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ikd_Tree_demo.cpp 10.70 KB
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Ecstasy-EC 提交于 2022-01-07 17:42 +08:00 . Update demo description
/*
Description: An example for using ikd-Tree
Author: Yixi Cai
Email: yixicai@connect.hku.hk
*/
#include <ikd_Tree.h>
#include <stdio.h>
#include <stdlib.h>
#include <random>
#include <algorithm>
using PointType = ikdTree_PointType;
using PointVector = KD_TREE<PointType>::PointVector;
#define X_MAX 5.0
#define X_MIN -5.0
#define Y_MAX 5.0
#define Y_MIN -5.0
#define Z_MAX 5.0
#define Z_MIN -5.0
#define Point_Num 20000
#define New_Point_Num 200
#define Delete_Point_Num 100
#define Nearest_Num 5
#define Test_Time 1000
#define Search_Counter 200
#define Box_Length 1.5
#define Box_Num 4
#define Delete_Box_Switch true
#define Add_Box_Switch true
PointVector point_cloud;
PointVector cloud_increment;
PointVector cloud_decrement;
PointVector cloud_deleted;
PointVector search_result;
PointVector raw_cmp_result;
PointVector DeletePoints;
PointVector removed_points;
KD_TREE<ikdTree_PointType> ikd_Tree(0.3,0.6,0.2);
float rand_float(float x_min, float x_max){
float rand_ratio = rand()/(float)RAND_MAX;
return (x_min + rand_ratio * (x_max - x_min));
}
/*
Generate the points to initialize an incremental k-d tree
*/
void generate_initial_point_cloud(int num){
PointVector ().swap(point_cloud);
PointType new_point;
for (int i=0;i<num;i++){
new_point.x = rand_float(X_MIN, X_MAX);
new_point.y = rand_float(Y_MIN, Y_MAX);
new_point.z = rand_float(Z_MIN, Z_MAX);
point_cloud.push_back(new_point);
}
return;
}
/*
Generate random new points for point-wise insertion to the incremental k-d tree
*/
void generate_increment_point_cloud(int num){
PointVector ().swap(cloud_increment);
PointType new_point;
for (int i=0;i<num;i++){
new_point.x = rand_float(X_MIN, X_MAX);
new_point.y = rand_float(Y_MIN, Y_MAX);
new_point.z = rand_float(Z_MIN, Z_MAX);
point_cloud.push_back(new_point);
cloud_increment.push_back(new_point);
}
return;
}
/*
Generate random points for point-wise delete on the incremental k-d tree
*/
void generate_decrement_point_cloud(int num){
PointVector ().swap(cloud_decrement);
auto rng = default_random_engine();
shuffle(point_cloud.begin(), point_cloud.end(), rng);
for (int i=0;i<num;i++){
cloud_decrement.push_back(point_cloud[point_cloud.size()-1]);
point_cloud.pop_back();
}
return;
}
/*
Generate random boxes for box-wise re-insertion on the incremental k-d tree
*/
void generate_box_increment(vector<BoxPointType> & Add_Boxes, float box_length, int box_num){
vector<BoxPointType> ().swap(Add_Boxes);
float d = box_length/2;
float x_p, y_p, z_p;
BoxPointType boxpoint;
for (int k=0;k < box_num; k++){
x_p = rand_float(X_MIN, X_MAX);
y_p = rand_float(Y_MIN, Y_MAX);
z_p = rand_float(Z_MIN, Z_MAX);
boxpoint.vertex_min[0] = x_p - d;
boxpoint.vertex_max[0] = x_p + d;
boxpoint.vertex_min[1] = y_p - d;
boxpoint.vertex_max[1] = y_p + d;
boxpoint.vertex_min[2] = z_p - d;
boxpoint.vertex_max[2] = z_p + d;
Add_Boxes.push_back(boxpoint);
int n = cloud_deleted.size();
int counter = 0;
while (counter < n){
PointType tmp = cloud_deleted[cloud_deleted.size()-1];
cloud_deleted.pop_back();
if (tmp.x +EPSS < boxpoint.vertex_min[0] || tmp.x - EPSS > boxpoint.vertex_max[0] || tmp.y + EPSS < boxpoint.vertex_min[1] || tmp.y - EPSS > boxpoint.vertex_max[1] || tmp.z + EPSS < boxpoint.vertex_min[2] || tmp.z - EPSS > boxpoint.vertex_max[2]){
cloud_deleted.insert(cloud_deleted.begin(),tmp);
} else {
point_cloud.push_back(tmp);
}
counter += 1;
}
}
}
/*
Generate random boxes for box-wise delete on the incremental k-d tree
*/
void generate_box_decrement(vector<BoxPointType> & Delete_Boxes, float box_length, int box_num){
vector<BoxPointType> ().swap(Delete_Boxes);
float d = box_length/2;
float x_p, y_p, z_p;
BoxPointType boxpoint;
for (int k=0;k < box_num; k++){
x_p = rand_float(X_MIN, X_MAX);
y_p = rand_float(Y_MIN, Y_MAX);
z_p = rand_float(Z_MIN, Z_MAX);
boxpoint.vertex_min[0] = x_p - d;
boxpoint.vertex_max[0] = x_p + d;
boxpoint.vertex_min[1] = y_p - d;
boxpoint.vertex_max[1] = y_p + d;
boxpoint.vertex_min[2] = z_p - d;
boxpoint.vertex_max[2] = z_p + d;
Delete_Boxes.push_back(boxpoint);
int n = point_cloud.size();
int counter = 0;
while (counter < n){
PointType tmp = point_cloud[point_cloud.size()-1];
point_cloud.pop_back();
if (tmp.x +EPSS < boxpoint.vertex_min[0] || tmp.x - EPSS > boxpoint.vertex_max[0] || tmp.y + EPSS < boxpoint.vertex_min[1] || tmp.y - EPSS > boxpoint.vertex_max[1] || tmp.z + EPSS < boxpoint.vertex_min[2] || tmp.z - EPSS > boxpoint.vertex_max[2]){
point_cloud.insert(point_cloud.begin(),tmp);
} else {
cloud_deleted.push_back(tmp);
}
counter += 1;
}
}
}
/*
Generate target point for nearest search on the incremental k-d tree
*/
PointType generate_target_point(){
PointType point;
point.x = rand_float(X_MIN, X_MAX);;
point.y = rand_float(Y_MIN, Y_MAX);
point.z = rand_float(Z_MIN, Z_MAX);
return point;
}
int main(int argc, char** argv){
srand((unsigned) time(NULL));
printf("Testing ...\n");
int counter = 0;
bool flag = true;
vector<BoxPointType> Delete_Boxes;
vector<BoxPointType> Add_Boxes;
vector<float> PointDist;
float average_total_time = 0.0;
float box_delete_time = 0.0;
float box_add_time = 0.0;
float add_time = 0.0;
float delete_time = 0.0;
float search_time = 0.0;
int box_delete_counter = 0;
int box_add_counter = 0;
PointType target;
// Initialize k-d tree
generate_initial_point_cloud(Point_Num);
auto t1 = chrono::high_resolution_clock::now();
ikd_Tree.Build(point_cloud);
auto t2 = chrono::high_resolution_clock::now();
auto build_duration = chrono::duration_cast<chrono::microseconds>(t2-t1).count();
while (counter < Test_Time){
printf("Test %d:\n",counter+1);
// Point-wise Insertion
generate_increment_point_cloud(New_Point_Num);
t1 = chrono::high_resolution_clock::now();
ikd_Tree.Add_Points(cloud_increment, false);
t2 = chrono::high_resolution_clock::now();
auto add_duration = chrono::duration_cast<chrono::microseconds>(t2-t1).count();
auto total_duration = add_duration;
printf("Add point time cost is %0.3f ms\n",float(add_duration)/1e3);
// Point-wise Delete
generate_decrement_point_cloud(Delete_Point_Num);
t1 = chrono::high_resolution_clock::now();
ikd_Tree.Delete_Points(cloud_decrement);
t2 = chrono::high_resolution_clock::now();
auto delete_duration = chrono::duration_cast<chrono::microseconds>(t2-t1).count();
total_duration += delete_duration;
printf("Delete point time cost is %0.3f ms\n",float(delete_duration)/1e3);
// Box-wise Delete
auto box_delete_duration = chrono::duration_cast<chrono::microseconds>(t2-t2).count();
if (Delete_Box_Switch && (counter+1) % 500 == 0){
printf("Waiting to generate 4 cuboids for box-wise delete test...\n");
generate_box_decrement(Delete_Boxes, Box_Length, Box_Num);
t1 = chrono::high_resolution_clock::now();
ikd_Tree.Delete_Point_Boxes(Delete_Boxes);
t2 = chrono::high_resolution_clock::now();
box_delete_counter ++;
box_delete_duration += chrono::duration_cast<chrono::microseconds>(t2-t1).count();
printf("Delete box points time cost is %0.3f ms\n",float(box_delete_duration)/1e3);
}
total_duration += box_delete_duration;
// Box-wise Re-insertion
auto box_add_duration = chrono::duration_cast<chrono::microseconds>(t2-t2).count();
if (Add_Box_Switch && (counter+1) % 100 == 0){
generate_box_increment(Add_Boxes, Box_Length, Box_Num);
t1 = chrono::high_resolution_clock::now();
ikd_Tree.Add_Point_Boxes(Add_Boxes);
t2 = chrono::high_resolution_clock::now();
box_add_counter ++;
box_add_duration += chrono::duration_cast<chrono::microseconds>(t2-t1).count();
printf("Add box points time cost is %0.3f ms\n",float(box_add_duration)/1e3);
}
total_duration += box_add_duration;
// Nearest Search
auto search_duration = chrono::duration_cast<chrono::microseconds>(t2-t2).count();
for (int k=0;k<Search_Counter;k++){
PointVector ().swap(search_result);
target = generate_target_point();
t1 = chrono::high_resolution_clock::now();
ikd_Tree.Nearest_Search(target, Nearest_Num, search_result, PointDist);
t2 = chrono::high_resolution_clock::now();
search_duration += chrono::duration_cast<chrono::microseconds>(t2-t1).count();
}
printf("Search nearest point time cost is %0.3f ms\n",float(search_duration)/1e3);
total_duration += search_duration;
printf("Total time is %0.3f ms\n",total_duration/1e3);
printf("Tree size is: %d\n\n", ikd_Tree.size());
// If necessary, the removed points can be collected.
PointVector ().swap(removed_points);
ikd_Tree.acquire_removed_points(removed_points);
// Calculate total running time
average_total_time += float(total_duration)/1e3;
box_delete_time += float(box_delete_duration)/1e3;
box_add_time += float(box_add_duration)/1e3;
add_time += float(add_duration)/1e3;
delete_time += float(delete_duration)/1e3;
search_time += float(search_duration)/1e3;
counter += 1;
}
printf("Finished %d times test\n",counter);
printf("Average Time:\n");
printf("Total Time is: %0.3fms\n",average_total_time/1e3);
printf("Point-wise Insertion (%d points): %0.3fms\n",New_Point_Num,add_time/counter);
printf("Point-wise Delete (%d points): %0.3fms\n", Delete_Point_Num,delete_time/counter);
printf("Box-wse Delete (%d boxes): %0.3fms\n",Box_Num,box_delete_time/box_delete_counter);
printf("Box-wse Re-insertion (%d boxes): %0.3fms\n",Box_Num,box_add_time/box_add_counter);
printf("Nearest Search (%d points): %0.3fms\n", Search_Counter,search_time/counter);
return 0;
}
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