def q4_1(I1, I2):
    
    if os.path.exists(q4_1_file):
      with np.load(q4_1_file) as data:
        F = data['F']
        assert F.shape == (3, 3), f"F shape is {F.shape} instead of (3, 3)"
        
        pts1 = data['pts1']
        pts2 = data['pts2']
        assert pts1.shape == pts2.shape, \
            f"pt1s shape {pts1.shape} != pts2 size {pts2.shape}"
            
        print(f"F:\n{F} matched {len(pts1)} points")
    else:
      
      if os.path.exists(q2_1_file):
          with np.load(q2_1_file, allow_pickle=True) as data:
              F = data['F']
      else:
          with np.load("../data/some_corresp.npz") as data:
              pts1 = data['pts1']
              pts2 = data['pts2']

              M = max(I1.shape[0], I1.shape[1])
              F = eightpoint(pts1=pts1, pts2=pts2, M=M)
              np.savez(q2_1_file, F=F, M=M)

          # Epipolar matching
          I1 = I1[::, ::, ::-1]
          I2 = I2[::, ::, ::-1]
          epipolarMatchGUI(I1=I1, I2=I2, F=F)
示例#2
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def testEpipolarCorrespondence():
    im1 = cv2.imread('../data/im1.png')
    im2 = cv2.imread('../data/im2.png')
    pts = np.load('../data/some_corresp.npz')
    pts1 = pts["pts1"]
    pts2 = pts["pts2"]
    M = max((im1.shape[0], im1.shape[1]))
    F = eightpoint(pts1, pts2, M)
    from helper import epipolarMatchGUI
    epipolarMatchGUI(im1, im2, F)
    np.savez('q4_1.npz', F=F, pts1=pts1, pts2=pts2)
示例#3
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def runEpipolarCorrespondence(im1, im2, pts1, pts2, M):
    F8 = eightpoint(pts1, pts2, M)

    try:
        p1, p2 = hp.epipolarMatchGUI(im1, im2, F8)
        np.savez('../results/files/q4_1.npz', F=F8, pts1=p1, pts2=p2)
    except Exception:
        pass
for f7 in F7:
    assert f7.shape == (3, 3), 'seven returns list of 3x3 matrix'

#print(F7.shape)
print('F7')
print(F7)
#helper.displayEpipolarF(im1, im2, F7[0])

# 3.1
print('E')
print(sub.essentialMatrix(F8, K1, K2))

C1 = np.concatenate([np.random.rand(3, 3), np.ones([3, 1])], axis=1)
C2 = np.concatenate([np.random.rand(3, 3), np.ones([3, 1])], axis=1)

P, err = sub.triangulate(C1, data['pts1'], C2, data['pts2'])
print(err)
assert P.shape == (N, 3), 'triangulate returns Nx3 matrix P'
assert np.isscalar(err), 'triangulate returns scalar err'

# 4.1
x2, y2 = sub.epipolarCorrespondence(im1, im2, F8, data['pts1'][0, 0],
                                    data['pts1'][0, 1])
assert np.isscalar(x2) & np.isscalar(
    y2), 'epipolarCorrespondence returns x & y coordinates'
np.savez('../results/q4_1.npz', F=F8, pts1=data['pts1'], pts2=data['pts2'])
helper.epipolarMatchGUI(im1, im2, F8)

print('Format check passed.')
示例#5
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from helper import epipolarMatchGUI
'''
Q4.1: 3D visualization of the temple images.
    Input:  im1, the first image
            im2, the second image
            F, the fundamental matrix
            x1, x-coordinates of a pixel on im1
            y1, y-coordinates of a pixel on im1
    Output: x2, x-coordinates of the pixel on im2
            y2, y-coordinates of the pixel on im2
'''

if __name__ == '__main__':
    data = np.load('../data/some_corresp.npz')
    im1 = plt.imread('../data/im1.png')
    im2 = plt.imread('../data/im2.png')
    pts1 = data['pts1']
    pts2 = data['pts2']

    N = data['pts1'].shape[0]  # N=110
    M = 640
    P1 = pts1
    P2 = np.zeros(P1.shape)
    F = sub.eightpoint(pts1, pts2, M)
    for i in range(P1.shape[0]):
        [P2[i, 0],
         P2[i, 1]] = sub.epipolarCorrespondence(im1, im2, F, P1[i, 0], P1[i,
                                                                          1])
    # np.savez('../jingruwu/data/q4_1.npz',P1=P1,P2=P2)
    epipolarMatchGUI(im1, im2, F)
data = np.load('../data/templeCoords.npz')
im1 = plt.imread('../data/im1.png')
im2 = plt.imread('../data/im2.png')
x1 = data['x1']
y1 = data['y1']

num, temp = x1.shape
pts1 = np.hstack((x1, y1))
pts2 = np.zeros((num, 2))

for i in range(num):
    x2, y2 = epipolarCorrespondence(im1, im2, F, x1[i, 0], y1[i, 0])
    pts2[i, 0] = x2
    pts2[i, 1] = y2
   
p1,p2=helper.epipolarMatchGUI(im1, im2, F)

P, err = triangulate(C1, pts1, C2, pts2)

fig = plt.figure()
ax = Axes3D(fig)
ax.scatter(P[:, 0], P[:, 1], P[:, 2])
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')

plt.show()

if (os.path.isfile('q4_2.npz') == False):
    np.savez('q4_2.npz', F=F, M1=M1, M2=M2, C1=C1, C2=C2)
        
示例#7
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# 2.2
pts1 = np.array([[256,270],[162,152],[199,127],[147,131],[381,236],[193,290],[157,231]])
pts2 = np.array([[257,266],[161,151],[197,135],[146,133],[380,215],[194,284],[157,211]])
Farray = sub.sevenpoint(pts1, pts2, M)
helper.displayEpipolarF(im1, im2, Farray[1])
np.savez('q2_2.npz', F=Farray[1], M=M, pts1=pts1, pts2=pts2)

# 3.1
intrinsic = np.load('../data/intrinsics.npz')
K1, K2 = intrinsic['K1'], intrinsic['K2']
E = sub.essentialMatrix(F8, K1, K2)
print(E)

# 4.1
selected_pts1, selected_pts2 = helper.epipolarMatchGUI(im1, im2, F8)
#np.savez('q4_1.npz', F=F8, pts1=selected_pts1, pts2=selected_pts2)

# 5.1
noise_data = np.load('../data/some_corresp_noisy.npz')
F, inliers = sub.ransacF(noise_data['pts1'], noise_data['pts2'], M)
np.savez('tmpnew.npz', F=F, inliers=inliers)
# helper.displayEpipolarF(im1, im2, F)
# F_compare = sub.eightpoint(noise_data['pts1'], noise_data['pts2'], M)
# helper.displayEpipolarF(im1, im2, F_compare)

# 5.2
r = np.ones([3, 1])
R = sub.rodrigues(r)
assert R.shape == (3, 3), 'rodrigues returns 3x3 matrix'
示例#8
0
    x1 = data['x1']
    y1 = data['y1']

    F = eightpoint(pts1, pts2, M)

    np.savez_compressed('./q2_1.npz', F=F, M=M)

    helper.displayEpipolarF(I1, I2, F)

    bestF, Farray_best, points1, points2 = BestFSevenPoints(pts1, pts2, M)

    np.savez_compressed('./q2_2.npz', F=bestF, M=M, pts1=points1, pts2=points2)

    helper.displayEpipolarF(I1, I2, bestF)

    E = essentialMatrix(F, K1, K2)

    Ms = helper.camera2(E)

    M2, M1, C2, C1, Points = findM2_function(K1, K2, Ms, pts1, pts2)

    np.savez_compressed('./q3_3.npz', M2=M2, C2=C2, P=Points)

    helper.epipolarMatchGUI(I1, I2, F)

    np.savez_compressed('./q4_1.npz', F=F, pts1=pts1, pts2=pts2)

    visualize.Visualize(I1, I2, x1, y1, C1, C2, F)

    np.savez_compressed('./q4_2.npz', F=F, C1=C1, C2=C2, M2=M2, M1=M1)
import helper as hp

data = np.load('../data/some_corresp.npz')
im1 = plt.imread('../data/im1.png')
im2 = plt.imread('../data/im2.png')
K_matrices = np.load('../data/intrinsics.npz')

N = data['pts1'].shape[0]
M = 640

K1 = K_matrices['K1']
K2 = K_matrices['K2']

F = sub.eightpoint(data['pts1'], data['pts2'], M)
E = sub.essentialMatrix(F, K1, K2)
M1 = np.concatenate([np.eye(3), np.zeros([3, 1])], axis=1)
C1 = np.dot(K1, M1)
M2s = hp.camera2(E)
'''
for i in range(M2s.shape[-1]):
    C2 = np.dot(K2,M2s[:,:,i])
    pts_3D, error = sub.triangulate(C1, data['pts1'], C2, data['pts2'])
    print(error)
'''
M2 = M2s[:, :, 2]
C2 = np.dot(K2, M2)
pts_3D, error = sub.triangulate(C1, data['pts1'], C2, data['pts2'])
#np.savez('../results/q3_3.npz',M2=M2,C2=C2,P=pts_3D)

hp.epipolarMatchGUI(im1, im2, F)