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# -*- coding: utf-8 -*-
# How to use Random Sample Consensus model
# http://pointclouds.org/documentation/tutorials/random_sample_consensus.php#random-sample-consensus
import numpy as np
import pcl
import random
import pcl.pcl_visualization
import math
import sys # W[ argv 擾邽
# boost::shared_ptr<pcl::visualization::PCLVisualizer> simpleVis (pcl::PointCloud<pcl::PointXYZ>::ConstPtr cloud)
# {
# // -----Open 3D viewer and add point cloud-----
# boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer (new pcl::visualization::PCLVisualizer ("3D Viewer"));
# viewer->setBackgroundColor (0, 0, 0);
# viewer->addPointCloud<pcl::PointXYZ> (cloud, "sample cloud");
# viewer->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud");
# //viewer->addCoordinateSystem (1.0, "global");
# viewer->initCameraParameters ();
# return (viewer);
# }
argvs = sys.argv # R}hCi[Xg̎擾
argc = len(argvs) # ̌
# // initialize PointClouds
# pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
# pcl::PointCloud<pcl::PointXYZ>::Ptr final (new pcl::PointCloud<pcl::PointXYZ>);
cloud = pcl.PointCloud()
final = pcl.PointCloud()
# // populate our PointCloud with points
# cloud->width = 500;
# cloud->height = 1;
# cloud->is_dense = false;
# cloud->points.resize (cloud->width * cloud->height);
# for (size_t i = 0; i < cloud->points.size (); ++i)
# {
# if (pcl::console::find_argument (argc, argv, "-s") >= 0 || pcl::console::find_argument (argc, argv, "-sf") >= 0)
# {
# cloud->points[i].x = 1024 * rand () / (RAND_MAX + 1.0);
# cloud->points[i].y = 1024 * rand () / (RAND_MAX + 1.0);
# if (i % 5 == 0)
# cloud->points[i].z = 1024 * rand () / (RAND_MAX + 1.0);
# else if(i % 2 == 0)
# cloud->points[i].z = sqrt( 1 - (cloud->points[i].x * cloud->points[i].x)
# - (cloud->points[i].y * cloud->points[i].y));
# else
# cloud->points[i].z = - sqrt( 1 - (cloud->points[i].x * cloud->points[i].x)
# - (cloud->points[i].y * cloud->points[i].y));
# }
# else
# {
# cloud->points[i].x = 1024 * rand () / (RAND_MAX + 1.0);
# cloud->points[i].y = 1024 * rand () / (RAND_MAX + 1.0);
# if( i % 2 == 0)
# cloud->points[i].z = 1024 * rand () / (RAND_MAX + 1.0);
# else
# cloud->points[i].z = -1 * (cloud->points[i].x + cloud->points[i].y);
# }
# }
points = np.zeros((1000, 3), dtype=np.float32)
RAND_MAX = 1024
for i in range(0, 1000):
if argc > 1:
if argvs[1] == "-s" or argvs[1] == "-sf":
points[i][0] = 1024 * random.random () / (RAND_MAX + 1.0)
points[i][1] = 1024 * random.random () / (RAND_MAX + 1.0)
# print("x : " + str(points[i][0]))
# print("y : " + str(points[i][1]))
if i % 5 == 0:
points[i][2] = 1024 * random.random () / (RAND_MAX + 1.0)
elif i % 2 == 0:
points[i][2] = math.sqrt(math.fabs(1 - (points[i][0] * points[i][0]) - (points[i][1] * points[i][1])))
# points[i][2] = math.sqrt(1 )
else:
points[i][2] = -1 * math.sqrt(math.fabs(1 - (points[i][0] * points[i][0]) - (points[i][1] * points[i][1])))
# points[i][2] = -1 * math.sqrt( 1 )
else:
points[i][0] = 1024 * random.random () / RAND_MAX
points[i][1] = 1024 * random.random () / RAND_MAX
if i % 2 == 0:
points[i][2] = 1024 * random.random () / RAND_MAX
else:
points[i][2] = -1 * (points[i][0] + points[i][1])
else:
points[i][0] = 1024 * random.random () / RAND_MAX
points[i][1] = 1024 * random.random () / RAND_MAX
if i % 2 == 0:
points[i][2] = 1024 * random.random () / RAND_MAX
else:
points[i][2] = -1 * (points[i][0] + points[i][1])
cloud.from_array(points)
# std::vector<int> inliers;
# // created RandomSampleConsensus object and compute the appropriated model
# pcl::SampleConsensusModelSphere<pcl::PointXYZ>::Ptr model_s(new pcl::SampleConsensusModelSphere<pcl::PointXYZ> (cloud));
# pcl::SampleConsensusModelPlane<pcl::PointXYZ>::Ptr model_p (new pcl::SampleConsensusModelPlane<pcl::PointXYZ> (cloud));
# if(pcl::console::find_argument (argc, argv, "-f") >= 0)
# {
# pcl::RandomSampleConsensus<pcl::PointXYZ> ransac (model_p);
# ransac.setDistanceThreshold (.01);
# ransac.computeModel();
# ransac.getInliers(inliers);
# }
# else if (pcl::console::find_argument (argc, argv, "-sf") >= 0 )
# {
# pcl::RandomSampleConsensus<pcl::PointXYZ> ransac (model_s);
# ransac.setDistanceThreshold (.01);
# ransac.computeModel();
# ransac.getInliers(inliers);
# }
###
# inliers = vector[int]
model_s = pcl.SampleConsensusModelSphere(cloud)
model_p = pcl.SampleConsensusModelPlane(cloud)
if argc > 1:
if argvs[1] == "-f":
ransac = pcl.RandomSampleConsensus (model_p)
ransac.set_DistanceThreshold (.01)
ransac.computeModel()
inliers = ransac.get_Inliers()
elif argvs[1] == "-sf":
ransac = pcl.RandomSampleConsensus (model_s)
ransac.set_DistanceThreshold (.01)
ransac.computeModel()
inliers = ransac.get_Inliers()
else:
inliers = []
else:
inliers = []
# // copies all inliers of the model computed to another PointCloud
# pcl::copyPointCloud<pcl::PointXYZ>(*cloud, inliers, *final);
# final = pcl.copyPointCloud(cloud, inliers)
# pcl.copyPointCloud(cloud, inliers, final)
# final = cloud
print(str(len(inliers)))
if len(inliers) != 0:
finalpoints = np.zeros((len(inliers), 3), dtype=np.float32)
for i in range(0, len(inliers)):
finalpoints[i][0] = cloud[inliers[i]][0]
finalpoints[i][1] = cloud[inliers[i]][1]
finalpoints[i][2] = cloud[inliers[i]][2]
final.from_array(finalpoints)
# current(0.3.0) Windows Only Test
isWindows = False
if isWindows == True:
# creates the visualization object and adds either our orignial cloud or all of the inliers
# depending on the command line arguments specified.
# boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer;
# if (pcl::console::find_argument (argc, argv, "-f") >= 0 || pcl::console::find_argument (argc, argv, "-sf") >= 0)
# viewer = simpleVis(final);
# else
# viewer = simpleVis(cloud);
if argc > 1:
if argvs[1] == "-f" or argvs[1] == "-sf":
viewer = pcl.pcl_visualization.PCLVisualizering('3D Viewer')
viewer.SetBackgroundColor (0, 0, 0)
viewer.AddPointCloud (final, b'sample cloud')
viewer.SetPointCloudRenderingProperties (pcl.pcl_visualization.PCLVISUALIZER_POINT_SIZE, 3, b'sample cloud')
viewer.InitCameraParameters ()
else:
viewer = pcl.pcl_visualization.PCLVisualizering('3D Viewer')
viewer.SetBackgroundColor (0, 0, 0)
viewer.AddPointCloud (cloud, b'sample cloud')
viewer.SetPointCloudRenderingProperties (pcl.pcl_visualization.PCLVISUALIZER_POINT_SIZE, 3, b'sample cloud')
viewer.InitCameraParameters ()
else:
viewer = pcl.pcl_visualization.PCLVisualizering('3D Viewer')
viewer.SetBackgroundColor (0, 0, 0)
viewer.AddPointCloud (cloud, b'sample cloud')
viewer.SetPointCloudRenderingProperties (pcl.pcl_visualization.PCLVISUALIZER_POINT_SIZE, 3, b'sample cloud')
viewer.InitCameraParameters ()
# while (!viewer->wasStopped ())
# {
# viewer->spinOnce (100);
# boost::this_thread::sleep (boost::posix_time::microseconds (100000));
# }
isStopped = False
while isStopped == False:
isStopped = viewer.WasStopped()
viewer.SpinOnce (100)
# boost::this_thread::sleep (boost::posix_time::microseconds (100000));
else:
pass
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