def calc_rms(im1, im2):
# http://effbot.org/zone/pil-comparing-images.htm#rms
# calculate the root-mean-square difference between two images
source, compare = utility.open_image(im1, im2)
"Calculate the root-mean-square difference between two images"
diff = ImageChops.difference(source, compare)
h = diff.histogram()
sq = (value * (idx**2) for idx, value in enumerate(h))
sum_of_squares = sum(sq)
rms = math.sqrt(sum_of_squares / float(source.size[0] * source.size[1]))
return round(rms, 0)
def ncc(im1, im2):
n = 33856
image, template = utility.open_image(im1, im2)
np_image = numpy.asarray(image.getdata())
np_template = numpy.asarray(template.getdata())
image_mean = np_image.mean()
image_std = np_image.std()
template_mean = np_template.mean()
template_std = np_template.std()
s = sum( ( image_mean / image_std ) * ( template_mean / template_std) )
x = 1 / n * s
return x
def op_transform(im1, im2, operation):
source, compare = utility.open_image(im1, im2)
if operation == 'xor':
x = algorithm.xor(source, compare)
return x
elif operation == 'union':
x = ImageChops.multiply(source, compare)
return x
elif operation == 'subtract':
x = algorithm.subtract(source, compare)
return x
elif operation == 'intersect':
x = algorithm.intersect(source, compare)
return x
elif operation == 'modified-subtract-horizontal':
x = algorithm.modified_subtract(source, compare, 'horizontal')
return x
elif operation == 'modified-subtract-vertical':
x = algorithm.modified_subtract(source, compare, 'vertical')
return x
def image_difference(im1, im2):
source, compare = utility.open_image(im1, im2)
return ImageChops.difference(source, compare).getbbox()
