def getBlobImage(original, settings, cutNo): """Show the colored blobs in an image at the cut specified by cutNo as int. The cut ratio are placed in the settings and only the first cut in this ratio-list will be analyzed. original should be the image data settings should be of class Settings cutNo as int""" # Get the cut defined by cutNo from the cuts from the first cut ratio in settings cut = lib.findMeans(cv.cvGetSize(original), settings.cutRatios[0])[cutNo] # Get the BW edge image edgeImage = getEdgeImage(original, settings) # Find the margin margin = marginCalculator.getPixels(original, cut, settings.marginPercentage) # Clever hack for putting the cut in an array tmp = [] tmp.append(cut) # Get results (blobImage, components) = analyzeCut(original, edgeImage, cut, settings, True) lib.drawLines(blobImage, blobImage, tmp) lib.drawMargin(blobImage, cut, margin) # Return result, what a surprise return blobImage
def getBoundingBoxImage(original, settings, cutNo, thickness=1, color=None): """Same as above but will paint the bounding boxes original should be the image data settings should be of class Settings cutNo as int color as CV_RGB""" # Get the cut defined by cutNo from the cuts from the first cut ratio in settings cut = lib.findMeans(cv.cvGetSize(original), settings.cutRatios[0])[cutNo] # Get the BW edge image edgeImage = getEdgeImage(original, settings) # Find the margin margin = marginCalculator.getPixels(original, cut, settings.marginPercentage) tmp = [] tmp.append(cut) components = analyzeCut(original, edgeImage, cut, settings) lib.drawMargin(original, cut, margin) # Draw the components lib.drawBoundingBoxes(original, components, thickness, color) return original
def analyzeImage(original, settings):
"""Runs the analysis on all cuts on an image"""
# Get the BW edge image
edgeImage = getEdgeImage(original, settings)
# Get cuts and place then in a dictionary by cut ratio
# XXX: Notice the ugly string conversion because python has an issue when
# converting the ratio to a dictionary index
cuts = {}
for ratio in settings.cutRatios:
cuts[str(ratio)] = lib.findMeans(cv.cvGetSize(original), ratio)
# New dictionary for holding the resulting components
# Hold on, now we're putting the result (which is a dictionary)
# inside a new dict (cutDict). This holds the result for the four cuts
# for a given ratio. We now put this dict inside the comps-dictionary
# which then can be used for lookup by the cut-ratio
comps = {}
for ratio in cuts:
cutDict = {}
for cutNo in range(len(cuts[ratio])):
cutComponents = analyzeCut(original, edgeImage, cuts[ratio][cutNo], settings)
cutDict[cutNo] = cutComponents
comps[ratio] = cutDict
# Clean up
cv.cvReleaseImage(edgeImage)
# This is a dictionary in a dictionary in a dictionary
return comps
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)
print "DO NOT EXPECT THE RUNNING TIME OF THIS TEST TO BE REPRESENTATIVE!"
print ""
print "THRESHOLDS AND EVERYTHING ELSE ARE HARDCODED!"
cutRatios = [0.6667, lib.PHI, 0.6]
settings = Settings(cutRatios)
# Run the analysis with the above settings
comps = naiveMethod.analyzeImage(image, settings)
# This is just for drawing the results
# The below methods can probably be combined but don't bother
# {{{
# Get and draw the cuts
cuts = {}
for ratio in settings.cutRatios:
cuts[str(ratio)] = lib.findMeans(cv.cvGetSize(image), ratio)
for ratio in cuts:
lib.drawLines(image, None, cuts[ratio], lib.getRandomColor())
# Get and draw the components
for ratio in comps:
for cut in comps[ratio]:
lib.drawBoundingBoxes(image, comps[ratio][cut])
# }}}
winname = "Failure"
highgui.cvNamedWindow (winname, highgui.CV_WINDOW_AUTOSIZE)
while True:
highgui.cvShowImage (winname, image)
c = highgui.cvWaitKey(0)
if c == 'q':
print "Exiting ..."
print ""
sys.exit(0)
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)
