def rps(img):
assert img.ndim == 2
radii2 = (np.arange(img.shape[0]).reshape((img.shape[0], 1)) ** 2) + (np.arange(img.shape[1])** 2)
radii2 = np.minimum(radii2, np.flipud(radii2))
radii2 = np.minimum(radii2, np.fliplr(radii2))
maxwidth = min(img.shape[0], img.shape[1]) / 8.0 # truncate early to avoid edge effects
if img.ptp() > 0:
img = img / np.median(abs(img - img.mean())) # intensity invariant
mag = abs(fft2(img - np.mean(img)))
power = mag**2
radii = np.floor(np.sqrt(radii2)).astype(np.int) + 1
labels = np.arange(2, np.floor(maxwidth)).astype(np.int).tolist() # skip DC component
if len(labels) > 0:
magsum = nd_sum(mag, radii, labels)
powersum = nd_sum(power, radii, labels)
return np.array(labels), np.array(magsum), np.array(powersum)
return [2], [0], [0]
def rps(img):
assert img.ndim == 2
radii2 = (np.arange(img.shape[0]).reshape((img.shape[0], 1)) ** 2) + (np.arange(img.shape[1])** 2)
radii2 = np.minimum(radii2, np.flipud(radii2))
radii2 = np.minimum(radii2, np.fliplr(radii2))
maxwidth = min(img.shape[0], img.shape[1]) / 8.0 # truncate early to avoid edge effects
if img.ptp() > 0:
img = img / np.median(abs(img - img.mean())) # intensity invariant
mag = abs(fft2(img - np.mean(img)))
power = mag**2
radii = np.floor(np.sqrt(radii2)).astype(np.int) + 1
labels = np.arange(2, np.floor(maxwidth)).astype(np.int).tolist() # skip DC component
if len(labels) > 0:
magsum = nd_sum(mag, radii, labels)
powersum = nd_sum(power, radii, labels)
return np.array(labels), np.array(magsum), np.array(powersum)
return [2], [0], [0]