def patch_match(a, b, angles=360, Rs=None, plot_corr=False):
"""Align two patches, using the log polar transform.
Parameters
----------
a : ndarray of uint8
Reference image.
b : ndarray of uint8
Target image.
angles : int
Number of angles to use in log-polar transform.
Rs : int
Number of radial samples used in the log-polar transform.
plot_corr : bool, optional
Whether to plot the phase correlation coefficients.
Returns
-------
c : float
Peak correlation value.
theta : float
Estimated rotation angle from `a` to `b`.
scale : float
Estimated scaling from `a` to `b`.
"""
from image import phase_corr
import supreme.transform as tr
angles = np.linspace(0, np.pi * 2, angles)
if Rs is None:
Rs = max(a.shape[:2])
A, angles, log_base = tr.logpolar(a, angles=angles, Rs=Rs, extra_info=True)
B = tr.logpolar(b, angles=angles, Rs=Rs)
cv = phase_corr(B, A)
m, n = np.unravel_index(np.argmax(cv), cv.shape)
if n > Rs/2:
n = n - Rs # correlation matched, but from the other side
if plot_corr:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
fig = plt.figure()
cv_cut = cv[max(0, m - 30):min(cv.shape[1], m + 30),
max(0, n - 30):min(cv.shape[0], n + 30)]
coords = sr.geometry.Grid(*cv_cut.shape)
ax3d = axes3d.Axes3D(fig)
ax3d.plot_wireframe(coords['cols'], coords['rows'], cv_cut)
ax3d.set_title('Phase correlation around peak\n$\\log(100 + x)$')
plt.show()
return cv[m, n], angles[m], np.exp(n * log_base)
def test_logpolar(self, level=1):
x = np.zeros((3, 3))
z = transform.logpolar(x)
assert_equal(z.shape, (12, 3))
x = np.zeros((3, 3, 3))
z = transform.logpolar(x)
assert_equal(z.shape, (12, 3, 3))
x = np.zeros((3, 3, 4))
z = transform.logpolar(x)
assert_equal(z.shape, (12, 3, 4))
z = transform.logpolar(x, angles=np.linspace(0, 2 * np.pi, 400))
assert_equal(z.shape, (400, 3, 4))
def test_logpolar(self, level=1):
x = np.zeros((3, 3))
z = transform.logpolar(x)
assert_equal(z.shape, (12, 3))
x = np.zeros((3, 3, 3))
z = transform.logpolar(x)
assert_equal(z.shape, (12, 3, 3))
x = np.zeros((3, 3, 4))
z = transform.logpolar(x)
assert_equal(z.shape, (12, 3, 4))
z = transform.logpolar(x, angles=np.linspace(0, 2*np.pi, 400))
assert_equal(z.shape, (400, 3, 4))
def test_logpolar_on_zeros(self):
x = np.zeros((3))
transform.logpolar(x)
def test_logpolar_on_zeros(self):
x = np.zeros((3))
transform.logpolar(x)
