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@@ -1,12 +1,12 @@
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from GrayscaleImage import GrayscaleImage
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from scipy.ndimage import convolve1d
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-from pylab import ceil, zeros, pi, e, exp, sqrt, array
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+from pylab import ceil, zeros, pi, exp, sqrt, array
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class GaussianFilter:
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def __init__(self, scale):
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self.scale = scale
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-
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+
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def gaussian(self, x):
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'''Return the value of a 1D Gaussian function for a given x and scale'''
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return exp(-(x ** 2 / (2 * self.scale ** 2))) / (sqrt(2 * pi) * self.scale)
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@@ -15,12 +15,12 @@ class GaussianFilter:
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'''Sample a one-dimensional Gaussian function of scale s'''
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radius = int(ceil(3 * self.scale))
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size = 2 * radius + 1
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-
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+
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result = zeros(size)
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- # Sample the Gaussian function
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+ # Sample the Gaussian function
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result = array([self.gaussian(x - radius) for x in xrange(size)])
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# The sum of all kernel values is equal to one
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- result /= result.sum()
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+ result /= result.sum()
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return result
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@@ -29,15 +29,15 @@ class GaussianFilter:
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kernel = self.get_1d_gaussian_kernel()
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image = convolve1d(image.data, kernel, axis=0, mode='nearest')
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return GrayscaleImage(None, convolve1d(image, kernel, axis=1, mode='nearest'))
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-
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+
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def filter(self, image):
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kernel = self.get_1d_gaussian_kernel()
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image.data = convolve1d(image.data, kernel, axis=0, mode='nearest')
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image.data = convolve1d(image.data, kernel, axis=1, mode='nearest')
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-
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+
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def get_scale(self):
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return self.scale
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-
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+
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def set_scale(self, scale):
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self.scale = float(scale)
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