def multiscale():
d_tot = np.zeros((J.shape[0], J.shape[1], 2, 1))
Jn = J
n_scales = 7
for n in range(n_scales, 2, -1):
sc = 2**(n - 1)
dn, Cn = LK_equation(I,
Jn,
sc * 2.0,
sc * 0.1, [40, 40],
remove_outliers=True)
d_tot += dn
Jn = Cn
lab2.gopimage(d_tot[:, :, :, 0])
plt.show()
(err1, err2) = LK_errors(I, J, Jn)
return d_tot[:, :, :, 0]
from matplotlib import pyplot as plt
import PIL.Image
from single_scale_error import LK_errors
from LK_equation import LK_equation
import lab2
def load_image_grayscale(path):
"Load a grayscale image by path"
return np.asarray(PIL.Image.open(path).convert('L'))
I = load_image_grayscale('SCcar4/SCcar4_00070.bmp')
J = load_image_grayscale('SCcar4/SCcar4_00071.bmp')
d_tot = np.zeros((J.shape[0], J.shape[1], 2, 1))
Jn = J
n_scales = 7
for n in range(n_scales, 2, -1):
sc = 2 ** (n - 1)
dn, Cn = LK_equation(I, Jn, sc * 2.0, sc * 0.1, [40, 40], remove_outliers=True)
d_tot += dn
Jn = Cn
lab2.gopimage(d_tot[:, :, :, 0])
plt.show()
(err1, err2) = LK_errors(I, J, Jn)
return I, J (I, J) = get_cameraman() plt.figure(1) plt.imshow(I) (ds, interpolated_J) = LK_equation(I, J, 15, 1.6, [10, 10]) #plt.imshow(interpolated_J, cmap="gray") #plt.show() plt.figure(2) plt.imshow(ds[:, :, 0, 0]) (err1, err2) = LK_errors(I, J, interpolated_J) plt.figure(3) lab2.gopimage(ds[:, :, :, 0]) plt.show() ''' plt.figure(1) plt.imshow(ds[:, :, 0, 0], cmap="gray") plt.figure(2) plt.imshow(I, cmap="gray") plt.figure(3) plt.imshow(J, cmap="gray") plt.show() '''
height = np.shape(J)[0]
xcoords = np.arange(0, width)
ycoords = np.arange(0, height)
Iinterpol = scipy.interpolate.RectBivariateSpline(ycoords, xcoords, I)
Jinterpol = scipy.interpolate.RectBivariateSpline(ycoords, xcoords, J)
mg = np.array(np.meshgrid(xcoords, ycoords)).reshape(2, -1)
Icoords = np.array(
[mg[0] - d[..., 0].flatten() / 2, mg[1] - d[..., 1].flatten() / 2])
Jcoords = np.array(
[mg[0] + d[..., 0].flatten() / 2, mg[1] + d[..., 1].flatten() / 2])
Id = Jinterpol(Icoords[1], Icoords[0], grid=False).reshape(np.shape(I))
Jd = Iinterpol(Jcoords[1], Jcoords[0], grid=False).reshape(np.shape(J))
lab2.image_grid({"I": I, "J": J}, share_all=True, imshow_opts={'cmap': 'gray'})
#plt.figure("I"), plt.imshow(I, cmap='gray')
#plt.figure("J"), plt.imshow(J, cmap='gray')
#plt.figure("Id"), plt.imshow(Id, cmap='gray')
#plt.figure("Jd"), plt.imshow(Jd, cmap='gray')
plt.figure("Jd"), plt.imshow(np.abs(Jd - Id), cmap='gray')
print("|J-I| = ", np.linalg.norm(J[30:-30, 30:-30] - I[30:-30, 30:-30]))
print("|Jd-Id| = ", np.linalg.norm(Jd[30:-30, 30:-30] - Id[30:-30, 30:-30]))
lab2.gopimage(d)
plt.show()