Beispiel #1
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 def test_svr_registration(self):
     res = l2dist_regs.registration_svr(self._source, self._target)
     res_rot = trans.identity_matrix()
     res_rot[:3, :3] = res.rot
     ref_rot = trans.identity_matrix()
     ref_rot[:3, :3] = self._tf.rot
     self.assertTrue(np.allclose(trans.euler_from_matrix(res_rot),
                                 trans.euler_from_matrix(ref_rot), atol=1.0e-1, rtol=1.0e-1))
     self.assertTrue(np.allclose(res.t, self._tf.t, atol=1.0e-2, rtol=1.0e-3))
Beispiel #2
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    def svr_pcd(self):
        output_every_tf = 'svr_every_tf.txt'
        output_seq_tf = 'svr_seq_tf.txt'
        with open(output_every_tf, 'a+') as f:
            f.write(original_tf_09)
        f.close()
        with open(output_seq_tf, 'a+') as f:
            f.write(original_tf_09)
        f.close()
        for i in range(self.number - 1):
            print(i)
            source_filename = '/media/chenxin/我不是硬盘/kitti_dataset/sequences/09/pcd/' + str(
                i + 1) + '.pcd'
            target_filename = '/media/chenxin/我不是硬盘/kitti_dataset/sequences/09/pcd/' + str(
                i) + '.pcd'
            source = o3.io.read_point_cloud(source_filename)
            source = source.voxel_down_sample(voxel_size=VOXEL)
            target = o3.io.read_point_cloud(target_filename)
            target = target.voxel_down_sample(voxel_size=VOXEL)

            np_source = np.asarray(source.points)
            #s_points_after_tf_basis = self.mul_tf_basis(np_source)
            s_points_after_tf_basis = self.calib_velo2cam(np_source)
            source.points = o3.utility.Vector3dVector(s_points_after_tf_basis)

            np_target = np.asarray(target.points)
            #t_points_after_tf_basis = self.mul_tf_basis(np_target)
            t_points_after_tf_basis = self.calib_velo2cam(np_target)
            target.points = o3.utility.Vector3dVector(t_points_after_tf_basis)

            start = timer()
            tf_param = l2dist_regs.registration_svr(source, target)
            end = timer()
            self.time.append(end - start)
            curr_tf = self.collect_tf(tf_param)
            seq_tf = np.dot(curr_tf, self.seq_tf)
            self.seq_tf = seq_tf
            self.output(output_every_tf, curr_tf)
            self.output(output_seq_tf, seq_tf)
waymopair = WaymoLIDARPair(
    max_frames=150,
    as_pc=True,
    voxel_size=0.5,
    filename=
    '/home/mlab-dhruv/Desktop/pointclouds/waymodata/segment-10206293520369375008_2796_800_2816_800_with_camera_labels.tfrecord'
)

done = False
all_trans = []
vis = WaymoLIDARVisCallback()
idx = 0
while True:
    prev_np, curr_np, prev_pc, curr_pc, done = waymopair.next_pair()
    if done:
        break

    #1: Compute L2 Gaussian Registration & Transform chain
    tf_param = l2dist_regs.registration_svr(prev_pc, curr_pc)
    all_trans.append(copy.deepcopy(tf_param.inverse()))
    if idx == 0:
        result = copy.deepcopy(curr_pc)
    else:
        result = convert_np_to_pc(
            np.linspace(-0.03, 0.01, num=20 * 3).reshape(-1, 3))
        result.colors = o3.utility.Vector3dVector(
            np.ones((20 * 3)).reshape(-1, 3) * np.array([1, 0, 0]))
    # idx+=1
    for tf in reversed(all_trans):
        result.points = tf.transform(result.points)
    vis(result, addpc=True)
                    [np.sin(th), np.cos(th), 0.0, 0.0], [0.0, 0.0, 1.0, 0.0],
                    [0.0, 0.0, 0.0, 1.0]])

all_trans = []

#1: a)Load Source & Target Pointclouds b) Transform Target c) Downsample for speed
source = o3.read_point_cloud(filepath)
target = copy.deepcopy(source)
target.transform(TRANSLATE_02x)
target.transform(ROT_30z)
source = o3.voxel_down_sample(source, voxel_size=0.003)
target = o3.voxel_down_sample(target, voxel_size=0.003)

#2: Compute L2 Gaussian Registration
# cbs = [callbacks.Open3dVisualizerCallback(source, target)]
tf_param = l2dist_regs.registration_svr(source, target)
result = copy.deepcopy(source)
# result.points = tf_param.transform(result.points)

for i in range(4):
    result.transform(TRANSLATE_005x)
result.transform(ROT_15z)
result.transform(ROT_15z)

print(tf_param.rot)
print(tf_param.t)

#3: draw result
source.paint_uniform_color([1, 0, 0])
target.paint_uniform_color([0, 1, 0])
result.paint_uniform_color([0, 0, 1])
Beispiel #5
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import numpy as np
import transforms3d as t3d
from probreg import l2dist_regs
from probreg import callbacks
import utils

source, target = utils.prepare_source_and_target_rigid_3d('bunny.pcd',
                                                          n_random=0)

cbs = [callbacks.Open3dVisualizerCallback(source, target)]
tf_param = l2dist_regs.registration_svr(source, target, callbacks=cbs)

print("result: ", np.rad2deg(t3d.euler.mat2euler(tf_param.rot)),
      tf_param.scale, tf_param.t)
Beispiel #6
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 def register(self, pcd1, pcd2):
     reg_svr = l2dist_regs.registration_svr(pcd1, pcd2)
     return reg_svr.transformation
Beispiel #7
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 def test_svr_registration(self):
     res = l2dist_regs.registration_svr(self._source, self._target)
     self.assertTrue(np.allclose(t3d.euler.mat2euler(res.rot),
                                 t3d.euler.mat2euler(self._tf.rot), atol=1.0e-1, rtol=1.0e-1))
     self.assertTrue(np.allclose(res.t, self._tf.t, atol=1.0e-2, rtol=1.0e-3))
def register_svr(source, target):
    tf_param = l2dist_regs.registration_svr(source, target)
    result = copy.deepcopy(source)
    result.points = tf_param.transform(result.points)
    return result, tf_param
Beispiel #9
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    o3.pipelines.registration.ICPConvergenceCriteria(
        max_iteration=max_iteration))
end = timer()
print('ICP(Open3D): ', end - start)

start = timer()
res = cpd.registration_cpd(source,
                           target,
                           maxiter=max_iteration,
                           tol=threshold)
end = timer()
print('CPD: ', end - start)

start = timer()
res = l2dist_regs.registration_svr(source,
                                   target,
                                   opt_maxiter=max_iteration,
                                   opt_tol=threshold)
end = timer()
print('SVR: ', end - start)

start = timer()
res = gmmtree.registration_gmmtree(source,
                                   target,
                                   maxiter=max_iteration,
                                   tol=threshold)
end = timer()
print('GMMTree: ', end - start)

start = timer()
res = filterreg.registration_filterreg(source,
                                       target,