def analyzeImage(original): scaleImage = cv.cvCreateImage(cv.cvSize(int(original.width*scale), int(original.height*scale)), 8, 3) cv.cvResize(original, scaleImage) # Create 1-channel image for the egdes edgeImage = cv.cvCreateImage(cv.cvGetSize(scaleImage), 8, 1) # Retrieve edges edgeDetector.findBWEdges(scaleImage, edgeImage, edgeThreshold1, edgeThreshold2) # Get cuts cuts = lib.findGoldenMeans(cv.cvGetSize(scaleImage)) # Run along allComponents = [] for cut in cuts: cutComponents = analyzeCut(scaleImage, edgeImage, cut) allComponents.append(cutComponents) # Get the collected component_dictionaries for dict in allComponents: lib.drawBoundingBoxes(original, dict, scale) # Draw the margins for cut in cuts: lib.drawMargin(original, cut, margin, scale) #include if super margen is need to drawn #lib.drawMargin(original, cut, superMargin, scale) return (original, allComponents)
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')
# Define cut
cut = lines[0]
print "Test plot and line scanner methods"
points = lineScanner.naiveLineScanner(out, cut)
out = highgui.cvLoadImage (filename)
comp_dict = {}
featureDetector.floodFillLine(image, out, points, cut, lo, up, comp_dict)
# Set margin
margin = 15
# Draw margin
lib.drawMargin(out, cut, margin)
# Set up constraints
constraints = regionSelector.Constraints(cv.cvGetSize(image), cut, margin, 0.002, 0.25)
# Prune components
newComponents = regionSelector.pruneRegions(comp_dict, constraints)
# Draw boxes of selected components
#lib.drawBoundingBoxes(out, newComponents)
# Get grids
grid = grid.gridIt(out, newComponents, 5)
for point in grid:
lib.plot(image, point, 1)
#lib.drawLines(out)
