);
fprintf(stderr, "\nOPTIONS:\n");
fprintf(stderr, " -i input_pc.ply PC to be evaluated\n");
fprintf(stderr, " -h fv.csv Save the feature vector as csv output (or use this paramenter as basename, in case \"-s\" is used).\n");
fprintf(stderr, " -n neiborhood_sizes_list Comma separated neiborhood size to test(eg: \"12,10,8\"\n");
fprintf(stderr, " -m metrics_enabled_list Comma separated boolean values of the enabled metrics, in the following order: DE2000 12-bit, DE2000 8-bit, Geo 16-bit, Geo 12-bit, Geo 8-bit)\n");
fprintf(stderr, " -v voxel_size Voxelize and use voxel size as specified\n");
fprintf(stderr, " -y Divide color attributes by 255\n");
fprintf(stderr, " -s Split results files (many output files!)\n");
return EXIT_SUCCESS;
}
int opt;
while ((opt = getopt(argc, argv, "i:h:n:m:v:ys")) != -1){
switch (opt){
case 'i':
strncpy (input_filename, optarg, MAX_FILENAME);
break;
case 's':
split_files = true;
break;
case 'h':
create_histogram = true;
strncpy (histogram_filename, optarg, MAX_FILENAME);
break;
case 'n':
strncpy (neiborhood_sizes_list, optarg, MAX_FILENAME);
break;
case 'm':
strncpy (metrics_enabled_list, optarg, MAX_FILENAME);
break;
case 'v':
voxelize = true;
voxel_size = atof(optarg);
break;
case 'y':
divide_color_by_255 = true;
break;
default:
fprintf(stderr, "Wrong command line.\n");
goto usage_info;
}
}
// COMMAND LINE PARSING //
if (neiborhood_sizes_list[0] == 0)
{
fprintf(stderr, "Specify at least one neighbour size.\n");
goto usage_info;
}
// parse input neighborhood list
char *tok = neiborhood_sizes_list;
strtok(neiborhood_sizes_list, ",");
do
{
sscanf(tok, "%d", &neiborhood_size[neiborhood_list_size]);
if (neiborhood_size[neiborhood_list_size] > max_neiborhood_size)
max_neiborhood_size = neiborhood_size[neiborhood_list_size];
neiborhood_list_size++;
} while ((tok = strtok(NULL, ",")) && neiborhood_list_size < MAX_NN_LIST_SIZE);
#if 1
fprintf(stderr, "total neighbours: %d max %d\n", neiborhood_list_size, max_neiborhood_size);
for (int i = 0; i < neiborhood_list_size; i++)
fprintf(stderr, "neighbours: %d\n", neiborhood_size[i]);
#endif
// parse metrics selection list
int metrics_counter = 0;
tok = metrics_enabled_list;
strtok(metrics_enabled_list, ",");
do
{
sscanf(tok, "%hhu", &metric_enabled[metrics_counter]);
// fprintf(stderr, "%d\n", metric_enabled[metrics_counter]);
metrics_counter++;
} while ((tok = strtok(NULL, ",")) && metrics_counter < MAX_NR_METRICS);
#if 1
fprintf(stderr, "total available metrics: %d\n", metrics_counter);
for (int i = 0; i < metrics_counter; i++)
fprintf(stderr, "metrics[%d]: %s\n", i, metric_enabled[i]? "enabled":"disabled");
#endif
// 2D vector with the histograms
double *histogram[MAX_NR_METRICS][neiborhood_list_size];
#if USE_OPENMP__ == 1
int max_threads = omp_get_max_threads();
fprintf(stderr, "OpenMP reported max threads = %d\n", max_threads);
#else
fprintf(stderr, "OpenMP build disabled.\n");
#endif
// METRICS INITIALIZATION //
int end_of_scale[MAX_NR_METRICS][neiborhood_list_size];
for (int j = 0; j < neiborhood_list_size; j++)
{
end_of_scale[DLCP_12B][j] = 4096;
end_of_scale[DLCP_8B][j] = 256;
end_of_scale[DGEO_16B][j] = 65536;
end_of_scale[DGEO_12B][j] = 4096;
end_of_scale[DGEO_8B][j] = 256;
}
for (int i = 0; i < MAX_NR_METRICS; i++)
{
if (metric_enabled[i] != 0)
{
for (int j = 0; j < neiborhood_list_size; j++)
{
histogram[i][j] = (double *) calloc(end_of_scale[i][j], sizeof(double));
memset (histogram[i][j], 0, sizeof(double) * end_of_scale[i][j]);
}
}
}
// OPEN THE PC FILE //
auto pc = make_shared<geometry::PointCloud>();
if (io::ReadPointCloud(input_filename, *pc))
{
fprintf(stderr, "Successfully read PC %s\n", input_filename);
}
else {
fprintf(stderr, "Failed to read PC %s.\n", input_filename);
return EXIT_FAILURE;
}
// workaround ".xyzrgb" 3dtk 2^8 unsigned integer rgb range not read correctly by Open3D
if (strstr (input_filename, ".xyzrgb") || divide_color_by_255)
{
for (size_t i = 0; i < pc->points_.size(); i++) {
pc->colors_[i](0) = pc->colors_[i](0) / 255.0;
pc->colors_[i](1) = pc->colors_[i](1) / 255.0;
pc->colors_[i](2) = pc->colors_[i](2) / 255.0;
}
}
if (voxelize)
{
pc = pc->VoxelDownSample(voxel_size);
}
// print_pointcloud(*pc, false);
// METRIC PROCESSING //
geometry::KDTreeFlann kdtree;
kdtree.SetGeometry(*pc);
// for each point in the PC - parallel execution using OpenMP
#if USE_OPENMP__ == 1
#pragma omp parallel for num_threads(max_threads) schedule(dynamic,1000)
#endif
for (size_t i = 0; i < pc->points_.size(); i++) {
int label[MAX_NR_METRICS];
memset(label, 0, sizeof(int) * MAX_NR_METRICS);
// for fast retrieval of nearest neighbor we use kd-tree
std::vector<int> indices_vec(max_neiborhood_size + 1);
std::vector<double> dists_vec(max_neiborhood_size + 1);
// get the nearest neighbors of point with index "i"
kdtree.SearchKNN(pc->points_[i], max_neiborhood_size + 1, indices_vec, dists_vec);
for (int foo = 0; foo < neiborhood_list_size; foo++)
{
int nn = neiborhood_size[foo] + 1;
const Eigen::Vector3d &point_color = pc->colors_[i];
const Eigen::Vector3d &point_normal = pc->normals_[i];
for (int j = 1 ; j < nn; j++)
{ // starting from 1, as index 0 refers to the own point.
const Eigen::Vector3d &color = pc->colors_[indices_vec[j]];
const Eigen::Vector3d &normal = pc->normals_[indices_vec[j]];
// const Eigen::Vector3d &point = pc->points_[indices_vec[j]];
double diff = 0;
if (metric_enabled[DLCP_8B] != 0 || metric_enabled[DLCP_12B] != 0)
{
ColorSpace::Rgb a(point_color(0) * 255, point_color(1) * 255, point_color(2) * 255);
ColorSpace::Rgb b(color(0) * 255, color(1) * 255, color(2) * 255);
// CIE LAB Delta E 2000 (CIEDE2000)
diff = ColorSpace::Cie2000Comparison::Compare(&a, &b);
#if 0 // for debugging purposes...
ColorSpace::Lab lab_a, lab_b;
a.To<ColorSpace::Lab>(&lab_a);
b.To<ColorSpace::Lab>(&lab_b);
fprintf(stderr, "CIE2000 diff = %.5f, l = %f a = %f b = %f l = %f a = %f b = %f\n", diff, lab_a.l, lab_a.a, lab_a.b, lab_b.l, lab_b.a, lab_b.b);
#endif
if (metric_enabled[DLCP_8B] != 0)
{
// if (diff >= 0 && diff < 2.5) // ~ Just Noticeable Difference
// label[DLCP_8B] |= 0;
if (diff >= 2.5 && diff < 5.0)
label[DLCP_8B] |= 1 << 0;
if (diff >= 5.0 && diff < 7.5)
label[DLCP_8B] |= 1 << 1;
if (diff >= 7.5 && diff < 10.0)
label[DLCP_8B] |= 1 << 2;
if (diff >= 10.0 && diff < 12.5)
label[DLCP_8B] |= 1 << 3;
if (diff >= 12.5 && diff < 15.0)
label[DLCP_8B] |= 1 << 4;
if (diff >= 15.0 && diff < 17.5)
label[DLCP_8B] |= 1 << 5;
if (diff >= 17.5 && diff < 20.0)
label[DLCP_8B] |= 1 << 6;
if (diff >= 20.0)
label[DLCP_8B] |= 1 << 7;
}
if (metric_enabled[DLCP_12B] != 0)
{
// if (diff >= 0 && diff < 1.5) // ~ Just Noticeable Difference
// label[DLCP_12B] |= 0;
if (diff >= 1.5 && diff < 3.0)
label[DLCP_12B] |= 1 << 0;
if (diff >= 3.0 && diff < 4.5)
label[DLCP_12B] |= 1 << 1;
if (diff >= 4.5 && diff < 6.0)
label[DLCP_12B] |= 1 << 2;
if (diff >= 6.0 && diff < 7.5)
label[DLCP_12B] |= 1 << 3;
if (diff >= 7.5 && diff < 9.0)
label[DLCP_12B] |= 1 << 4;
if (diff >= 9.0 && diff < 10.5)
label[DLCP_12B] |= 1 << 5;
if (diff >= 10.5 && diff < 12.0)
label[DLCP_12B] |= 1 << 6;
if (diff >= 12.0 && diff < 13.5)
label[DLCP_12B] |= 1 << 7;
if (diff >= 13.5 && diff < 15.0)
label[DLCP_12B] |= 1 << 8;
if (diff >= 15.0 && diff < 16.5)
label[DLCP_12B] |= 1 << 9;
if (diff >= 16.5 && diff < 18.0)
label[DLCP_12B] |= 1 << 10;
if (diff >= 18.0)
label[DLCP_12B] |= 1 << 11;
}
}
double dist = 0;
if (metric_enabled[DGEO_16B] || metric_enabled[DGEO_12B] || metric_enabled[DGEO_8B])
{
dist = sqrt ( (pow((point_normal[0] - normal[0]), 2)) +
(pow((point_normal[1] - normal[1]), 2)) +
(pow((point_normal[2] - normal[2]), 2)) );
// fprintf(stderr, "dist: %.8f central pt normal: %.4f %.4f %.4f\nneighbo pt normal: %.4f %.4f %.4f\n\n", dist, point_normal(0), point_normal(1), point_normal(2), normal(0), normal(1), normal(2));
}
if (metric_enabled[DGEO_16B] != 0)
{
// if (dist >= 0 && dist < 0.05)
// label[DGEO_16B] |= 0;
if (dist >= 0.05 && dist < 0.1)
label[DGEO_16B] |= 1 << 0;
if (dist >= 0.1 && dist < 0.175)
label[DGEO_16B] |= 1 << 1;
if (dist >= 0.175 && dist < 0.275)
label[DGEO_16B] |= 1 << 2;
if (dist >= 0.275 && dist < 0.4)
label[DGEO_16B] |= 1 << 3;
if (dist >= 0.4 && dist < 0.525)
label[DGEO_16B] |= 1 << 4;
if (dist >= 0.525 && dist < 0.65)
label[DGEO_16B] |= 1 << 5;
if (dist >= 0.65 && dist < 0.775)
label[DGEO_16B] |= 1 << 6;
if (dist >= 0.775 && dist < 0.9)
label[DGEO_16B] |= 1 << 7;
if (dist >= 0.9 && dist < 1.025)
label[DGEO_16B] |= 1 << 8;
if (dist >= 1.025 && dist < 1.15)
label[DGEO_16B] |= 1 << 9;
if (dist >= 1.15 && dist < 1.275)
label[DGEO_16B] |= 1 << 10;
if (dist >= 1.275 && dist < 1.4)
label[DGEO_16B] |= 1 << 11;
if (dist >= 1.4 && dist < 1.525)
label[DGEO_16B] |= 1 << 12;
if (dist >= 1.525 && dist < 1.65)
label[DGEO_16B] |= 1 << 13;
if (dist >= 1.65 && dist < 1.8)
label[DGEO_16B] |= 1 << 14;
if (dist >= 1.8 && dist < 2.0)
label[DGEO_16B] |= 1 << 15;
}
if (metric_enabled[DGEO_12B] != 0)
{
// if (dist >= 0 && dist < 0.05)
// label[DGEO_16B] |= 0;
if (dist >= 0.05 && dist < 0.1)
label[DGEO_12B] |= 1 << 0;
if (dist >= 0.1 && dist < 0.3)
label[DGEO_12B] |= 1 << 1;
if (dist >= 0.3 && dist < 0.45)
label[DGEO_12B] |= 1 << 2;
if (dist >= 0.45 && dist < 0.6)
label[DGEO_12B] |= 1 << 3;
if (dist >= 0.6 && dist < 0.75)
label[DGEO_12B] |= 1 << 4;
if (dist >= 0.75 && dist < 0.9)
label[DGEO_12B] |= 1 << 5;
if (dist >= 0.9 && dist < 1.05)
label[DGEO_12B] |= 1 << 6;
if (dist >= 1.05 && dist < 1.2)
label[DGEO_12B] |= 1 << 7;
if (dist >= 1.2 && dist < 1.35)
label[DGEO_12B] |= 1 << 8;
if (dist >= 1.35 && dist < 1.55)
label[DGEO_12B] |= 1 << 9;
if (dist >= 1.55 && dist < 1.75)
label[DGEO_12B] |= 1 << 10;
if (dist >= 1.75 && dist < 2.0)
label[DGEO_12B] |= 1 << 11;
}
if (metric_enabled[DGEO_8B] != 0)
{
if ( normal(0) < 0 && normal(1) < 0 && normal(2) < 0 )
label[DGEO_8B] |= 1 << 0;
if ( normal(0) < 0 && normal(1) < 0 && normal(2) >= 0 )
label[DGEO_8B] |= 1 << 1;
if ( normal(0) < 0 && normal(1) >= 0 && normal(2) < 0 )
label[DGEO_8B] |= 1 << 2;
if ( normal(0) < 0 && normal(1) >= 0 && normal(2) >= 0 )
label[DGEO_8B] |= 1 << 3;
if ( normal(0) >= 0 && normal(1) < 0 && normal(2) < 0 )
label[DGEO_8B] |= 1 << 4;
if ( normal(0) >= 0 && normal(1) < 0 && normal(2) >= 0 )
label[DGEO_8B] |= 1 << 5;
if ( normal(0) >= 0 && normal(1) >= 0 && normal(2) < 0 )
label[DGEO_8B] |= 1 << 6;
if ( normal(0) >= 0 && normal(1) >= 0 && normal(2) >= 0 )
label[DGEO_8B] |= 1 << 7;
}
}
for (int i = 0; i < MAX_NR_METRICS; i++)
{
if (metric_enabled[i] != 0)
{
histogram[i][foo][label[i]]++;
}
}
}
}
// normalize
for (int i = 0; i < MAX_NR_METRICS; i++)
{
if (metric_enabled[i] != 0)
{
for (int foo = 0; foo < neiborhood_list_size; foo++)
{
for (int j = 0; j < end_of_scale[i][foo]; j++)
{
histogram[i][foo][j] = histogram[i][foo][j] / pc->points_.size();
}
}
}
}
// Results output
FILE *hist_fp;
// write
if (create_histogram == true)
{
if (split_files == true)
{
for (int i = 0; i < MAX_NR_METRICS; i++)
{
if (metric_enabled[i] != 0)
{
for (int foo = 0; foo < neiborhood_list_size; foo++)
{
char filename[4096];
// this is our output file format for split files!
sprintf(filename, "%s_M%02d_N%02d.csv", histogram_filename, i, neiborhood_size[foo]);
hist_fp = fopen(filename, "a");
if (hist_fp == NULL)
{
fprintf(stderr, "Could not write histogram output path: %s.\n", filename);
exit (EXIT_FAILURE);
}
fprintf(hist_fp, "%s,", input_filename);
for (int j = 0; j < end_of_scale[i][foo]; j++)
{
if ( fpclassify(histogram[i][foo][j]) == FP_ZERO ) // if (histogram[i][foo][j] == 0.0) ...
fprintf(hist_fp, "0.0%s", (j != (end_of_scale[i][foo] - 1))? ",":"");
else
fprintf(hist_fp, "%0.16f%s", histogram[i][foo][j],(j != (end_of_scale[i][foo] - 1))? ",":"");
}
fprintf(hist_fp, "\n");
fclose(hist_fp);
}
}
}
}
if (split_files == false)
{
hist_fp = fopen(histogram_filename, "a");
// Write the output //
if (hist_fp == NULL)
{
fprintf(stderr, "Could not write histogram output path: %s.\n", histogram_filename);
exit (EXIT_FAILURE);
}
// fwrite(normalize ? (void *)histogram_normalized : (void *)histogram, 8, end_of_scale, hist_fp); // ps: sizeof(double) == sizeof(uint64_t) == 8 // binary write
for (int i = 0; i < MAX_NR_METRICS; i++)
{
if (metric_enabled[i] != 0)
{
for (int foo = 0; foo < neiborhood_list_size; foo++)
{
fprintf(hist_fp, "%s,metric_%d,n_%d,", input_filename, i, neiborhood_size[foo]);
for (int j = 0; j < end_of_scale[i][foo]; j++)
{
if ( fpclassify(histogram[i][foo][j]) == FP_ZERO ) // if (histogram[i][foo][j] == 0.0) ...
fprintf(hist_fp, "0.0%s", (j != (end_of_scale[i][foo] - 1))? ",":"");
else
fprintf(hist_fp, "%0.16f%s", histogram[i][foo][j],(j != (end_of_scale[i][foo] - 1))? ",":"");
}
fprintf(hist_fp, "\n");
}
}
}
fclose(hist_fp);
}
}
return EXIT_SUCCESS;
}