def initialize_las(path):
h = header.Header()
h.dataformat_id = 3
h.major_version = 1
h.minor_version = 3
h.scale = [0.00001, 0.00001, 0.00001]
f = file.File('pointcloud_classified.las', mode="w", header=h)
# Classification by name of pcl in input
for filename in glob.glob(os.path.join(path, '*.ply')):
print(filename)
name = filename.split("/")[-1]
name = name.split(".")[0]
pathfile = filename
if name == "rgb":
setClassification(f, pathfile, 1)
if name == "ground":
setClassification(f, pathfile, 2)
if name == "vegetation":
setClassification(f, pathfile, 3)
if name == "road":
setClassification(f, pathfile, 4)
if name == "cables":
setClassification(f, pathfile, 5)
if name == "building":
setClassification(f, pathfile, 6)
if name == "poles":
setClassification(f, pathfile, 7)
if name == "anomalies":
setClassification(f, pathfile, 8)
def toSphericalMercator(inputFile,outputFile):
# Open the LAS file and reproject to Pseudo-Mercator
# WGS 84 / Pseudo-Mercator -- Spherical Mercator, Google Maps, OpenStreetMap, Bing, ArcGIS, ESRI
targetProjection = srs.SRS()
targetProjection.set_userinput('epsg:3857') # Ending projection ( http://epsg.io/3857 )
inf = file.File(inputFile, header=None, mode='r', in_srs=None , out_srs=targetProjection)
inh = inf.header
# If the height is in US Feets scale them into meters
if (inh.srs.proj4.find('+units=us-ft')):
scaleZ = 0.3048006096012192
# Create the out put file.
outh = header.Header()
outh.dataformat_id = 1
outh.scale = [0.01,0.01,0.01]
outh.offset = [0.0,0.0,-0.0]
outsrs = srs.SRS()
outsrs.set_userinput('epsg:3857')
outh.srs = outsrs
outh.schema = inh.schema
# Open file
outf = file.File(outputFile, mode='w', header=outh)
# filter the outside the bBox (projected)
for p in inf:
p.z = p.z * scaleZ
outf.write(p)
outf.close();
def __init__(self, onlybuildings, PlaneImage):
only_building = file.File(onlybuildings, mode='r')
# Get the value of bounding box
height = width = 0
oldlasnm = onlybuildings
outputtxt = 'output.txt'
fout = open(outputtxt, 'w')
cmd = 'lasinfo ' + oldlasnm + '>' + outputtxt
subprocess.check_output(cmd, shell=True)
fout.close()
rows = [i.split()[2:] for i in open(outputtxt, 'r') if "Bounding" in i]
box = [i.strip(',') for i in rows[0]]
minx = float(box[0])
miny = float(box[1])
maxx = float(box[2])
maxy = float(box[3])
height = int(ceil(maxy - miny))
width = int(ceil(maxx - minx))
print(height, width)
h = header.Header()
h.dataformat_id = 3
# h = only_building.header
print(h.min, h.max)
lidar_list = [pnt for pnt in only_building]
im = Image.new('RGB', (height, width))
for i in range(0, len(lidar_list)):
temp = lidar_list[i]
temp.z = 0
im.putpixel(
[int(temp.x - minx), int(temp.y - miny)],
(temp.color.red, temp.color.green, temp.color.blue))
# im.append((temp.color.red, temp.color.green, temp.color.blue))
# print(temp.color.red, temp.color.green, temp.color.blue)
# fw.write(temp)
# im.putdata([(i.color.red,i.color.green, i.color.blue)
# for i in lidar_list])
im.save(PlaneImage)
print(len(lidar_list))
# fw.close()
only_building.close()
def open_output(self):
h = header.Header()
prec = 10**-(self.options.precision - 1)
h.scale = [prec, prec, prec]
if self.options.offset:
h.offset = [self.min.x, self.min.y, self.min.z]
if self.options.verbose:
print 'using minimum offsets', h.offset
if self.srs:
h.srs = self.srs
output = lasfile.File(self.options.output, mode='w', header=h)
return output
def write_file(version, format):
h = header.Header()
h.guid = g
h.date = datetime.datetime.now()
h.dataformat_id = format
h.major_version = 1
h.minor_version = version
h.min = [p.x, p.y, p.z]
h.max = [p.x, p.y, p.z]
h.point_return_count = [0L, number_of_points, 0L, 0L, 0L, 0L, 0L, 0L]
h.srs = s
h.date = p.time
f = file.File('1.%d_%d.las' % (version, format), mode='w', header=h)
for i in xrange(number_of_points):
f.write(p)
f.close()
def cropTile(inputFile, x, y, z):
# Get the edges of a tile
south, west, north, east = tileEdges(x, y, z)
scaleZ = 1.0
# Open the LAS file and reproject to Pseudo-Mercator
# WGS 84 / Pseudo-Mercator -- Spherical Mercator, Google Maps, OpenStreetMap, Bing, ArcGIS, ESRI
targetProjection = srs.SRS()
targetProjection.set_userinput(
'epsg:3857') # Ending projection ( http://epsg.io/3857 )
inf = file.File(inputFile,
header=None,
mode='r',
in_srs=None,
out_srs=targetProjection)
inh = inf.header
# If the height is in US Feets scale them into meters
if (inh.srs.proj4.find('+units=us-ft')):
scaleZ = 0.3048006096012192
# Create the out put file.
outh = header.Header()
outh.dataformat_id = 1
outh.scale = [0.01, 0.01, 0.01]
outh.offset = [0.0, 0.0, -0.0]
outsrs = srs.SRS()
outsrs.set_userinput('epsg:3857')
outh.srs = outsrs
outh.schema = inh.schema
# Open file
outf = file.File(str(int(x)) + '-' + str(int(y)) + '-' + str(int(z)) +
'.las',
mode='w',
header=outh)
# filter the outside the bBox (projected)
for p in inf:
if west <= p.x <= east and south <= p.y <= north:
p.z = p.z * scaleZ
outf.write(p)
print '%.2f,%.2f,%.2f' % (p.x, p.y, p.z)
outf.close()
def removevegetation(self, newlasfile, oldlasfile, NdviImage):
h = header.Header()
h.dataformat_id = 3
h.minor_version = 1
###############################################
'''get bounding box'''
##################################################
outputtxt = './data/output.txt'
fout = open(outputtxt, 'a')
cmd = 'lasinfo ' + oldlasfile + '>' + outputtxt
subprocess.check_output(cmd, shell=True)
fout.close()
rows = [i.split()[2:] for i in open(outputtxt, 'r') if "Bounding" in i]
box = [i.strip(',') for i in rows[0]]
minx = float(box[0])
miny = float(box[1])
maxx = float(box[2])
maxy = float(box[3])
######################################################
g = gdal.Open(NdviImage)
lasfile = file.File(oldlasfile, mode='r')
newlas = file.File(newlasfile, mode='w', header=h)
#######################################################
ndviband = g.ReadAsArray()
ndviband = np.array(ndviband, dtype=float)
m = len(ndviband) # y axe len
n = len(ndviband[0]) # x axe len
#######################################################
# print lastotif(2035311.686,525276.565,minx,miny,maxx,maxy,m,n)
count = 0
for p in lasfile:
xy = self.lastotif(p.x, p.y, minx, miny, maxx, maxy, m, n)
yval = xy[1]
xval = xy[0]
if yval <= m and xval <= n and ndviband[yval - 1][xval - 1] < 0.25:
newlas.write(p)
count += 1
print count
newlas.close()
def open_output(self):
self.header = header.Header()
prec = 10**-(self.options.precision-1)
self.header.scale = [prec, prec, prec]
if self.options.offset:
h.offset = [self.minx, self.miny, self.minz]
if self.options.verbose:
print 'using minimum offsets', h.offset
self.header.compressed = self.options.compressed
if self.srs:
self.header.srs = self.srs
self.header.data_format_id = 1
output = lasfile.File(self.options.output,mode='w',header=self.header)
return output
from liblas import header h = header.Header() h.dataformat_id = 1
#print panel startTime = time() xMin = panel[0] - 5 yMin = panel[1] - 5 zMin = panel[2] - 5 xMax = panel[3] + 5 yMax = panel[4] + 5 zMax = panel[5] + 5 dx = 0.5 dy = 0.5 print "Создание заголовка" # Запись файла #from liblas import header h = header.Header() # Формируем заголовок ### Support storing time values h.major_version = 1 h.minor_version = 2 h.dataformat_id = 2 h.min = [xMin, yMin, zMin] h.max = [xMax, yMax, zMax] h.scale = [0.01, 0.01, 0.01] h.offset = [0.0, 0.0, 0.0] #h.point_records_count = int(((xMax-xMin)/dx) * ((yMax-yMin)/dy)) #h.project_id = "00000000-0000-0000-0000-000000000000" #h.guid = "00000000-0000-0000-0000-000000000000" #s.proj4 = '' print "Запись в файл LAS" las_file = file.File(name_las + ".las", mode='w',
