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// ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// The MIT License (MIT)
//
// Copyright (c) 2018-2021 www.open3d.org
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
// IN THE SOFTWARE.
// ----------------------------------------------------------------------------
#include "pybind/t/pipelines/slac/slac.h"
#include "open3d/t/geometry/PointCloud.h"
#include "open3d/t/pipelines/slac/ControlGrid.h"
#include "open3d/t/pipelines/slac/SLACOptimizer.h"
#include "open3d/utility/Logging.h"
#include "pybind/docstring.h"
namespace open3d {
namespace t {
namespace pipelines {
namespace slac {
void pybind_slac_classes(py::module &m) {
py::class_<SLACOptimizerParams> slac_optimizer_params(
m, "slac_optimizer_params",
"SLAC parameters to tune in optimization.");
py::detail::bind_copy_functions<SLACOptimizerParams>(slac_optimizer_params);
slac_optimizer_params
.def(py::init<const int, const float, const float, const float,
const float, const core::Device, const std::string>(),
"max_iterations"_a = 5, "voxel_size"_a = 0.05,
"distance_threshold"_a = 0.07, "fitness_threshold"_a = 0.3,
"regularizer_weight"_a = 1, "device"_a = core::Device("CPU:0"),
"slac_folder"_a = "")
.def_readwrite("max_iterations",
&SLACOptimizerParams::max_iterations_,
"Number of iterations.")
.def_readwrite("voxel_size", &SLACOptimizerParams::voxel_size_,
"Voxel size to downsample input point cloud.")
.def_readwrite("distance_threshold",
&SLACOptimizerParams::distance_threshold_,
" Distance threshold to filter inconsistent "
"correspondences.")
.def_readwrite("fitness_threshold",
&SLACOptimizerParams::fitness_threshold_,
"Fitness threshold to filter inconsistent pairs.")
.def_readwrite("regularizer_weight",
&SLACOptimizerParams::regularizer_weight_,
"Weight of the regularizer.")
.def_readwrite("device", &SLACOptimizerParams::device_,
"Device to use.")
.def_readwrite("slac_folder", &SLACOptimizerParams::slac_folder_,
"Relative directory to store SLAC results in the "
"dataset folder.")
.def(
"get_subfolder_name",
[](const SLACOptimizerParams &slac_optimizer_params) {
return slac_optimizer_params.GetSubfolderName();
},
"Relative directory to store SLAC results in the dataset "
"folder.")
.def("__repr__", [](const SLACOptimizerParams ¶ms) {
return fmt::format(
"SLACOptimizerParams[max_iterations={:d}, "
"voxel_size={:e}, distance_threshold={:e}, "
"fitness_threshold={:e}, regularizer_weight={:e}, "
"device={}, slac_folder={}].",
params.max_iterations_, params.voxel_size_,
params.distance_threshold_, params.fitness_threshold_,
params.regularizer_weight_, params.device_.ToString(),
params.slac_folder_);
});
py::class_<SLACDebugOption> slac_debug_option(m, "slac_debug_option",
"SLAC debug options.");
py::detail::bind_copy_functions<SLACDebugOption>(slac_debug_option);
slac_debug_option
.def(py::init<const bool, const int>(), "debug"_a = false,
"debug_start_node_idx"_a = 0)
.def(py::init<const int>(), "debug_start_node_idx"_a)
.def_readwrite("debug", &SLACDebugOption::debug_, "Enable debug.")
.def_readwrite("debug_start_node_idx",
&SLACDebugOption::debug_start_node_idx_,
"The node id to start debugging with. Smaller nodes "
"will be skipped for visualization.")
.def("__repr__", [](const SLACDebugOption &debug_option) {
return fmt::format(
"SLACDebugOption[debug={}, "
"debug_start_node_idx={:d}].",
debug_option.debug_,
debug_option.debug_start_node_idx_);
});
py::class_<ControlGrid> control_grid(
m, "control_grid",
" ControlGrid is a spatially hashed voxel grid used for non-rigid "
"point cloud registration and TSDF integration. Each grid stores a "
"map from the initial grid location to the deformed location. You "
"can imagine a control grid as a jelly that is warped upon "
"perturbation with its overall shape preserved. "
"Reference: "
"https://github.com/qianyizh/ElasticReconstruction/blob/master/"
"FragmentOptimizer/OptApp.cpp "
"http://vladlen.info/papers/elastic-fragments.pdf. ");
py::detail::bind_copy_functions<ControlGrid>(control_grid);
control_grid.def(py::init<>())
.def(py::init<float, int64_t, const core::Device>(), "grid_size"_a,
"grid_count"_a = 1000, "device"_a = core::Device("CPU:0"))
.def(py::init<float, core::Tensor, core::Tensor,
const core::Device>(),
"grid_size"_a, "keys"_a, "values"_a,
"device"_a = core::Device("CPU:0"))
.def(
"touch",
[](ControlGrid &control_grid, geometry::PointCloud &pcd) {
control_grid.Touch(pcd);
},
"Allocate control grids in the shared camera space.",
"pointcloud"_a)
.def("compactify", &ControlGrid::Compactify,
"Force rehashing, so that all entries are remapped to [0, "
"size) and form a contiguous index map.")
.def("get_neighbor_grid_map", &ControlGrid::GetNeighborGridMap,
"Get the neighbor indices per grid to construct the "
"regularizer. "
"Returns a 6-way neighbor grid map for all the active "
"entries of shape (N, ). "
"\n - buf_indices Active indices in the buffer of shape (N, ) "
"\n - buf_indices_nb Neighbor indices (including "
"non-allocated "
"entries) for the active entries of shape (N, 6). "
"\n - masks_nb Corresponding neighbor masks of shape (N, "
"6). ")
.def(
"parameterize",
[](ControlGrid &control_grid,
const geometry::PointCloud &pcd) {
return control_grid.Parameterize(pcd);
},
"Parameterize an input point cloud by embedding each point "
"in the grid "
"with 8 corners via indexing and interpolation. "
"Returns: A PointCloud with parameterization attributes: "
"\n- neighbors: Index of 8 neighbor control grid points of "
"shape (8, ) in Int64. "
"\n- ratios: Interpolation ratios of 8 neighbor control "
"grid points of shape (8, ) in Float32.",
"pointcloud"_a)
.def(
"deform",
[](ControlGrid &control_grid,
const geometry::PointCloud &pcd) {
return control_grid.Deform(pcd);
},
"Non-rigidly deform a point cloud using the control grid.",
"pointcloud"_a)
.def(
"deform",
[](ControlGrid &control_grid, const geometry::Image &depth,
const core::Tensor &intrinsics,
const core::Tensor &extrinsics, float depth_scale,
float depth_max) {
return control_grid.Deform(depth, intrinsics,
extrinsics, depth_scale,
depth_max);
},
"Non-rigidly deform a depth image by "
"\n- unprojecting the depth image to a point cloud "
"\n- deform the point cloud; "
"\n- project the deformed point cloud back to the image. ",
"depth"_a, "intrinsics"_a, "extrinsics"_a, "depth_scale"_a,
"depth_max"_a)
.def(
"deform",
[](ControlGrid &control_grid,
const geometry::RGBDImage &rgbd,
const core::Tensor &intrinsics,
const core::Tensor &extrinsics, float depth_scale,
float depth_max) {
return control_grid.Deform(rgbd, intrinsics, extrinsics,
depth_scale, depth_max);
},
"Non-rigidly deform a RGBD image by "
"\n- unprojecting the RGBD image to a point cloud "
"\n- deform the point cloud; "
"\n- project the deformed point cloud back to the image. ",
"rgbd"_a, "intrinsics"_a, "extrinsics"_a, "depth_scale"_a,
"depth_max"_a)
.def("get_init_positions", &ControlGrid::GetInitPositions,
"Get control grid original positions directly from tensor "
"keys.")
.def("get_curr_positions", &ControlGrid::GetCurrPositions,
"Get control grid shifted positions from tensor values "
"(optimized in-place)")
.def(
"get_hashmap",
[](ControlGrid &control_grid) {
return *control_grid.GetHashMap();
},
"Get the control grid hashmap.")
.def("size", &ControlGrid::Size)
.def("get_device", &ControlGrid::GetDevice)
.def("get_anchor_idx", &ControlGrid::GetAnchorIdx)
.def("__repr__", [](ControlGrid &control_grid) {
return fmt::format(
"ControlGrid[size={:d}, "
"anchor_idx={:d}].",
control_grid.Size(), control_grid.GetAnchorIdx());
});
}
// SLAC functions have similar arguments, sharing arg docstrings.
static const std::unordered_map<std::string, std::string>
map_shared_argument_docstrings = {
{"fnames_processed",
"List of filenames (str) for pre-processed pointcloud "
"fragments."},
{"fragment_filenames",
"List of filenames (str) for pointcloud fragments."},
{"fragment_pose_graph", "PoseGraph for pointcloud fragments"},
{"params",
"slac_optimizer_params Parameters to tune in optimization."},
{"debug_option", "debug options."}};
void pybind_slac_methods(py::module &m) {
m.def("save_correspondences_for_pointclouds",
&SaveCorrespondencesForPointClouds,
py::call_guard<py::gil_scoped_release>(),
"Read pose graph containing loop closures and odometry to compute "
"correspondences. Uses aggressive pruning -- reject any suspicious "
"pair.",
"fnames_processed"_a, "fragment_pose_graph"_a,
"params"_a = SLACOptimizerParams(),
"debug_option"_a = SLACDebugOption());
docstring::FunctionDocInject(m, "save_correspondences_for_pointclouds",
map_shared_argument_docstrings);
m.def("run_slac_optimizer_for_fragments", &RunSLACOptimizerForFragments,
"Simultaneous Localization and Calibration: Self-Calibration of "
"Consumer Depth Cameras, CVPR 2014 Qian-Yi Zhou and Vladlen Koltun "
"Estimate a shared control grid for all fragments for scene "
"reconstruction, implemented in "
"https://github.com/qianyizh/ElasticReconstruction. ",
"fragment_filenames"_a, "fragment_pose_graph"_a,
"params"_a = SLACOptimizerParams(),
"debug_option"_a = SLACDebugOption());
docstring::FunctionDocInject(m, "run_slac_optimizer_for_fragments",
map_shared_argument_docstrings);
m.def("run_rigid_optimizer_for_fragments", &RunRigidOptimizerForFragments,
"Extended ICP to simultaneously align multiple point clouds with "
"dense pairwise point-to-plane distances.",
"fragment_filenames"_a, "fragment_pose_graph"_a,
"params"_a = SLACOptimizerParams(),
"debug_option"_a = SLACDebugOption());
docstring::FunctionDocInject(m, "run_rigid_optimizer_for_fragments",
map_shared_argument_docstrings);
}
void pybind_slac(py::module &m) {
py::module m_submodule = m.def_submodule(
"slac",
"Tensor-based Simultaneous Localisation and Calibration pipeline.");
pybind_slac_classes(m_submodule);
pybind_slac_methods(m_submodule);
}
} // namespace slac
} // namespace pipelines
} // namespace t
} // namespace open3d
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