Пример #1
0
def test_relative_pose():
    print("Testing relative pose")

    d = RelativePoseDataset(10, 0.0, 0.0)

    # running experiments
    twopt_translation = pyopengv.relative_pose_twopt(d.bearing_vectors1,
                                                     d.bearing_vectors2,
                                                     d.rotation)
    fivept_nister_essentials = pyopengv.relative_pose_fivept_nister(
        d.bearing_vectors1, d.bearing_vectors2)
    fivept_kneip_rotations = pyopengv.relative_pose_fivept_kneip(
        d.bearing_vectors1, d.bearing_vectors2)
    sevenpt_essentials = pyopengv.relative_pose_sevenpt(
        d.bearing_vectors1, d.bearing_vectors2)
    eightpt_essential = pyopengv.relative_pose_eightpt(d.bearing_vectors1,
                                                       d.bearing_vectors2)
    t_perturbed, R_perturbed = getPerturbedPose(d.position, d.rotation, 0.01)
    eigensolver_rotation = pyopengv.relative_pose_eigensolver(
        d.bearing_vectors1, d.bearing_vectors2, R_perturbed)
    t_perturbed, R_perturbed = getPerturbedPose(d.position, d.rotation, 0.1)
    nonlinear_transformation = pyopengv.relative_pose_optimize_nonlinear(
        d.bearing_vectors1, d.bearing_vectors2, t_perturbed, R_perturbed)

    assert proportional(d.position, twopt_translation)
    assert matrix_in_list(d.essential, fivept_nister_essentials)
    assert matrix_in_list(d.rotation, fivept_kneip_rotations)
    assert matrix_in_list(d.essential, sevenpt_essentials)
    assert proportional(d.essential, eightpt_essential)
    assert proportional(d.rotation, eigensolver_rotation)
    assert same_transformation(d.position, d.rotation,
                               nonlinear_transformation)

    print("Done testing relative pose")
Пример #2
0
def test_relative_pose():
    print "Testing relative pose"

    d = RelativePoseDataset(10, 0.0, 0.0)

    # running experiments
    twopt_translation = pyopengv.relative_pose_twopt(d.bearing_vectors1, d.bearing_vectors2, d.rotation)
    fivept_nister_essentials = pyopengv.relative_pose_fivept_nister(d.bearing_vectors1, d.bearing_vectors2)
    fivept_kneip_rotations = pyopengv.relative_pose_fivept_kneip(d.bearing_vectors1, d.bearing_vectors2)
    sevenpt_essentials = pyopengv.relative_pose_sevenpt(d.bearing_vectors1, d.bearing_vectors2)
    eightpt_essential = pyopengv.relative_pose_eightpt(d.bearing_vectors1, d.bearing_vectors2)
    t_perturbed, R_perturbed = getPerturbedPose( d.position, d.rotation, 0.01)
    eigensolver_rotation = pyopengv.relative_pose_eigensolver(d.bearing_vectors1, d.bearing_vectors2, R_perturbed)
    t_perturbed, R_perturbed = getPerturbedPose( d.position, d.rotation, 0.1)
    nonlinear_transformation = pyopengv.relative_pose_optimize_nonlinear(d.bearing_vectors1, d.bearing_vectors2, t_perturbed, R_perturbed)

    assert proportional(d.position, twopt_translation)
    assert matrix_in_list(d.essential, fivept_nister_essentials)
    assert matrix_in_list(d.rotation, fivept_kneip_rotations)
    assert matrix_in_list(d.essential, sevenpt_essentials)
    assert proportional(d.essential, eightpt_essential)
    assert proportional(d.rotation, eigensolver_rotation)
    assert same_transformation(d.position, d.rotation, nonlinear_transformation)

    print "Done testing relative pose"
Пример #3
0
    def Pose_test(self, frame1, frame2):
        feature1 = self._config.LoadFeature(frame1)
        feature2 = self._config.LoadFeature(frame2)

        [loc1, des1] = [feature1['location'], feature1['descriptor']]
        [loc2, des2] = [feature2['location'], feature2['descriptor']]

        flann = pyflann.FLANN()
        result, dist = flann.nn(des2,
                                des1,
                                2,
                                algorithm="kmeans",
                                branching=32,
                                iterations=10,
                                checks=200)

        index1 = np.arange(loc1.shape[0])
        compare = (dist[:, 0].astype(np.float32) /
                   dist[:, 1]) < self._config.Get('flann_threshold')

        index1 = index1[compare]
        index2 = result[:, 0][compare]

        loc1 = loc1[index1, :]
        loc2 = loc2[index2, :]

        [F1, M1] = cv2.findFundamentalMat(loc1, loc2, cv2.FM_RANSAC)
        [F2, M2] = cv2.findFundamentalMat(loc2, loc1, cv2.FM_RANSAC)
        M = M1 * M2
        M = np.reshape(M, [-1])
        loc1 = loc1[M == 1, :]
        loc2 = loc2[M == 1, :]

        loc1 = normalized(loc1, 720, 1280)
        loc2 = normalized(loc2, 720, 1280)

        a = np.ones([loc1.shape[0], 3], np.float)
        a[:, :2] = loc1
        b = np.ones([loc1.shape[0], 3], np.float)
        b[:, :2] = loc2
        # print a
        # eight point is better
        M = pyopengv.relative_pose_eightpt(a, b)
        # print M
        i = 20
        print a[i, :]
        print b[i, :]
        print np.dot(np.dot(a[i, :], M), b[i, :].T)
        '''