def floodFillBetweenPoints(out, lo, up, line, component_dict):
"""Floofill the image at point x,y whit are lower and upper thres hold namt lo and up
Start and stop point is the point that the def runs from to"""
#Sets the flag
flags = 4 + (255 << 8) + cv.CV_FLOODFILL_FIXED_RANGE
# Set the region to None, as we haven't found any yet
comp = None
(p1, p2) = line.getPoints()
if p1.x == p2.x:
# Initialize the seed and set deltas for increasing the seed
dx = 0
dy = 1
min = p1.y
max = p2.y - 1
elif p1.y == p2.y:
# Initialize the seed and set deltas for increasing the seed
dx = 1
dy = 0
min = p1.x
max = p2.x - 1
else:
raise lib.OrientationException("Unknown orientation")
seed = p1
# Get a new color that is not in the component dictionary
color = lib.getRandomColor()
inDict = colorString(color) in component_dict
while inDict:
color = lib.getRandomColor(color)
inDict = colorString(color) in component_dict
#Color between start_point+1 and point-1
#Tmp is the tims we find new color that lie in component_dict.
#This giv are indekeder that telle os have mots time we save whit the check
for i in range(min, max):
seed = cv.cvPoint(seed.x + dx, seed.y + dy)
#Check if the color of the next pixel equals color
if not (lib.isSameColor(out[seed.y][seed.x], color)):
#Check if the color of the next pixel are in component_dict
if not (colorString(out[seed.y][seed.x]) in component_dict):
comp = cv.CvConnectedComp()
cv.cvFloodFill(out, seed, color, cv.CV_RGB(lo,lo,lo), cv.CV_RGB(up,up,up),comp)# ,flags, None);
# Color the pixel again to make sure we return the entire region
cv.cvFloodFill(out, seed, color, cv.CV_RGB(lo,lo,lo), cv.CV_RGB(up,up,up),comp)# ,flags, None);
# Put the results in the component dictionary if we have found a region
if not (comp is None):
component_dict[colorString(color)] = (color, comp)
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)