def getSettingsForRunId(runId): """Return the settings instance for a given run""" runInstance = Run.selectBy(id=runId)[0] # Get the cut ratios cutRatios = getCutRatiosForRunId(runId) settings = Settings(cutRatios) settings.setThresholds(runInstance.trsh1, runInstance.trsh2) settings.setLo(runInstance.lo) settings.setUp(runInstance.up) settings.setMarginPercentage(runInstance.marginPercentage) return settings
def main():
"""
Just the test
This method is a good resource on how to handle the results.
Save images in this method if you have to.
"""
filename = sys.argv[1]
image = highgui.cvLoadImage (filename)
cutRatios = [lib.PHI]
#cutRatios = [0.618]
settings = Settings(cutRatios)
image = highgui.cvLoadImage (filename)
thickness = 4
settings.setMarginPercentage(0.025)
settings.setMethod(sys.argv[3])
cut = int(sys.argv[2])
winname = sys.argv[1]
#settings.setThresholds(100,150)
# Set the color for the boxes
#color = lib.COL_BLACK
#color = lib.COL_WHITE
#color = lib.COL_RED
color = lib.COL_GREEN
#color = lib.COL_BLUE
blobImg = blobResult(image, settings, cut)
boxxImg = boundingBoxResult(image, settings, cut, thickness, color)
cutt = lib.findMeans(cv.cvGetSize(image), settings.cutRatios[0])[cut]
# cuttet verdi, dog skal det vi generaliseres lidt
oriantesen = cutt.getPoints()[0].x == cutt.getPoints()[1].x
if oriantesen:
cutPixel = cutt.getPoints()[1].x
else:
cutPixel = cutt.getPoints()[1].y
if oriantesen:
# print 'hej'
cv.cvLine(boxxImg, cv.cvPoint(cutPixel, cutt.getPoints()[0].y), cv.cvPoint(cutPixel, cutt.getPoints()[1].y), lib.COL_RED)
else:
cv.cvLine(boxxImg, cv.cvPoint(cutt.getPoints()[0].x, cutPixel), cv.cvPoint(cutt.getPoints()[1].x, cutPixel), lib.COL_RED)
# Save images
highgui.cvSaveImage('flood_cut_%s.png' % cut, boxxImg)
highgui.cvSaveImage('blobs_cut_%s.png' % cut, blobImg)
# Show images
compareImages(blobImg, boxxImg, "blob", winname)
def main():
"""
Just the test
This method is a god resource on how to handle the results
"""
filename = sys.argv[1]
image = highgui.cvLoadImage (filename)
cutRatios = [0.61]
settings = Settings(cutRatios)
image = highgui.cvLoadImage (filename)
thickness = 4
settings.setMarginPercentage(0.025)
cutNo = int(sys.argv[2])
cut = lib.findMeans(cv.cvGetSize(image), settings.cutRatios[0])[cutNo]
# Get the BW edge image
edgeImage = naiveMethod.getEdgeImage(image, settings)
(blobImg, comp) = naiveMethod.analyzeCut(image, edgeImage, cut, settings, 'True')
#liste af liste
gridPointsList = grid.gridIt(blobImg, comp)
#print gridPointsList
points = centerOfMass(gridPointsList)
#(x,y)
for point in points:
cv.cvLine(image, cv.cvPoint(point, 0), cv.cvPoint(point,600), COL_GREEN)
lib.drawBoundingBoxes(image, comp)
#highgui.cvSaveImage('floodfillbilledet.png', blobImg)
#highgui.cvSaveImage('boindingboxbilledet.png', boxxImg)
showImage(image, 'name')
def main():
"""
Just the test
This method is a god resource on how to handle the results
"""
filename = sys.argv[1]
image = highgui.cvLoadImage (filename)
cutRatios = [0.75]
#cutRatios = [lib.PHI]
settings = Settings(cutRatios)
image = highgui.cvLoadImage (filename)
thickness = 4
settings.setMarginPercentage(0.025)
cutNo = int(sys.argv[2])
#udtrak af cut
cut = lib.findMeans(cv.cvGetSize(image), settings.cutRatios[0])[cutNo]
# cuttet verdi, dog skal det vi generaliseres lidt
oriantesen = cut.getPoints()[0].x == cut.getPoints()[1].x
if oriantesen:
cutPixel = cut.getPoints()[1].x
else:
cutPixel = cut.getPoints()[1].y
#Get the BW edge image
edgeImage = expandedMethod.getEdgeImage(image, settings)
(blobImg, comp) = expandedMethod.analyzeCut(image, edgeImage, cut, settings, 'True')
#Liste af liste
# Find the margin
margin = marginCalculator.getPixels(image, cut, settings.marginPercentage)
lib.drawMargin(image, cut, margin)
#Udregning af gridet
gridPointsList = grid.gridIt(blobImg, comp)
#hvor mange pixel der er pa den ende side i forhold til den anden, i procent
pixelRatio = pixelSideCounter(gridPointsList, cutPixel, oriantesen)
print pixelRatio
#Udregning af center og mass
points = centerOfMass(gridPointsList, oriantesen)
#Draw the cut
#print cut.getPoints()[0].y
#print cut.getPoints()[1].y
#print cut.getPoints()[0].x
#print cut.getPoints()[1].x
#print cutPixel
if oriantesen:
# print 'hej'
cv.cvLine(image, cv.cvPoint(cutPixel, cut.getPoints()[0].y), cv.cvPoint(cutPixel, cut.getPoints()[1].y), COL_RED)
else:
cv.cvLine(image, cv.cvPoint(cut.getPoints()[0].x, cutPixel), cv.cvPoint(cut.getPoints()[1].x, cutPixel), COL_RED)
#Draw center of mass
for point in points:
if oriantesen:
# print 'hej'
# print point
cv.cvLine(image, cv.cvPoint(point, cut.getPoints()[0].y), cv.cvPoint(point, cut.getPoints()[1].y), COL_GREEN)
else:
# print point
cv.cvLine(image, cv.cvPoint(cut.getPoints()[0].x, point), cv.cvPoint(cut.getPoints()[1].x, point), COL_GREEN)
lib.drawBoundingBoxes(image, comp, 4, COL_GREEN)
#highgui.cvSaveImage('floodfillbilledet.png', blobImg)
highgui.cvSaveImage('centerOfMass.png', image)
showImage(image, 'name')
def main():
"""
Just the test
This method is a good resource on how to handle the results.
Save images in this method if you have to.
"""
filename = sys.argv[1]
image = highgui.cvLoadImage (filename)
cutRatios = [lib.PHI]
#cutRatios = [0.75]
ratios = (0.51803398874999995, 0.56803398875, 0.61803398875000004, 0.66666000000000003, 0.71803398875000002, 0.76803398874999995, 0.81803398875, 0.86803398875000004 , 0.91803398874999997, 0.96803398875000002)
settings = Settings(cutRatios)
image = highgui.cvLoadImage (filename)
thickness = 4
settings.setMarginPercentage(0.024)
cuts = (0,1,2,3)
cut = int(sys.argv[2])
winname = sys.argv[3]+".png"
#settings.setThresholds(100,150)
# Set the color for the boxes
#color = lib.COL_BLACK
#color = lib.COL_WHITE
#color = lib.COL_RED
color = lib.COL_GREEN
#color = lib.COL_BLUE
tmp = 0
for r in cuts:
cut = r
print str(r), '---------------------------------'
for i in ratios:
#settings = Settings(cutRatios)
print i
cutd = lib.findMeans(cv.cvGetSize(image), i)[cut]
edgeImage = naiveMethod.getEdgeImage(image, settings)
components = naiveMethod.analyzeCut(image, edgeImage, cutd, settings)
print len(components)
tmp = tmp + len(components)
print tmp
blobImg = blobResult(image, settings, cut)
boxxImg = boundingBoxResult(image, settings, cut, thickness, color)
cutt = lib.findMeans(cv.cvGetSize(image), settings.cutRatios[0])[cut]
# cuttet verdi, dog skal det vi generaliseres lidt
oriantesen = cutt.getPoints()[0].x == cutt.getPoints()[1].x
if oriantesen:
cutPixel = cutt.getPoints()[1].x
else:
cutPixel = cutt.getPoints()[1].y
if oriantesen:
# print 'hej'
cv.cvLine(boxxImg, cv.cvPoint(cutPixel, cutt.getPoints()[0].y), cv.cvPoint(cutPixel, cutt.getPoints()[1].y), lib.COL_RED)
else:
cv.cvLine(boxxImg, cv.cvPoint(cutt.getPoints()[0].x, cutPixel), cv.cvPoint(cutt.getPoints()[1].x, cutPixel), lib.COL_RED)
# Save images
highgui.cvSaveImage('floodfillbilledet.png', blobImg)
highgui.cvSaveImage(winname, boxxImg)
# Show images
compareImages(blobImg, boxxImg, "blob", winname)
