def __init__(self, verbose=False): self.solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) self.solver = g2o.OptimizationAlgorithmLevenberg(self.solver) self.optimizer = g2o.SparseOptimizer() self.optimizer.set_verbose(verbose) self.optimizer.set_algorithm(self.solver)
def bundle_adjustment(ps_1, ps_2, r_mat, t_vec): optimizer = g2o.SparseOptimizer() solver = g2o.BlockSolverSim3(g2o.LinearSolverCSparseSim3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer.set_algorithm(solver) pose = g2o.VertexSE3Expmap() pose.set_estimate(g2o.SE3Quat(np.identity(3), np.zeros((3,)))) pose.set_id(0) optimizer.add_vertex(pose) index = 1 for p1, p2 in zip(ps_1, ps_2): edge = g2o.EdgeStereoSE3ProjectXYZOnlyPose() edge.cam_project(p2) edge.set_id(index) edge.set_vertex(0, pose) edge.set_measurement(p1) edge.set_information(np.identity(3)) optimizer.add_edge(edge) index += 1 optimizer.initialize_optimization() optimizer.set_verbose(True) optimizer.optimize(100) print('T = \n', pose.estimate().matrix())
def optimize(self): # create g2o optimizer opt = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) opt.set_algorithm(solver) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) # add frames to graph for f in self.frames: pose = f.pose #pose = np.linalg.inv(pose) sbacam = g2o.SBACam(g2o.SE3Quat(pose[0:3, 0:3], pose[0:3, 3])) sbacam.set_cam(f.K[0][0], f.K[1][1], f.K[0][2], f.K[1][2], 1.0) v_se3 = g2o.VertexCam() v_se3.set_id(f.id) v_se3.set_estimate(sbacam) v_se3.set_fixed(f.id <= 1) opt.add_vertex(v_se3) # add points to frames PT_ID_OFFSET = 0x10000 for p in self.points: pt = g2o.VertexSBAPointXYZ() pt.set_id(p.id + PT_ID_OFFSET) pt.set_estimate(p.pt[0:3]) pt.set_marginalized(True) pt.set_fixed(False) opt.add_vertex(pt) for f in p.frames: edge = g2o.EdgeProjectP2MC() edge.set_vertex(0, pt) edge.set_vertex(1, opt.vertex(f.id)) uv = f.kpus[f.pts.index(p)] edge.set_measurement(uv) edge.set_information(np.eye(2)) edge.set_robust_kernel(robust_kernel) opt.add_edge(edge) opt.set_verbose(True) opt.initialize_optimization() opt.optimize(50) # put frames back for f in self.frames: est = opt.vertex(f.id).estimate() R = est.rotation().matrix() t = est.translation() f.pose = poseRt(R, t) # put points back for p in self.points: est = opt.vertex(p.id + PT_ID_OFFSET).estimate() p.pt = np.array(est)
def __init__(self): self.optimizer = g2o.SparseOptimizer() # self.solver = g2o.BlockSolverX(g2o.LinearSolverDenseX()) # self.solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) self.solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) self.algorithm = g2o.OptimizationAlgorithmLevenberg(self.solver) self.optimizer.set_algorithm(self.algorithm) self.already_initialized = False self.last_lost = 0 self.lock = ControlableLock(True)
def optimize(self): # init g2o solver opt = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) opt.set_algorithm(solver) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) # add frames to graph for frame in self.frames: pose = frame.pose sbacam = g2o.SBACam( g2o.SE3Quat(frame.pose[0:3, 0:3], frame.pose[0:3, 3])) # sbacam.set_cam(frame.K[0][0], frame.K[1][1], frame.K[2][0], frame.K[2][1], 1.0) sbacam.set_cam(1.0, 1.0, 0.0, 0.0, 1.0) v_se3 = g2o.VertexCam() v_se3.set_id(frame.id) v_se3.set_estimate(sbacam) v_se3.set_fixed(frame.id == 0) opt.add_vertex(v_se3) # add points to frames PT_ID_OFFSET = 0x10000 for point in self.points: pt = g2o.VertexSBAPointXYZ() pt.set_id(point.id + PT_ID_OFFSET) pt.set_estimate(point.pt[0:3]) pt.set_marginalized(True) pt.set_fixed(False) opt.add_vertex(pt) for frame in point.frames: edge = g2o.EdgeProjectP2MC() edge.set_vertex(0, pt) edge.set_vertex(1, opt.vertex(frame.id)) uv = frame.kps[frame.pts.index(point)] edge.set_measurement(uv) edge.set_information(np.eye(2)) edge.set_robust_kernel(robust_kernel) opt.add_edge(edge) # opt.set_verbose(True) opt.initialize_optimization() opt.optimize(20) # add pose back to frame for frame in self.frames: est = opt.vertex(frame.id).estimate() R = est.rotation().matrix() t = est.translation() frame.pose = poseRt(R, t)
def __init__(self, max_iterations=100, verbose=False, online=False): solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) self.optimizer = g2o.SparseOptimizer() self.optimizer.set_verbose(True) self.optimizer.set_algorithm(solver) self.current_pose = None self.max_iterations = max_iterations self.verbose = verbose self.online = online self.clear()
def oprimizer(self): ## Init optimizer optimizer = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer.set_algorithm(solver) ## add frames to graph for f in self.frames: v_se3 = g2o.VertexSE3() v_se3.set_id(f.id) v_se3.set_estimate(f.pose) v_se3.set_fixed(f.id == 0) optimizer.add_vertex(v_se3)
def prepare_optimiser(self, verbose): # create g2o optimizer self.opt = g2o.SparseOptimizer() self.solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) self.solver = g2o.OptimizationAlgorithmLevenberg(self.solver) self.opt.set_algorithm(self.solver) # add normalized camera cam = g2o.CameraParameters(1.0, (0.0, 0.0), 0) cam.set_id(0) self.opt.add_parameter(cam) self.robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) self.graph_frames, self.graph_points = {}, {} if verbose: self.opt.set_verbose(True)
def main(): solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer = g2o.SparseOptimizer() optimizer.set_verbose(True) optimizer.set_algorithm(solver) optimizer.load(args.input) print('num vertices:{}'.format(len(optimizer.vertices()))) print('num edges:{}'.format(len(optimizer.edges()))) for i in range(len(optimizer.vertices())): vp_se3 = optimizer.vertex(i) print(dir(vp_se3)) print(vp_se3.id) break
def main(): #solver = g2o.BlockSolverX(g2o.LinearSolverCholmodX()) solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer = g2o.SparseOptimizer() optimizer.set_verbose(True) optimizer.set_algorithm(solver) optimizer.load(args.input) print('num vertices:', len(optimizer.vertices())) print('num edges:', len(optimizer.edges()), end='\n\n') optimizer.initialize_optimization() optimizer.optimize(args.max_iterations) if len(args.output) > 0: optimizer.save(args.output)
def optimize(self, max_iters): opt = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) opt.set_algorithm(solver) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) # adding frames to graph for f in self.frames: sbacam = g2o.SBACam(g2o.SE3Quat(f.pose[0:3, 0:3], f.pose[0:3, 3])) sbacam.set_cam(f.T[0][0], f.T[1][1], f.T[2][0], f.T[2][1], 1.0) v_se3 = g2o.VertexCam() v_se3.set_id(f.id) v_se3.set_estimate(sbacam) v_se3.set_fixed(f.id == 0) opt.add_vertex(v_se3) # add points to graph for p in self.points: pt = g2o.VertexSBAPointXYZ() pt.set_id(p.id + 0x10000) pt.set_estimate(p.location[0:3]) pt.set_marginalized(True) pt.set_fixed(False) opt.add_vertex(pt) # add connections between frames that contain a point in the graph for f in p.frames: edge = g2o.EdgeProjectP2MC() edge.set_vertex(0, pt) edge.set_vertex(1, opt.vertex(f.id)) uv = f.kpts[f.pts.index(p)] edge.set_measurement(uv) edge.set_information(np.eye(2)) edge.set_robust_kernel(robust_kernel) opt.add_edge(edge) opt.set_verbose(True) opt.initialize_optimization() opt.optimize(max_iters)
def optimize(self): # optimizer opt = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) opt.set_algorithm(solver) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) for f in self.frames: sbacam = g2o.SBACam(g2o.SE3Quat(f.pose[:3, :3], f.pose[:3, 3])) sbacam.set_cam(f.K[0][0], f.K[1][1], f.K[2][0], f.K[2][1], 1.0) v_se3 = g2o.VertexCam() v_se3.set_id(f.id) v_se3.set_estimate(sbacam) v_se3.set_fixed(f.id == 0) opt.add_vertex(v_se3) for p in self.points: pt = g2o.VertexSBAPointXYZ() pt.set_id(p.id + 0x10000) pt.set_estimate(p.pt[0:3]) pt.set_marginalized(True) pt.set_fixed(False) opt.add_vertex(pt) for f in p.frames: edge = g2o.EdgeProjectP2MC() edge.set_vertex(0, pt) edge.set_vertex(1, opt.vertex(f.id)) uv = f.kps[f.pts.index(p)] edge.set_measurement(uv) edge.set_information(np.eye(2)) edge.set_robust_kernel(robust_kernel) opt.add_edge(edge) opt.set_verbose(True) opt.initialize_optimization() opt.optimize(20)
def bundle_adjustment(points_3d, points_2d, r_mat, t_vec): optimizer = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer.set_algorithm(solver) pose = g2o.VertexSE3Expmap() pose.set_estimate(g2o.SE3Quat(r_mat, t_vec.reshape((3, )))) pose.set_id(0) optimizer.add_vertex(pose) index = 1 for p_3d in points_3d: point = g2o.VertexSBAPointXYZ() point.set_id(index) point.set_estimate(p_3d) point.set_marginalized(True) optimizer.add_vertex(point) index += 1 camera = g2o.CameraParameters(K[0, 0], np.array([K[0, 2], K[1, 2]]), 0) camera.set_id(0) optimizer.add_parameter(camera) index = 1 for p_2d in points_2d: edge = g2o.EdgeProjectXYZ2UV() edge.set_id(index) edge.set_vertex(0, optimizer.vertex(index)) edge.set_vertex(1, pose) edge.set_measurement(p_2d) edge.set_parameter_id(0, 0) edge.set_information(np.identity(2)) optimizer.add_edge(edge) index += 1 optimizer.initialize_optimization() optimizer.set_verbose(True) optimizer.optimize(100) print('T = \n', pose.estimate().matrix())
def main(): optimizer = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer.set_algorithm(solver) true_points = np.hstack([ np.random.random((500, 1)) * 3 - 1.5, np.random.random((500, 1)) - 0.5, np.random.random((500, 1)) + 3 ]) focal_length = [500, 500] principal_point = [320, 240] baseline = 0.075 camera = g2o.CameraParameters(500, [320, 240], 0.075) camera.set_id(10000) optimizer.add_parameter(camera) true_poses = [] num_pose = 5 for i in range(num_pose): # pose here transform points from world coordinates to camera coordinates pose = g2o.SE3Quat(np.identity(3), [i * 0.04 - 1, 0, 0]) true_poses.append(pose) v_se3 = g2o.VertexSE3Expmap() v_se3.set_id(i) v_se3.set_estimate(pose) if i < 2: v_se3.set_fixed(True) optimizer.add_vertex(v_se3) point_id = num_pose inliers = dict() sse = defaultdict(float) for i, point in enumerate(true_points): visible = [] for j, pose in enumerate(true_poses): z = camera.cam_map(pose * point) if 0 <= z[0] < 640 and 0 <= z[1] < 480: visible.append((j, z)) if len(visible) < 2: continue vp = g2o.VertexSBAPointXYZ() vp.set_id(point_id) vp.set_marginalized(True) vp.set_estimate(point + np.random.randn(3)) optimizer.add_vertex(vp) inlier = True for j, z in visible: if np.random.random() < args.outlier_ratio: inlier = False z = np.array([ np.random.uniform(64, 640), np.random.uniform(0, 480), np.random.uniform(0, 64) ]) # disparity z[2] = z[0] - z[2] z += np.random.randn(2) * args.pixel_noise edge = g2o.Edge_XYZ_VSC() edge.set_vertex(0, vp) edge.set_vertex(1, optimizer.vertex(j)) edge.set_measurement(z) edge.set_information(np.identity(2)) if args.robust_kernel: edge.set_robust_kernel(g2o.RobustKernelHuber()) edge.set_parameter_id(0, 0) optimizer.add_edge(edge) if inlier: inliers[point_id] = i error = vp.estimate() - true_points[i] sse[0] += np.sum(error**2) point_id += 1 print('Performing full BA:') optimizer.initialize_optimization() optimizer.set_verbose(True) optimizer.optimize(10) for i in inliers: vp = optimizer.vertex(i) error = vp.estimate() - true_points[inliers[i]] sse[1] += np.sum(error**2) print('\nCamera focal: \n{}\n'.format(camera.focal_length)) print('\nCamera principal point: \n{}\n'.format(camera.principal_point)) print('\nRMSE (inliers only):') print('before optimization:', np.sqrt(sse[0] / len(inliers))) print('after optimization:', np.sqrt(sse[1] / len(inliers)))
def __init__(self): self._optimizer = g2o.SparseOptimizer() block_solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) optimization_algorithm = g2o.OptimizationAlgorithmLevenberg( block_solver) self._optimizer.set_algorithm(optimization_algorithm)
def graph_to_optimizer(self): """Convert a :class: graph to a :class: g2o.SparseOptimizer. Only the edges and vertices fields need to be filled out. Returns: A :class: g2o.SparseOptimizer that can be optimized via its optimize class method. """ optimizer = g2o.SparseOptimizer() optimizer.set_algorithm(g2o.OptimizationAlgorithmLevenberg( g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()))) if self.is_sparse_bundle_adjustment: for i in self.vertices: if self.vertices[i].mode == VertexType.TAGPOINT: vertex = g2o.VertexSBAPointXYZ() vertex.set_estimate(self.vertices[i].estimate[:3]) else: vertex = g2o.VertexSE3Expmap() vertex.set_estimate(pose_to_se3quat(self.vertices[i].estimate)) vertex.set_id(i) vertex.set_fixed(self.vertices[i].fixed) optimizer.add_vertex(vertex) cam_idx = 0 for i in self.edges: if self.edges[i].corner_ids is None: edge = g2o.EdgeSE3Expmap() for j, k in enumerate([self.edges[i].startuid, self.edges[i].enduid]): edge.set_vertex(j, optimizer.vertex(k)) edge.set_measurement(pose_to_se3quat(self.edges[i].measurement)) edge.set_information(self.edges[i].information) optimizer.add_edge(edge) else: # Note: we only use the focal length in the x direction since: (a) that's all that g2o supports and # (b) it is always the same in ARKit (at least currently) cam = g2o.CameraParameters(self.edges[i].camera_intrinsics[0], self.edges[i].camera_intrinsics[2:], 0) cam.set_id(cam_idx) optimizer.add_parameter(cam) for corner_idx, corner_id in enumerate(self.edges[i].corner_ids): edge = g2o.EdgeProjectPSI2UV() edge.resize(3) edge.set_vertex(0, optimizer.vertex(corner_id)) edge.set_vertex(1, optimizer.vertex(self.edges[i].startuid)) edge.set_vertex(2, optimizer.vertex(self.edges[i].enduid)) edge.set_information(self.edges[i].information) edge.set_measurement(self.edges[i].measurement[corner_idx * 2:corner_idx * 2 + 2]) edge.set_parameter_id(0, cam_idx) if self.use_huber: edge.set_robust_kernel(g2o.RobustKernelHuber(self.huber_delta)) optimizer.add_edge(edge) cam_idx += 1 else: for i in self.vertices: vertex = g2o.VertexSE3() vertex.set_id(i) vertex.set_estimate(pose_to_isometry(self.vertices[i].estimate)) vertex.set_fixed(self.vertices[i].fixed) optimizer.add_vertex(vertex) for i in self.edges: edge = g2o.EdgeSE3() for j, k in enumerate([self.edges[i].startuid, self.edges[i].enduid]): edge.set_vertex(j, optimizer.vertex(k)) edge.set_measurement(pose_to_isometry(self.edges[i].measurement)) edge.set_information(self.edges[i].information) edge.set_id(i) optimizer.add_edge(edge) return optimizer
def main(): optimizer = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer.set_algorithm(solver) focal_length = 1000 principal_point = (320, 240) cam = g2o.CameraParameters(focal_length, principal_point, 0) cam.set_id(0) optimizer.add_parameter(cam) true_points = np.hstack([ np.random.random((500, 1)) * 3 - 1.5, np.random.random((500, 1)) - 0.5, np.random.random((500, 1)) + 3 ]) true_poses = [] num_pose = 15 for i in range(num_pose): # pose here means transform points from world coordinates to camera coordinates pose = g2o.SE3Quat(np.identity(3), [i * 0.04 - 1, 0, 0]) true_poses.append(pose) v_se3 = g2o.VertexSE3Expmap() v_se3.set_id(i) v_se3.set_estimate(pose) if i < 2: v_se3.set_fixed(True) optimizer.add_vertex(v_se3) point_id = num_pose inliers = dict() sse = defaultdict(float) for i, point in enumerate(true_points): visible = [] for j, pose in enumerate(true_poses): z = cam.cam_map(pose * point) if 0 <= z[0] < 640 and 0 <= z[1] < 480: visible.append((j, z)) if len(visible) < 2: continue vp = g2o.VertexSBAPointXYZ() vp.set_id(point_id) vp.set_marginalized(True) vp.set_estimate(point + np.random.randn(3)) optimizer.add_vertex(vp) inlier = True for j, z in visible: if np.random.random() < args.outlier_ratio: inlier = False z = np.random.random(2) * [640, 480] z += np.random.randn(2) * args.pixel_noise edge = g2o.EdgeProjectXYZ2UV() edge.set_vertex(0, vp) edge.set_vertex(1, optimizer.vertex(j)) edge.set_measurement(z) edge.set_information(np.identity(2)) if args.robust_kernel: edge.set_robust_kernel(g2o.RobustKernelHuber()) edge.set_parameter_id(0, 0) optimizer.add_edge(edge) if inlier: inliers[point_id] = i error = vp.estimate() - true_points[i] sse[0] += np.sum(error**2) point_id += 1 print('num vertices:', len(optimizer.vertices())) print('num edges:', len(optimizer.edges())) print('Performing full BA:') optimizer.initialize_optimization() optimizer.set_verbose(True) optimizer.optimize(10) for i in inliers: print(i) vp = optimizer.vertex(i) error = vp.estimate() - true_points[inliers[i]] sse[1] += np.sum(error**2) print('\nRMSE (inliers only):') print('before optimization:', np.sqrt(sse[0] / len(inliers))) print('after optimization:', np.sqrt(sse[1] / len(inliers)))
def local_bundle_adjustment(keyframes, points, keyframes_ref=[], fixed_points=False, verbose=False, rounds=10, abort_flag=g2o.Flag(), map_lock=None): # create g2o optimizer opt = g2o.SparseOptimizer() block_solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) #block_solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) #block_solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(block_solver) opt.set_algorithm(solver) opt.set_force_stop_flag(abort_flag) #robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) # chi-square 2 DOFs thHuberMono = math.sqrt(5.991); # chi-square 2 DOFS graph_keyframes, graph_points = {}, {} # add frame vertices to graph for kf in keyframes: if kf.is_bad: continue #print('adding vertex frame ', f.id, ' to graph') se3 = g2o.SE3Quat(kf.Rcw, kf.tcw) v_se3 = g2o.VertexSE3Expmap() v_se3.set_estimate(se3) v_se3.set_id(kf.kid * 2) # even ids (use f.kid here!) v_se3.set_fixed(kf.kid==0) # (use f.kid here!) opt.add_vertex(v_se3) graph_keyframes[kf] = v_se3 # confirm pose correctness #est = v_se3.estimate() #assert np.allclose(pose[0:3, 0:3], est.rotation().matrix()) #assert np.allclose(pose[0:3, 3], est.translation()) # add reference frame vertices to graph for kf in keyframes_ref: if kf.is_bad: continue #print('adding vertex frame ', f.id, ' to graph') se3 = g2o.SE3Quat(kf.Rcw, kf.tcw) v_se3 = g2o.VertexSE3Expmap() v_se3.set_estimate(se3) v_se3.set_id(kf.kid * 2) # even ids (use f.kid here!) v_se3.set_fixed(True) opt.add_vertex(v_se3) graph_keyframes[kf] = v_se3 graph_edges = {} num_edges = 0 num_bad_edges = 0 # add point vertices to graph for p in points: assert(p is not None) if p.is_bad: # do not consider bad points continue if not any([f in keyframes for f in p.keyframes()]): Printer.orange('point %d without a viewing keyframe in input keyframes!!' %(p.id)) #Printer.orange(' keyframes: ',p.observations_string()) continue #print('adding vertex point ', p.id,' to graph') v_p = g2o.VertexSBAPointXYZ() v_p.set_id(p.id * 2 + 1) # odd ids v_p.set_estimate(p.pt[0:3]) v_p.set_marginalized(True) v_p.set_fixed(fixed_points) opt.add_vertex(v_p) graph_points[p] = v_p # add edges for kf, p_idx in p.observations(): if kf.is_bad: continue if kf not in graph_keyframes: continue if __debug__: p_f = kf.get_point_match(p_idx) if p_f != p: print('frame: ', kf.id, ' missing point ', p.id, ' at index p_idx: ', p_idx) if p_f is not None: print('p_f:', p_f) print('p:',p) assert(kf.get_point_match(p_idx) is p) #print('adding edge between point ', p.id,' and frame ', f.id) edge = g2o.EdgeSE3ProjectXYZ() edge.set_vertex(0, v_p) edge.set_vertex(1, graph_keyframes[kf]) edge.set_measurement(kf.kpsu[p_idx]) invSigma2 = Frame.feature_manager.inv_level_sigmas2[kf.octaves[p_idx]] edge.set_information(np.eye(2)*invSigma2) edge.set_robust_kernel(g2o.RobustKernelHuber(thHuberMono)) edge.fx = kf.camera.fx edge.fy = kf.camera.fy edge.cx = kf.camera.cx edge.cy = kf.camera.cy opt.add_edge(edge) graph_edges[edge] = (p,kf,p_idx) # one has kf.points[p_idx] == p num_edges += 1 if verbose: opt.set_verbose(True) if abort_flag.value: return -1,0 # initial optimization opt.initialize_optimization() opt.optimize(5) if not abort_flag.value: chi2Mono = 5.991 # chi-square 2 DOFs # check inliers observation for edge, edge_data in graph_edges.items(): p = edge_data[0] if p.is_bad: continue if edge.chi2() > chi2Mono or not edge.is_depth_positive(): edge.set_level(1) num_bad_edges += 1 edge.set_robust_kernel(None) # optimize again without outliers opt.initialize_optimization() opt.optimize(rounds) # search for final outlier observations and clean map num_bad_observations = 0 # final bad observations outliers_data = [] for edge, edge_data in graph_edges.items(): p, kf, p_idx = edge_data if p.is_bad: continue assert(kf.get_point_match(p_idx) is p) if edge.chi2() > chi2Mono or not edge.is_depth_positive(): num_bad_observations += 1 outliers_data.append(edge_data) if map_lock is None: map_lock = RLock() # put a fake lock with map_lock: # remove outlier observations for d in outliers_data: p, kf, p_idx = d p_f = kf.get_point_match(p_idx) if p_f is not None: assert(p_f is p) p.remove_observation(kf,p_idx) # the following instruction is now included in p.remove_observation() #f.remove_point(p) # it removes multiple point instances (if these are present) #f.remove_point_match(p_idx) # this does not remove multiple point instances, but now there cannot be multiple instances any more # put frames back for kf in graph_keyframes: est = graph_keyframes[kf].estimate() #R = est.rotation().matrix() #t = est.translation() #f.update_pose(poseRt(R, t)) kf.update_pose(g2o.Isometry3d(est.orientation(), est.position())) # put points back if not fixed_points: for p in graph_points: p.update_position(np.array(graph_points[p].estimate())) p.update_normal_and_depth(force=True) active_edges = num_edges-num_bad_edges mean_squared_error = opt.active_chi2()/active_edges return mean_squared_error, num_bad_observations/max(num_edges,1)
def __init__(self): self.optimizer = g2o.SparseOptimizer() solver = g2o.BlockSolverSE2(g2o.LinearSolverCholmodSE2()) solver = g2o.OptimizationAlgorithmLevenberg(solver) self.optimizer.set_algorithm(solver)
def main(): optimizer = g2o.SparseOptimizer() solver = g2o.BlockSolverX(g2o.LinearSolverCSparseX()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer.set_algorithm(solver) true_points = np.hstack([ np.random.random((1000, 1)) * 3 - 1.5, np.random.random((1000, 1)) - 0.5, np.random.random((1000, 1)) + 10 ]) focal_length = (500, 500) principal_point = (320, 240) baseline = 0.075 g2o.VertexSCam.set_cam(*focal_length, *principal_point, baseline) for i in range(2): t = np.array([0, 0, i]) cam = g2o.Isometry3d(np.identity(3), t) vc = g2o.VertexSCam() vc.set_id(i) vc.set_estimate(cam) if i == 0: vc.set_fixed(True) vc.set_all() optimizer.add_vertex(vc) trans0 = optimizer.vertex(0).estimate().inverse() trans1 = optimizer.vertex(1).estimate().inverse() for i in range(len(true_points)): pt0 = trans0 * true_points[i] pt1 = trans1 * true_points[i] # add noise pt0 += np.random.randn(3) * args.pos_noise pt1 += np.random.randn(3) * args.pos_noise # form edge, with normals in varioius positions nm0 = np.array([0, i, 1]) nm0 = nm0 / np.linalg.norm(nm0) nm1 = np.array([0, i, 1]) nm1 = nm1 / np.linalg.norm(nm1) meas = g2o.EdgeGICP() meas.pos0 = pt0 meas.pos1 = pt1 meas.normal0 = nm0 meas.normal1 = nm1 edge = g2o.Edge_V_V_GICP() edge.set_vertex(0, optimizer.vertex(0)) edge.set_vertex(1, optimizer.vertex(1)) edge.set_measurement(meas) edge.set_information(meas.prec0(0.01)) optimizer.add_edge(edge) # set up SBA projections if args.num_points > 0: true_points = np.hstack([ np.random.random((args.num_points, 1)) * 3 - 1.5, np.random.random((args.num_points, 1)) - 0.5, np.random.random((args.num_points, 1)) + 10 ]) cam_num = 2 for i, point in enumerate(true_points): vp = g2o.VertexSBAPointXYZ() vp.set_id(cam_num + i) vp.set_marginalized(True) vp.set_estimate(point + np.random.randn(3)) optimizer.add_vertex(vp) for j in range(cam_num): z = optimizer.vertex(j).map_point(point) if 0 <= z[0] < 640 and 0 <= z[1] < 480: z += np.random.randn(3) * args.pixel_noise * [ 1, 1, 1 / 16. ] edge = g2o.Edge_XYZ_VSC() edge.set_vertex(0, vp) edge.set_vertex(1, optimizer.vertex(j)) edge.set_measurement(z) edge.set_information(np.identity(3)) edge.set_robust_kernel(g2o.RobustKernelHuber()) optimizer.add_edge(edge) # move second cam off of its true position vc = optimizer.vertex(1) cam = g2o.Isometry3d(vc.estimate().R, np.array([-0.1, -0.1, 0.2])) vc.set_estimate(cam) optimizer.initialize_optimization() optimizer.compute_active_errors() print('Initial chi2 =', optimizer.chi2()) optimizer.set_verbose(True) optimizer.optimize(20) print('\nSecond vertex should be near [0, 0, 1]') print('before optimization:', cam.t) print('after optimization:', optimizer.vertex(1).estimate().t) print('error:', optimizer.vertex(1).estimate().t - [0, 0, 1]) '''
def optimize(frames, points, local_window, fix_points, verbose=False, rounds=50): if local_window is None: local_frames = frames else: local_frames = frames[-local_window:] # create g2o optimizer opt = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) opt.set_algorithm(solver) # add normalized camera cam = g2o.CameraParameters(1.0, (0.0, 0.0), 0) cam.set_id(0) opt.add_parameter(cam) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) graph_frames, graph_points = {}, {} # add frames to graph for f in (local_frames if fix_points else frames): pose = f.pose se3 = g2o.SE3Quat(pose[0:3, 0:3], pose[0:3, 3]) v_se3 = g2o.VertexSE3Expmap() v_se3.set_estimate(se3) v_se3.set_id(f.id * 2) v_se3.set_fixed(f.id <= 1 or f not in local_frames) #v_se3.set_fixed(f.id != 0) opt.add_vertex(v_se3) # confirm pose correctness est = v_se3.estimate() assert np.allclose(pose[0:3, 0:3], est.rotation().matrix()) assert np.allclose(pose[0:3, 3], est.translation()) graph_frames[f] = v_se3 # add points to frames for p in points: if not any([f in local_frames for f in p.frames]): continue pt = g2o.VertexSBAPointXYZ() pt.set_id(p.id * 2 + 1) pt.set_estimate(p.pt[0:3]) pt.set_marginalized(True) pt.set_fixed(fix_points) opt.add_vertex(pt) graph_points[p] = pt # add edges for f, idx in zip(p.frames, p.idxs): if f not in graph_frames: continue edge = g2o.EdgeProjectXYZ2UV() edge.set_parameter_id(0, 0) edge.set_vertex(0, pt) edge.set_vertex(1, graph_frames[f]) edge.set_measurement(f.kps[idx]) edge.set_information(np.eye(2)) edge.set_robust_kernel(robust_kernel) opt.add_edge(edge) if verbose: opt.set_verbose(True) opt.initialize_optimization() opt.optimize(rounds) # put frames back for f in graph_frames: est = graph_frames[f].estimate() R = est.rotation().matrix() t = est.translation() f.pose = poseRt(R, t) # put points back if not fix_points: for p in graph_points: p.pt = np.array(graph_points[p].estimate()) return opt.active_chi2()
def main(): optimizer = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer.set_algorithm(solver) focal_length = (500, 500) principal_point = (320, 240) baseline = 0.075 true_points = np.hstack([ np.random.random((500, 1)) * 3 - 1.5, np.random.random((500, 1)) - 0.5, np.random.random((500, 1)) + 3]) num_pose = 15 for i in range(num_pose): # pose here means transform points from camera coordinates to world coordinates pose = g2o.SE3Quat(np.identity(3), [i*0.04-1, 0, 0]) sbacam = g2o.SBACam(pose) sbacam.set_cam(*focal_length, *principal_point, baseline) v_cam = g2o.VertexCam() v_cam.set_id(i) v_cam.set_estimate(sbacam) if i < 2: v_cam.set_fixed(True) optimizer.add_vertex(v_cam) point_id = num_pose inliers = dict() sse = defaultdict(float) for i, point in enumerate(true_points): visible = [] for j in range(num_pose): proj = optimizer.vertex(j).estimate().w2i.dot( np.hstack([point, [1]])) # project to left camera z = proj[:2] / proj[2] if 0 <= z[0] < 640 and 0 <= z[1] < 480: visible.append((j, z)) if len(visible) < 2: continue vp = g2o.VertexSBAPointXYZ() vp.set_id(point_id) vp.set_marginalized(True) vp.set_estimate(point + np.random.randn(3)) optimizer.add_vertex(vp) inlier = True for j, z in visible: if np.random.random() < args.outlier_ratio: inlier = False z = np.random.random(2) * [640, 480] z += np.random.randn(2) * args.pixel_noise edge = g2o.EdgeProjectP2MC() # if stereo, use EdgeProjectP2SC edge.set_vertex(0, vp) edge.set_vertex(1, optimizer.vertex(j)) edge.set_measurement(z) edge.set_information(np.identity(2)) if args.robust_kernel: edge.set_robust_kernel(g2o.RobustKernelHuber()) #edge.set_parameter_id(0, 0) optimizer.add_edge(edge) if inlier: inliers[point_id] = i error = vp.estimate() - true_points[i] sse[0] += np.sum(error**2) point_id += 1 print('num vertices:', len(optimizer.vertices())) print('num edges:', len(optimizer.edges())) print('Performing full BA:') optimizer.initialize_optimization() optimizer.set_verbose(True) optimizer.optimize(10) for i in inliers: vp = optimizer.vertex(i) error = vp.estimate() - true_points[inliers[i]] sse[1] += np.sum(error**2) print('\nRMSE (inliers only):') print('before optimization:', np.sqrt(sse[0] / len(inliers))) print('after optimization:', np.sqrt(sse[1] / len(inliers)))
def optimize(self, local_window=20, fix_points=False, verbose=False): # create g2o optimizer opt = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) opt.set_algorithm(solver) if self.alt: principal_point = (self.frames[0].K[0][2], self.frames[0].K[1][2]) cam = g2o.CameraParameters(self.frames[0].K[0][0], principal_point, 0) cam.set_id(0) opt.add_parameter(cam) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) if local_window is None: local_frames = self.frames else: local_frames = self.frames[-local_window:] graph_frames, graph_points = {}, {} # add frames to graph for f in (local_frames if fix_points else self.frames): if not self.alt: pose = np.linalg.inv(f.pose) se3 = g2o.SE3Quat(pose[0:3, 0:3], pose[0:3, 3]) sbacam = g2o.SBACam(se3) sbacam.set_cam(f.K[0][0], f.K[1][1], f.K[0][2], f.K[1][2], 0.0) v_se3 = g2o.VertexCam() v_se3.set_estimate(sbacam) else: pose = f.pose se3 = g2o.SE3Quat(pose[0:3, 0:3], pose[0:3, 3]) v_se3 = g2o.VertexSE3Expmap() v_se3.set_estimate(se3) v_se3.set_id(f.id * 2) v_se3.set_fixed(f.id <= 1 or f not in local_frames) # v_se3.set_fixed(f.id != 0) opt.add_vertex(v_se3) # confirm pose correctness est = v_se3.estimate() assert np.allclose(pose[0:3, 0:3], est.rotation().matrix()) assert np.allclose(pose[0:3, 3], est.translation()) graph_frames[f] = v_se3 # add points to frames for p in self.points: if not any([f in local_frames for f in p.frames]): continue pt = g2o.VertexSBAPointXYZ() pt.set_id(p.id * 2 + 1) pt.set_estimate(p.loc[0:3]) pt.set_marginalized(True) pt.set_fixed(fix_points) opt.add_vertex(pt) graph_points[p] = pt # add edges for f, idx in zip(p.frames, p.idxs): if f not in graph_frames: continue if not self.alt: edge = g2o.EdgeProjectP2MC() else: edge = g2o.EdgeProjectXYZ2UV() edge.set_parameter_id(0, 0) edge.set_vertex(0, pt) edge.set_vertex(1, graph_frames[f]) uv = f.raw_pts[idx] edge.set_measurement(uv) edge.set_information(np.eye(2)) edge.set_robust_kernel(robust_kernel) opt.add_edge(edge) if verbose: opt.set_verbose(True) opt.initialize_optimization() opt.optimize(50) # put frames back for f in graph_frames: est = graph_frames[f].estimate() R = est.rotation().matrix() t = est.translation() if not self.alt: f.pose = np.linalg.inv(pose_homogeneous(R, t)) else: f.pose = pose_homogeneous(R, t) # put points back (and cull) if not fix_points: culled_pt_count = 0 for p in graph_points: est = graph_points[p].estimate() p.pt = np.array(est) # remove points if the number of observations <= (n-1) old_point = len( p.frames) <= 9 and p.frames[-1].id + 17 < self.max_frame # compute reprojection error errs = [] for f, idx in zip(p.frames, p.idxs): uv = f.raw_pts[idx] proj = np.dot(np.dot(f.K, f.pose[:3]), np.array([est[0], est[1], est[2], 1.0])) proj = proj[0:2] / proj[2] errs.append(np.linalg.norm(proj - uv)) # cull if old_point or np.mean(errs) > 2: culled_pt_count += 1 self.points.remove(p) p.delete() print("Culled: %d points" % culled_pt_count) return opt.active_chi2()
import sys import numpy as np import math sys.path.append("../../") from config import Config import g2o opt = g2o.SparseOptimizer() block_solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) solver = g2o.OptimizationAlgorithmLevenberg(block_solver) opt.set_algorithm(solver) flag = g2o.Flag() print('flag: ', flag.value) opt.set_force_stop_flag(flag) flag.value = False print('opt flag: ', opt.force_stop_flag()) flag.value = True print('opt flag: ', opt.force_stop_flag())
def optimize(self, K, frames, fix_points=False): PT_OFFSET = 10000 opt = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) opt.set_algorithm(solver) rk = g2o.RobustKernelHuber(np.sqrt(5.991)) # only optimize these poses and their Points local_frames = self.frames[-frames:] # a vertex for each camera pose for f in self.frames: assert (f.id < PT_OFFSET) quat = g2o.SE3Quat(f.pose[:3, :3], f.pose[:3, 3]) sbacam = g2o.SBACam(quat) sbacam.set_cam(K[0, 0], K[1, 1], K[0, 2], K[1, 2], 1.0) # for pixel input v = g2o.VertexCam() v.set_id(f.id) v.set_estimate(sbacam) v.set_fixed(f.id < 2 or f not in local_frames) opt.add_vertex(v) # a vertex for each point in cloud for p in self.points: # if p.frames[-1] not in local_frames: if not any([f in local_frames for f in p.frames]): continue vp = g2o.VertexSBAPointXYZ() vp.set_id(PT_OFFSET + p.id) vp.set_estimate(p.pt3d) vp.set_marginalized(True) vp.set_fixed(fix_points) opt.add_vertex(vp) # edge connects every camera with every point for f in p.frames: edge = g2o.EdgeProjectP2MC() # edge = g2o.EdgeSE3ProjectXYZ() edge.set_vertex(0, vp) edge.set_vertex(1, opt.vertex(f.id)) idx = f.pts.index(p) edge.set_measurement(f.kpus[idx]) edge.set_information(np.eye(2)) edge.set_robust_kernel(rk) opt.add_edge(edge) # opt.set_verbose(True) opt.initialize_optimization() opt.optimize(20) # print("chi2", opt.active_chi2()) # get back optimized poses self.opath = [] for f in self.frames: f_est = opt.vertex(f.id).estimate() R = f_est.rotation().matrix() t = f_est.translation() Rt = np.eye(4) Rt[:3, :3] = R Rt[:3, 3] = t.T # print(Rt) self.opath.append(t) f.pose = Rt if fix_points: return new_points = [] # add back or cull for p in self.points: vp = opt.vertex(PT_OFFSET + p.id) if vp is None: # not updated new_points.append(p) continue vp = opt.vertex(PT_OFFSET + p.id) p_est = vp.estimate() # if (len(p.frames) <= 5) and (p.frames[-1] not in local_frames): # p.delete() # continue errors = [] for f in p.frames: f_est = opt.vertex(f.id).estimate() measured = f.kpus[f.pts.index(p)] projected = f_est.w2i.dot(np.hstack( [p_est, [1]])) # only works because is VertexCam projected = projected[:2] / projected[ 2] # don't forget to h**o errors.append(np.linalg.norm(measured - projected)) error = np.mean(errors) # mean of squares - over all frames if error > 1.0: # px # print(f"error {error}, dropping") p.delete() else: p.pt3d = np.array(p_est) new_points.append(p) print("Dropping:", len(self.points) - len(new_points), ", Remaining:", len(new_points)) self.points = new_points
def bundle_adjustment(keyframes, points, local_window, fixed_points=False, verbose=False, rounds=10, use_robust_kernel=False, abort_flag=g2o.Flag()): if local_window is None: local_frames = keyframes else: local_frames = keyframes[-local_window:] # create g2o optimizer opt = g2o.SparseOptimizer() block_solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) #block_solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(block_solver) opt.set_algorithm(solver) opt.set_force_stop_flag(abort_flag) thHuberMono = math.sqrt(5.991); # chi-square 2 DOFS graph_keyframes, graph_points = {}, {} # add frame vertices to graph for kf in (local_frames if fixed_points else keyframes): # if points are fixed then consider just the local frames, otherwise we need all frames or at least two frames for each point if kf.is_bad: continue #print('adding vertex frame ', f.id, ' to graph') se3 = g2o.SE3Quat(kf.Rcw, kf.tcw) v_se3 = g2o.VertexSE3Expmap() v_se3.set_estimate(se3) v_se3.set_id(kf.kid * 2) # even ids (use f.kid here!) v_se3.set_fixed(kf.kid==0 or kf not in local_frames) #(use f.kid here!) opt.add_vertex(v_se3) # confirm pose correctness #est = v_se3.estimate() #assert np.allclose(pose[0:3, 0:3], est.rotation().matrix()) #assert np.allclose(pose[0:3, 3], est.translation()) graph_keyframes[kf] = v_se3 num_edges = 0 # add point vertices to graph for p in points: assert(p is not None) if p.is_bad: # do not consider bad points continue if __debug__: if not any([f in keyframes for f in p.keyframes()]): Printer.red('point without a viewing frame!!') continue #print('adding vertex point ', p.id,' to graph') v_p = g2o.VertexSBAPointXYZ() v_p.set_id(p.id * 2 + 1) # odd ids v_p.set_estimate(p.pt[0:3]) v_p.set_marginalized(True) v_p.set_fixed(fixed_points) opt.add_vertex(v_p) graph_points[p] = v_p # add edges for kf, idx in p.observations(): if kf.is_bad: continue if kf not in graph_keyframes: continue #print('adding edge between point ', p.id,' and frame ', f.id) edge = g2o.EdgeSE3ProjectXYZ() edge.set_vertex(0, v_p) edge.set_vertex(1, graph_keyframes[kf]) edge.set_measurement(kf.kpsu[idx]) invSigma2 = Frame.feature_manager.inv_level_sigmas2[kf.octaves[idx]] edge.set_information(np.eye(2)*invSigma2) if use_robust_kernel: edge.set_robust_kernel(g2o.RobustKernelHuber(thHuberMono)) edge.fx = kf.camera.fx edge.fy = kf.camera.fy edge.cx = kf.camera.cx edge.cy = kf.camera.cy opt.add_edge(edge) num_edges += 1 if verbose: opt.set_verbose(True) opt.initialize_optimization() opt.optimize(rounds) # put frames back for kf in graph_keyframes: est = graph_keyframes[kf].estimate() #R = est.rotation().matrix() #t = est.translation() #f.update_pose(poseRt(R, t)) kf.update_pose(g2o.Isometry3d(est.orientation(), est.position())) # put points back if not fixed_points: for p in graph_points: p.update_position(np.array(graph_points[p].estimate())) p.update_normal_and_depth(force=True) mean_squared_error = opt.active_chi2()/max(num_edges,1) return mean_squared_error
def optimize(self): # create g2o optimizer opt = g2o.SparseOptimizer() solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) opt.set_algorithm(solver) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) if LOCAL_WINDOW is None: local_frames = self.frames else: local_frames = self.frames[-LOCAL_WINDOW:] # add frames to graph for f in self.frames: pose = f.pose sbacam = g2o.SBACam(g2o.SE3Quat(pose[0:3, 0:3], pose[0:3, 3])) sbacam.set_cam(f.K[0][0], f.K[1][1], f.K[0][2], f.K[1][2], 1.0) v_se3 = g2o.VertexCam() v_se3.set_id(f.id) v_se3.set_estimate(sbacam) v_se3.set_fixed(f.id <= 1 or f not in local_frames) opt.add_vertex(v_se3) # add points to frames PT_ID_OFFSET = 0x10000 for p in self.points: if not any([f in local_frames for f in p.frames]): continue pt = g2o.VertexSBAPointXYZ() pt.set_id(p.id + PT_ID_OFFSET) pt.set_estimate(p.pt[0:3]) pt.set_marginalized(True) pt.set_fixed(False) opt.add_vertex(pt) for f in p.frames: edge = g2o.EdgeProjectP2MC() edge.set_vertex(0, pt) edge.set_vertex(1, opt.vertex(f.id)) uv = f.kpus[f.pts.index(p)] edge.set_measurement(uv) edge.set_information(np.eye(2)) edge.set_robust_kernel(robust_kernel) opt.add_edge(edge) #opt.set_verbose(True) opt.initialize_optimization() opt.optimize(50) # put frames back for f in self.frames: est = opt.vertex(f.id).estimate() R = est.rotation().matrix() t = est.translation() f.pose = poseRt(R, t) # put points back (and cull) new_points = [] for p in self.points: vert = opt.vertex(p.id + PT_ID_OFFSET) if vert is None: new_points.append(p) continue est = vert.estimate() # 2 match point that's old old_point = len(p.frames) == 2 and p.frames[-1] not in local_frames # compute reprojection error errs = [] for f in p.frames: uv = f.kpus[f.pts.index(p)] proj = np.dot(np.dot(f.K, np.linalg.inv(f.pose)[:3]), np.array([est[0], est[1], est[2], 1.0])) proj = proj[0:2] / proj[2] errs.append(np.linalg.norm(proj-uv)) # cull if (old_point and np.mean(errs) > 30) or np.mean(errs) > 100: p.delete() continue p.pt = np.array(est) new_points.append(p) self.points = new_points return opt.chi2()
def optimize(self, local_window = LOCAL_WINDOW, fix_points = False, verbose = False): # create the g2o optimizer optimizer = g2o.SparseOptimizer() graph_solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) graph_solver = g2o.OptimizationAlgorithmLevenberg(graph_solver) optimizer.set_algorithm(graph_solver) robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) if local_window is None: local_frames = self.frames else: local_frames = self.frames[-local_window:] # add frames to the graph for f in self.frames: pose = np.linalg.inv(f.pose) sbacam = g2o.SBACam(g2o.SE3Quat(pose[0:3, 0:3], pose[0:3, 3])) sbacam.set_cam(f.k[0][0], f.k[1][1], f.k[0][2], f.k[1][2], 1.0) v_se3 = g2o.VertexCam() v_se3.set_id(f.id) v_se3.set_estimate(sbacam) v_se3.set_fixed(f.id <= 1 or f not in local_frames) optimizer.add_vertex(v_se3) # add points to the frames point_id_offset = 0x10000 for p in self.points: if not any([f in local_frames for f in p.frames]): continue pt = g2o.VertexSBAPointXYZ() pt.set_id(p.id + point_id_offset) pt.set_estimate(p.point[0:3]) pt.set_marginalized(True) pt.set_fixed(fix_points) optimizer.add_vertex(pt) for f in p.frames: edge = g2o.EdgeProjectP2MC() edge.set_vertex(0, pt) edge.set_vertex(1, optimizer.vertex(f.id)) uv = f._kps[f.pts.index(p)] edge.set_measurement(uv) edge.set_information(np.eye(2)) edge.set_robust_kernel(robust_kernel) optimizer.add_edge(edge) if verbose: optimizer.set_verbose(True) optimizer.initialize_optimization() optimizer.optimize(20) # put the frames back for f in self.frames: estimate = optimizer.vertex(f.id).estimate() r = estimate.rotation().matrix() t = estimate.translation() f.pose = np.linalg.inv(pose_rt(r, t)) # put points back if not fix_points: new_points = [] for p in self.points: vert = optimizer.vertex(p.id + point_id_offset) if vert is None: new_points.append(p) continue estimate = vert.estimate() old_point = len(p.frames) <= 2 and p.frames[-1] not in local_frames # try and computer the reprojection error of the point errors = [] for f in p.frames:g uv = f._kps[f.pts.index(p)] proj = np.dot(np.dot(f.k, f.pose[:3]), np.array([estimate[0], estimate[1], estimate[2], 1.0])) proj = proj[0:2]/proj[2] errors.append(np.linalg.norm(proj-uv)) # culling if old_point or np.mean(errors) > 5: p.delete_point() continue p.point = np.array(estimate) new_points.append(p) print("Culled points: %d" %(len(self.points) - len(new_points))) self.points = new_points return optimizer.active_chi2()
def main(): optimizer = g2o.SparseOptimizer() # solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) # solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) solver = g2o.OptimizationAlgorithmLevenberg(solver) optimizer.set_algorithm(solver) # Convergence Criterion terminate = g2o.SparseOptimizerTerminateAction() terminate.set_gain_threshold(1e-6) optimizer.add_post_iteration_action(terminate) # Robust cost Function (Huber function) delta delta = np.sqrt(5.991) true_points = np.hstack([ np.random.random((25, 1)) * 3 - 1.5, np.random.random((25, 1)) - 0.5, np.random.random((25, 1)) + 3]) fx = 600. fy = 600. cx = 320. cy = 240. principal_point = (cx, cy) cam = g2o.CameraParameters(fx, principal_point, 0) true_poses = [] num_pose = 10 for i in range(num_pose): # pose here means transform points from world coordinates to camera coordinates pose = g2o.SE3Quat(np.identity(3), [i*0.04-1, 0, 0]) true_poses.append(pose) v_se3 = g2o.VertexSE3Expmap() v_se3.set_id(i) v_se3.set_estimate(pose) if i < 2: v_se3.set_fixed(True) optimizer.add_vertex(v_se3) print(optimizer.vertices()) point_id = num_pose inliers = dict() sse = defaultdict(float) vp_edge = [] for i, point in enumerate(true_points): visible = [] for j, pose in enumerate(true_poses): z = cam.cam_map(pose * point) if 0 <= z[0] < 640 and 0 <= z[1] < 480: visible.append((j, z)) if len(visible) < 2: continue vp = g2o.VertexSBAPointXYZ() vp.set_estimate(point + np.random.randn(3)) vp.set_id(point_id) vp.set_marginalized(True) optimizer.add_vertex(vp) inlier = True for j, z in visible: if np.random.random() < args.outlier_ratio: inlier = False z = np.random.random(2) * [640, 480] z += np.random.randn(2) * args.pixel_noise e = g2o.EdgeSE3ProjectXYZ() e.set_vertex(0,vp) e.set_vertex(1,optimizer.vertex(j)) e.set_measurement(z) e.set_information(np.identity(2)) rk = g2o.RobustKernelHuber() e.set_robust_kernel(rk) rk.set_delta(delta) e.fx = fx e.fy = fy e.cx = cx e.cy = cy optimizer.add_edge(e) vp_edge.append(e) if inlier: inliers[point_id] = i error = vp.estimate() - true_points[i] sse[0] += np.sum(error**2) point_id += 1 print('num vertices:', len(optimizer.vertices())) print('num edges:', len(optimizer.edges())) print(optimizer.vertices()) print() print('Performing full BA:') optimizer.initialize_optimization() optimizer.set_verbose(True) optimizer.optimize(5) for i in inliers: vp = optimizer.vertex(i) error = vp.estimate() - true_points[inliers[i]] sse[1] += np.sum(error**2) print('\nRMSE (inliers only):') print('before optimization:', np.sqrt(sse[0] / len(inliers))) print('after optimization:', np.sqrt(sse[1] / len(inliers))) # print(optimizer.vertices()) print() for i in xrange(num_pose): print(optimizer.vertex(i).estimate().inverse().matrix()) j = num_pose for i in xrange(len(inliers)): print(optimizer.vertex(j).estimate().shape) j += 1 i = 0 """
def pose_optimization(frame, verbose=False, rounds=10): is_ok = True # create g2o optimizer opt = g2o.SparseOptimizer() #block_solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) #block_solver = g2o.BlockSolverSE3(g2o.LinearSolverDenseSE3()) block_solver = g2o.BlockSolverSE3(g2o.LinearSolverEigenSE3()) solver = g2o.OptimizationAlgorithmLevenberg(block_solver) opt.set_algorithm(solver) #robust_kernel = g2o.RobustKernelHuber(np.sqrt(5.991)) # chi-square 2 DOFs thHuberMono = math.sqrt(5.991); # chi-square 2 DOFS point_edge_pairs = {} num_point_edges = 0 v_se3 = g2o.VertexSE3Expmap() v_se3.set_estimate(g2o.SE3Quat(frame.Rcw, frame.tcw)) v_se3.set_id(0) v_se3.set_fixed(False) opt.add_vertex(v_se3) with MapPoint.global_lock: # add point vertices to graph for idx, p in enumerate(frame.points): if p is None: continue # reset outlier flag frame.outliers[idx] = False # add edge #print('adding edge between point ', p.id,' and frame ', frame.id) edge = g2o.EdgeSE3ProjectXYZOnlyPose() edge.set_vertex(0, opt.vertex(0)) edge.set_measurement(frame.kpsu[idx]) invSigma2 = Frame.feature_manager.inv_level_sigmas2[frame.octaves[idx]] edge.set_information(np.eye(2)*invSigma2) edge.set_robust_kernel(g2o.RobustKernelHuber(thHuberMono)) edge.fx = frame.camera.fx edge.fy = frame.camera.fy edge.cx = frame.camera.cx edge.cy = frame.camera.cy edge.Xw = p.pt[0:3] opt.add_edge(edge) point_edge_pairs[p] = (edge, idx) # one edge per point num_point_edges += 1 if num_point_edges < 3: Printer.red('pose_optimization: not enough correspondences!') is_ok = False return 0, is_ok, 0 if verbose: opt.set_verbose(True) # perform 4 optimizations: # after each optimization we classify observation as inlier/outlier; # at the next optimization, outliers are not included, but at the end they can be classified as inliers again chi2Mono = 5.991 # chi-square 2 DOFs num_bad_point_edges = 0 for it in range(4): v_se3.set_estimate(g2o.SE3Quat(frame.Rcw, frame.tcw)) opt.initialize_optimization() opt.optimize(rounds) num_bad_point_edges = 0 for p, edge_pair in point_edge_pairs.items(): edge, idx = edge_pair if frame.outliers[idx]: edge.compute_error() chi2 = edge.chi2() if chi2 > chi2Mono: frame.outliers[idx] = True edge.set_level(1) num_bad_point_edges +=1 else: frame.outliers[idx] = False edge.set_level(0) if it == 2: edge.set_robust_kernel(None) if len(opt.edges()) < 10: Printer.red('pose_optimization: stopped - not enough edges!') is_ok = False break print('pose optimization: available ', num_point_edges, ' points, found ', num_bad_point_edges, ' bad points') if num_point_edges == num_bad_point_edges: Printer.red('pose_optimization: all the available correspondences are bad!') is_ok = False # update pose estimation if is_ok: est = v_se3.estimate() # R = est.rotation().matrix() # t = est.translation() # frame.update_pose(poseRt(R, t)) frame.update_pose(g2o.Isometry3d(est.orientation(), est.position())) # since we have only one frame here, each edge corresponds to a single distinct point num_valid_points = num_point_edges - num_bad_point_edges mean_squared_error = opt.active_chi2()/max(num_valid_points,1) return mean_squared_error, is_ok, num_valid_points