def main():
cv.NamedWindow("Result", 1)
for name in os.listdir(os.getcwd()):
try:
print 'Start processing ' + str(name)
print '##############################'
animal = cv.LoadImage(name, cv.CV_LOAD_IMAGE_GRAYSCALE)
cv.Threshold(animal, edge, 128 ,255, cv.CV_THRESH_BINARY_INV)
ncas = cv.FindContours(edge, cv.CreateMemStorage(), cv.CV_RETR_LIST, cv.CV_CHAIN_APPROX_NONE,(0,0))
croped, ratio, box = cropRoi(animal, ncas)
cv.Threshold(croped,croped,128,255, cv.CV_THRESH_BINARY)
del ncas
cv.ShowImage("Result", croped)
cv.WaitKey(0)
saveImage(croped, name, savepath, animalpath)
print '##############################'
except IOError, e:
print "Problem opening: ", e
def cropImages(nc, image):
print 'Croping images starts'
images =[]
ratios =[]
boxes=[]
# Checks if the clusterization was performed correctly so that there is a white figure on black beckground
# After this block the image in all the cases should be WHITE on the BLACK background.
check = checkBlack(image, nc)
if check == 'blackonwhite':
cv.Threshold(image,image,128,255, cv.CV_THRESH_BINARY_INV)
elif check == 'whiteonblack':
cv.Threshold(image,image,128,255, cv.CV_THRESH_BINARY)
for i in range(countContours(nc)):
contour = getContour(nc, i)
if len(contour)> minconlength:
croped, ratio, box = cropRoi(image, contour)
ratios.append(ratio)
images.append(croped)
boxes.append(box)
print 'Croping images finished'
return images, ratios, boxes
