def compute_algo_circumference():
# Time measurement
start = time.clock()
# Read lidars datas
lidarsSet.read_datas_files()
# Plot raw datas
lidarsSet.plot_raw_datas()
# Compute raw datas into merged datas
lidarsSet.compute_raw_datas()
# Remove outliers
if len(utility.mergedPointsXY) > constants.min_points:
#utility.remove_outliers()
# Compute contour
contour.contour()
cust_print("Circumference computed in: " + str(time.clock() - start) +
' sec.')
# Show the plots
if constants.disp_charts:
cust_print('\nClose all figures to continue...\n')
plt.show(block=True)
else:
cust_print(
' Not enough data point have been read in the expected area!')
def createAlgsList(self):
# First we populate the list of algorithms with those created
# extending GeoAlgorithm directly (those that execute GDAL
# using the console)
self.preloadedAlgs = [nearblack(), information(), warp(), translate(),
rgb2pct(), pct2rgb(), merge(), buildvrt(), polygonize(), gdaladdo(),
ClipByExtent(), ClipByMask(), contour(), rasterize(), proximity(),
sieve(), fillnodata(), ExtractProjection(), gdal2xyz(),
hillshade(), slope(), aspect(), tri(), tpi(), roughness(),
ColorRelief(), GridInvDist(), GridAverage(), GridNearest(),
GridDataMetrics(), gdaltindex(), gdalcalc(), rasterize_over(),
# ----- OGR tools -----
OgrInfo(), Ogr2Ogr(), Ogr2OgrClip(), Ogr2OgrClipExtent(),
Ogr2OgrToPostGis(), Ogr2OgrToPostGisList(), Ogr2OgrPointsOnLines(),
Ogr2OgrBuffer(), Ogr2OgrDissolve(), Ogr2OgrOneSideBuffer(),
Ogr2OgrTableToPostGisList(), OgrSql(),
]
# And then we add those that are created as python scripts
folder = self.scriptsFolder()
if os.path.exists(folder):
for descriptionFile in os.listdir(folder):
if descriptionFile.endswith('py'):
try:
fullpath = os.path.join(self.scriptsFolder(),
descriptionFile)
alg = GdalScriptAlgorithm(fullpath)
self.preloadedAlgs.append(alg)
except WrongScriptException as e:
ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, e.msg)
def createAlgsList(self):
# First we populate the list of algorithms with those created
# extending GeoAlgorithm directly (those that execute GDAL
# using the console)
self.preloadedAlgs = [nearblack(), information(), warp(), translate(),
rgb2pct(), pct2rgb(), merge(), polygonize(), gdaladdo(),
ClipByExtent(), ClipByMask(), contour(), rasterize(), proximity(),
sieve(), fillnodata(), ExtractProjection(), gdal2xyz(),
hillshade(), slope(), aspect(), tri(), tpi(), roughness(),
ColorRelief(), GridInvDist(), GridAverage(), GridNearest(),
GridDataMetrics(),
# ----- OGR tools -----
OgrInfo(), Ogr2Ogr(), OgrSql(),
]
# And then we add those that are created as python scripts
folder = self.scriptsFolder()
if os.path.exists(folder):
for descriptionFile in os.listdir(folder):
if descriptionFile.endswith('py'):
try:
fullpath = os.path.join(self.scriptsFolder(),
descriptionFile)
alg = GdalScriptAlgorithm(fullpath)
self.preloadedAlgs.append(alg)
except WrongScriptException, e:
ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, e.msg)
def __find_contours(self, img, thresh):
#1
src = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 2
src = cv2.GaussianBlur(src, (5, 5), 0)
# Set threshold and maxValue
#thresh = 200
maxValue = 255
# 3
th, dst = cv2.threshold(src, thresh, maxValue, cv2.THRESH_BINARY)
# 4
edges = cv2.Canny(dst, 0, 75, apertureSize=5)
# 5
dst, conts, hierarchy = cv2.findContours(dst, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
contours = []
print hierarchy[0]
for x in xrange(0, len(conts), 1):
a_contour = contour(conts[x], hierarchy[0][x][0],
hierarchy[0][x][1], hierarchy[0][x][2],
hierarchy[0][x][3])
contours.append(a_contour)
return contours
def __find_contours(self, image, thresh):
contours = []
#opencv functies die uit de mee gegeven afbeelding contouren en hun hierarchy haalt, zie SAD voor details
#find contours returned een lijst met contouren, een contour is een lijst met punten.
#find contours geeft ook een lijst met een hierarchy, een hierarchy is een lijst waarbij de index over een komt met het
#bijbehorende contour in de hierarchy staan de previous(de vorige contour met de zelfde parrent), de next(het volgende contour met de zelfde parrent), de parrent(welk countour om de contour heen zit) en de child(wat is het eerste contour in ddeze contour)
#all deze getallen verwijzen naar een index van dit desbetrevvende contour. wenneer een dergelijk veld leeg is is de waarde -1
#structuur hierarchy: [Next, Previous, First_Child, Parent]
src = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
src = cv2.GaussianBlur(src, (5, 5), 0)
maxValue = 255
th, dst = cv2.threshold(src, thresh, maxValue, cv2.THRESH_BINARY)
edges = cv2.Canny(dst, 0, 75, apertureSize=5)
dst, conts, hierarchy = cv2.findContours(dst, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
for index in xrange(0, len(conts) - 1, 1):
cont = contour(conts[index])
j = hierarchy[0][index][2] #j is de index van de parrent
if j > -1: #oftewel als er een parrent is
cont.add_child(j)
while hierarchy[0][j][
0] > -1: #oftewel while er een next child is
j = hierarchy[0][j][
2] #j is nu index van de volgende child
cont.add_child(j)
contours.append(cont)
return contours
def createAlgsList(self):
# First we populate the list of algorithms with those created
# extending GeoAlgorithm directly (those that execute GDAL
# using the console)
self.preloadedAlgs = [
nearblack(),
information(),
warp(),
translate(),
rgb2pct(),
pct2rgb(),
merge(),
buildvrt(),
polygonize(),
gdaladdo(),
ClipByExtent(),
ClipByMask(),
contour(),
rasterize(),
proximity(),
sieve(),
fillnodata(),
ExtractProjection(),
gdal2xyz(),
hillshade(),
slope(),
aspect(),
tri(),
tpi(),
roughness(),
ColorRelief(),
GridInvDist(),
GridAverage(),
GridNearest(),
GridDataMetrics(),
gdaltindex(),
gdalcalc(),
rasterize_over(),
retile(),
gdal2tiles(),
# ----- OGR tools -----
OgrInfo(),
Ogr2Ogr(),
Ogr2OgrClip(),
Ogr2OgrClipExtent(),
Ogr2OgrToPostGis(),
Ogr2OgrToPostGisList(),
Ogr2OgrPointsOnLines(),
Ogr2OgrBuffer(),
Ogr2OgrDissolve(),
Ogr2OgrOneSideBuffer(),
Ogr2OgrTableToPostGisList(),
OgrSql(),
]
def createAlgsList(self):
# First we populate the list of algorithms with those created
# extending GeoAlgorithm directly (those that execute GDAL
# using the console)
self.preloadedAlgs = [
nearblack(),
information(),
warp(),
translate(),
rgb2pct(),
pct2rgb(),
merge(),
buildvrt(),
polygonize(),
gdaladdo(),
ClipByExtent(),
ClipByMask(),
contour(),
rasterize(),
proximity(),
sieve(),
fillnodata(),
ExtractProjection(),
gdal2xyz(),
hillshade(),
slope(),
aspect(),
tri(),
tpi(),
roughness(),
ColorRelief(),
GridInvDist(),
GridAverage(),
GridNearest(),
GridDataMetrics(),
gdaltindex(),
gdalcalc(),
rasterize_over(),
retile(),
gdal2tiles(),
# ----- OGR tools -----
OgrInfo(),
Ogr2Ogr(),
Ogr2OgrClip(),
Ogr2OgrClipExtent(),
Ogr2OgrToPostGis(),
Ogr2OgrToPostGisList(),
Ogr2OgrPointsOnLines(),
Ogr2OgrBuffer(),
Ogr2OgrDissolve(),
Ogr2OgrOneSideBuffer(),
Ogr2OgrTableToPostGisList(),
OgrSql(),
]
import h5py
import contour
import math
h5file = h5py.File('ng__t.h5')
temp = h5file['image']['data'][0].T[::-1]
contours = contour.contour(temp, [310., 1550.])
print("full: %d" % reduce(
lambda x, y: x + y, [len(l) for c in contours.values() for l in c.lines]))
f = open('temp_full.svg', 'w')
f.write(contour.svg(temp.shape[0], temp.shape[1], contours))
f.close()
for theta in [5, 10, 15, 20]:
threshold = math.cos(theta * math.pi / 180.0)
simple_contours = contour.simplify(contours, threshold)
print(u"%02d\u00b0: %d" %
(theta,
reduce(lambda x, y: x + y,
[len(l) for c in simple_contours.values()
for l in c.lines])))
f = open('temp_%02d.svg' % theta, 'w')
f.write(contour.svg(temp.shape[0], temp.shape[1], simple_contours))
f.close()
def contour_at(self, f, lvl):
# Find a point on f at lvl
e0 = f.edge
if e0.has_level(lvl):
pass
elif e0.next.has_level(lvl):
e0 = e0.next
pX0 = e0.at_level(lvl)
c = contour(pX0)
walking = True
forward = True
currEdge = e0.twin
switch = True
while walking:
if switch:
e1 = currEdge.next
e2 = e1.next
switch = False
else:
e1 = currEdge.prev
e2 = e1.prev
switch = True
if forward:
if e1.has_level(lvl):
pXc = e1.at_level(lvl)
if e1.twin != None and e1.twin.next != None:
currEdge = e1.twin
else:
forward = False
switch = False
currEdge = e0
elif e2.has_level(lvl):
pXc = e2.at_level(lvl)
if e2.twin != None and e2.twin.next != None:
currEdge = e2.twin
else:
forward = False
switch = False
currEdge = e0
if e1 == e0 or e2 == e0:
walking = False
c.append(pXc)
else:
if e1.has_level(lvl):
pXc = e1.at_level(lvl)
if e1.twin != None:
currEdge = e1.twin
else:
walking = False
elif e2.has_level(lvl):
pXc = e2.at_level(lvl)
if e2.twin != None:
currEdge = e2.twin
else:
walking = False
c.prepend(pXc)
c.complete(forward)
return c
import h5py
import contour
import math
h5file=h5py.File('ng__t.h5')
temp=h5file['image']['data'][0].T[::-1]
contours=contour.contour(temp,[310.,1550.])
print("full: %d"%reduce(lambda x,y: x+y,[len(l) for c in contours.values() for l in c.lines]))
f=open('temp_full.svg','w')
f.write(contour.svg(temp.shape[0],temp.shape[1],contours))
f.close()
for theta in [5,10,15,20]:
threshold=math.cos(theta*math.pi/180.0)
simple_contours=contour.simplify(contours,threshold)
print(u"%02d\u00b0: %d"%(theta,reduce(lambda x,y: x+y,[len(l) for c in simple_contours.values() for l in c.lines])))
f=open('temp_%02d.svg'%theta,'w')
f.write(contour.svg(temp.shape[0],temp.shape[1],simple_contours))
f.close()
