def addGesture(self, name, points):
self.pointClouds.append(PointCloud(name, points))
num = 0
for i in range(len(self.pointClouds)):
if self.pointClouds[i].name == name:
num += 1
return num
def get_plane():
# s = 2*np.pi
pc = PointCloud()
for x in np.linspace(0, 1, 20):
for y in np.linspace(0, 1, 20):
pc.add_point(x, y, x)
return pc
def setPointCloudsDemo(self):
self.pointClouds.append(
PointCloud("T", [
Point(30, 7, 1),
Point(103, 7, 1),
Point(66, 7, 2),
Point(66, 87, 2)
]))
self.pointClouds.append(
PointCloud("N", [
Point(177, 92, 1),
Point(177, 2, 1),
Point(182, 1, 2),
Point(246, 95, 2),
Point(247, 87, 3),
Point(247, 1, 3)
]))
def recognize(self, points):
candidate = PointCloud("", points)
#print("here", len(points))
u = -1
b = math.inf
for i in range(len(self.pointClouds)):
d = GreedyCloudMatch(candidate.points, self.pointClouds[i])
if (d < b):
b = d
u = i
return "No match" if u == -1 else self.pointClouds[u].name
def get_circle():
pc = PointCloud()
t = np.linspace(0, 2 * np.pi, 1000)
points = []
for k in t:
x = np.cos(k) # + .03*np.sin(10*k)
y = np.sin(k) # + .03*np.sin(10*k)
pc.add_point(x, y, 0)
# for _ in xrange(100):
# x = 2*(np.random.random()-0.5)
# y = 2*(np.random.random()-0.5)
# pc.add_point(x, y, 0)
for pt in pc.points:
pt.normal = -pt.position / np.sqrt(np.dot(pt.position, pt.position))
return pc
def get_sphere():
r = 1
pc = PointCloud()
for phi in np.linspace(0, np.pi, 10):
for theta in np.linspace(0, 2 * np.pi, 10):
z = r * np.cos(phi)
x = r * np.sin(phi) * np.cos(theta)
y = r * np.sin(phi) * np.sin(theta)
# dx = (random.random() - 0.5)/ 10
# dy = (random.random() - 0.5)/ 10
# dz = (random.random() - 0.5)/ 10
# pc.add_point(x+dx,y+dy,z+dz)
pc.add_point(x, y, z)
for pt in pc.points:
pt.normal = -pt.position / np.sqrt(np.dot(pt.position, pt.position))
return pc
from skimage import filters
import os
import time
start_time = time.time()
FILE_NAME = "T_joint_attempt_2.txt"
PIT_ANGLE = int(input('Define PIT indentation angle in degrees:'))
os.chdir("t-scans/T_joint_scans/")
print("Loading point cloud...")
if os.path.exists(FILE_NAME) == True:
print(FILE_NAME)
npArr = np.loadtxt(fname=FILE_NAME)
npArr = np.delete(npArr, 3, 1)
pcd = PointCloud(npArr, type='NPARR')
print("Preprocessing point cloud...")
pcd.deleteZPoints(0)
#pcd.setOffset(0, 0, -120)
#pcd.pcd = o3d.geometry.PointCloud.remove_statistical_outlier(pcd.pcd, 1000, 1)[0]
pcd.getParameters()
#np.save(processed_file, np.asarray(pcd.pcd.points))
else:
print('Cannot access file')
exit()
#pcd.pcd = o3d.geometry.PointCloud.remove_statistical_outlier(pcd.pcd, 1000, 1)[0]
pcd.getPointCloudLines() # Construct arrays of point cloud lines
img = pcd.pcd_to_image()
npArr = pcd.img_to_pcd(img)
pcd = PointCloud(npArr, type='NPARR')
#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Fri Jul 6 13:25:59 2018 @author: cameron """ import pointCloud.PointCloud filePath = '/home/cameron/Dropbox/T2_Dataset/molGeom/T2_2_num_molGeom.cif' pc = PointCloud(filePath) pc.plot()