OpenVDB 11.0.0

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Filter.h
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1// Copyright Contributors to the OpenVDB Project
2// SPDX-License-Identifier: MPL-2.0
3//
4/// @author Ken Museth
5///
6/// @file tools/Filter.h
7///
8/// @brief Filtering of VDB volumes. All operations can optionally be masked
9/// with another grid that acts as an alpha-mask. By default, filtering
10/// operations do not modify the topology of the input tree and thus do
11/// not process active tiles. However Filter::setProcessTiles can be
12/// used to process active tiles, densifying them on demand when necessary.
13
14#ifndef OPENVDB_TOOLS_FILTER_HAS_BEEN_INCLUDED
15#define OPENVDB_TOOLS_FILTER_HAS_BEEN_INCLUDED
16
17#include <openvdb/Types.h>
18#include <openvdb/Grid.h>
19#include <openvdb/math/Math.h>
20#include <openvdb/math/Stencils.h>
21#include <openvdb/math/Transform.h>
22#include <openvdb/tree/NodeManager.h>
23#include <openvdb/tree/LeafManager.h>
24#include <openvdb/util/NullInterrupter.h>
25#include <openvdb/util/Util.h>
26#include <openvdb/thread/Threading.h>
27#include "Interpolation.h"
28
29#include <tbb/parallel_for.h>
30#include <tbb/concurrent_vector.h>
31
32#include <algorithm> // for std::max()
33#include <functional>
34#include <type_traits>
35
36 namespace openvdb {
37 OPENVDB_USE_VERSION_NAMESPACE
38 namespace OPENVDB_VERSION_NAME {
39 namespace tools {
40
41/// @brief Volume filtering (e.g., diffusion) with optional alpha masking
42 template<typename GridT,
43 typename MaskT = typename GridT::template ValueConverter<float>::Type,
44 typename InterruptT = util::NullInterrupter>
45 class Filter
46{
47 public:
48 using GridType = GridT;
49 using MaskType = MaskT;
50 using TreeType = typename GridType::TreeType;
51 using LeafType = typename TreeType::LeafNodeType;
52 using ValueType = typename GridType::ValueType;
53 using AlphaType = typename MaskType::ValueType;
54 using LeafManagerType = typename tree::LeafManager<TreeType>;
55 using RangeType = typename LeafManagerType::LeafRange;
56 using BufferType = typename LeafManagerType::BufferType;
57 static_assert(std::is_floating_point<AlphaType>::value,
58 "openvdb::tools::Filter requires a mask grid with floating-point values");
59
60 /// Constructor
61 /// @param grid Grid to be filtered.
62 /// @param interrupt Optional interrupter.
63 Filter(GridT& grid, InterruptT* interrupt = nullptr)
64 : mGrid(&grid)
65 , mTask(nullptr)
66 , mInterrupter(interrupt)
67 , mMask(nullptr)
68 , mGrainSize(1)
69 , mMinMask(0)
70 , mMaxMask(1)
71 , mInvertMask(false)
72 , mTiles(false) {}
73
74 /// @brief Shallow copy constructor called by tbb::parallel_for()
75 /// threads during filtering.
76 /// @param other The other Filter from which to copy.
77 Filter(const Filter& other)
78 : mGrid(other.mGrid)
79 , mTask(other.mTask)
80 , mInterrupter(other.mInterrupter)
81 , mMask(other.mMask)
82 , mGrainSize(other.mGrainSize)
83 , mMinMask(other.mMinMask)
84 , mMaxMask(other.mMaxMask)
85 , mInvertMask(other.mInvertMask)
86 , mTiles(other.mTiles) {}
87
88 /// @return the grain-size used for multi-threading
89 int getGrainSize() const { return mGrainSize; }
90 /// @brief Set the grain-size used for multi-threading.
91 /// @note A grain size of 0 or less disables multi-threading!
92 void setGrainSize(int grainsize) { mGrainSize = grainsize; }
93
94 /// @return whether active tiles are being processed
95 bool getProcessTiles() const { return mTiles; }
96 /// @brief Set whether active tiles should also be processed.
97 /// @note If true, some tiles may become voxelized
98 /// @warning If using with a mask, ensure that the mask topology matches the
99 /// tile topology of the filter grid as tiles will not respect overlapping
100 /// mask values at tree levels finer than themselves e.g. a leaf level tile
101 /// will only use the corresponding tile ijk value in the mask grid
102 void setProcessTiles(bool flag) { mTiles = flag; }
103
104 /// @brief Return the minimum value of the mask to be used for the
105 /// derivation of a smooth alpha value.
106 AlphaType minMask() const { return mMinMask; }
107 /// @brief Return the maximum value of the mask to be used for the
108 /// derivation of a smooth alpha value.
109 AlphaType maxMask() const { return mMaxMask; }
110 /// @brief Define the range for the (optional) scalar mask.
111 /// @param min Minimum value of the range.
112 /// @param max Maximum value of the range.
113 /// @details Mask values outside the range are clamped to zero or one, and
114 /// values inside the range map smoothly to 0->1 (unless the mask is inverted).
115 /// @throw ValueError if @a min is not smaller than @a max.
116 void setMaskRange(AlphaType min, AlphaType max)
117 {
118 if (!(min < max)) OPENVDB_THROW(ValueError, "Invalid mask range (expects min < max)");
119 mMinMask = min;
120 mMaxMask = max;
121 }
122
123 /// @brief Return true if the mask is inverted, i.e. min->max in the
124 /// original mask maps to 1->0 in the inverted alpha mask.
125 bool isMaskInverted() const { return mInvertMask; }
126 /// @brief Invert the optional mask, i.e. min->max in the original
127 /// mask maps to 1->0 in the inverted alpha mask.
128 void invertMask(bool invert=true) { mInvertMask = invert; }
129
130 /// @brief One iteration of a fast separable mean-value (i.e. box) filter.
131 /// @param width The width of the mean-value filter is 2*width+1 voxels.
132 /// @param iterations Number of times the mean-value filter is applied.
133 /// @param mask Optional alpha mask.
134 void mean(int width = 1, int iterations = 1, const MaskType* mask = nullptr);
135
136 /// @brief One iteration of a fast separable Gaussian filter.
137 ///
138 /// @note This is approximated as 4 iterations of a separable mean filter
139 /// which typically leads an approximation that's better than 95%!
140 /// @param width The width of the mean-value filter is 2*width+1 voxels.
141 /// @param iterations Number of times the mean-value filter is applied.
142 /// @param mask Optional alpha mask.
143 void gaussian(int width = 1, int iterations = 1, const MaskType* mask = nullptr);
144
145 /// @brief One iteration of a median-value filter
146 ///
147 /// @note This filter is not separable and is hence relatively slow!
148 /// @param width The width of the mean-value filter is 2*width+1 voxels.
149 /// @param iterations Number of times the mean-value filter is applied.
150 /// @param mask Optional alpha mask.
151 void median(int width = 1, int iterations = 1, const MaskType* mask = nullptr);
152
153 /// Offsets (i.e. adds) a constant value to all active voxels.
154 /// @param offset Offset in the same units as the grid.
155 /// @param mask Optional alpha mask.
156 void offset(ValueType offset, const MaskType* mask = nullptr);
157
158 /// @brief Used internally by tbb::parallel_for()
159 /// @param range Range of LeafNodes over which to multi-thread.
160 ///
161 /// @warning Never call this method directly!
162 void operator()(const RangeType& range) const
163 {
164 if (mTask) mTask(const_cast<Filter*>(this), range);
165 else OPENVDB_THROW(ValueError, "task is undefined - call median(), mean(), etc.");
166 }
167
168 private:
169 using LeafT = typename TreeType::LeafNodeType;
170 using VoxelIterT = typename LeafT::ValueOnIter;
171 using VoxelCIterT = typename LeafT::ValueOnCIter;
172 using BufferT = typename tree::LeafManager<TreeType>::BufferType;
173 using LeafIterT = typename RangeType::Iterator;
174 using AlphaMaskT = tools::AlphaMask<GridT, MaskT>;
175
176 void cook(LeafManagerType& leafs);
177
178 template<size_t Axis>
179 struct Avg {
180 Avg(const GridT* grid, Int32 w): acc(grid->tree()), width(w), frac(1.f/float(2*w+1)) {}
181 inline ValueType operator()(Coord xyz);
182 typename GridT::ConstAccessor acc;
183 const Int32 width;
184 const float frac;
185 };
186
187 // Private filter methods called by tbb::parallel_for threads
188 template <typename AvgT>
189 void doBox(const RangeType& r, Int32 w);
190 void doBoxX(const RangeType& r, Int32 w) { this->doBox<Avg<0> >(r,w); }
191 void doBoxY(const RangeType& r, Int32 w) { this->doBox<Avg<1> >(r,w); }
192 void doBoxZ(const RangeType& r, Int32 w) { this->doBox<Avg<2> >(r,w); }
193 void doMedian(const RangeType&, int);
194 void doOffset(const RangeType&, ValueType);
195 /// @return true if the process was interrupted
196 bool wasInterrupted();
197
198 GridType* mGrid;
199 typename std::function<void (Filter*, const RangeType&)> mTask;
200 InterruptT* mInterrupter;
201 const MaskType* mMask;
202 int mGrainSize;
203 AlphaType mMinMask, mMaxMask;
204 bool mInvertMask;
205 bool mTiles;
206}; // end of Filter class
207
208
209////////////////////////////////////////
210
211/// @cond OPENVDB_DOCS_INTERNAL
212
213 namespace filter_internal {
214
215 template<typename TreeT>
216 struct Voxelizer
217{
218 // NodeManager for processing internal/root node values
219 // @note Should not cache leaf nodes
220 using NodeManagerT = tree::NodeManager<TreeT, TreeT::RootNodeType::LEVEL-1>;
221 using MaskT = typename TreeT::template ValueConverter<ValueMask>::Type;
222
223 Voxelizer(TreeT& tree, const bool allNeighbors, const size_t grainSize)
224 : mVoxelTopology()
225 , mManager(nullptr)
226 , mGrainSize(grainSize)
227 , mOp(tree, mVoxelTopology, allNeighbors ? 26 : 6) {}
228
229 /// @brief Convert tiles to leaf nodes that exist at a particular
230 /// voxel distance away
231 /// @param width distance in voxels to seach for tiles from each leaf
232 /// @return Returns how many search iterations were performed, which
233 /// also represents how many leaf node neighbors may have been
234 /// created. Returns 0 if the tree is already entirely voxelized
235 int run(const int width)
236 {
237 if (!mOp.tree().hasActiveTiles()) return 0;
238 this->init();
239 int count = 0;
240 for (int i = 0; i < width; i += int(TreeT::LeafNodeType::DIM), ++count) {
241 if (i > 0) mManager->rebuild();
242 mManager->foreachBottomUp(mOp, mGrainSize > 0, mGrainSize);
243 mOp.tree().topologyUnion(mVoxelTopology);
244 }
245 return count;
246 }
247
248 private:
249 void init()
250 {
251 if (mManager) {
252 mManager->rebuild();
253 }
254 else {
255 // @note We don't actually need the leaf topology here, just the
256 // internal node structure so that we can generate leaf nodes in parallel
257 mVoxelTopology.topologyUnion(mOp.tree());
258 mManager.reset(new NodeManagerT(mOp.tree()));
259 }
260 }
261
262 struct CreateVoxelMask
263 {
264 using LeafT = typename TreeT::LeafNodeType;
265 using RootT = typename TreeT::RootNodeType;
266
267 CreateVoxelMask(TreeT& tree, MaskT& mask, const size_t NN)
268 : mTree(tree), mVoxelTopology(mask), mNeighbors(NN) {}
269
270 TreeT& tree() { return mTree; }
271
272 // do nothing for leaf nodes. They shouldn't even be cached as
273 // part of the NodeManager used with this method.
274 void operator()(const LeafT&) const { assert(false); }
275
276 void operator()(const RootT& node) const
277 {
278 using ChildT = typename RootT::ChildNodeType;
279 static constexpr Int32 CHILDDIM = Int32(ChildT::DIM);
280 static constexpr Int32 LEAFDIM = Int32(LeafT::DIM);
281 const Tester op(mTree, mNeighbors);
282
283 auto step =
284 [&](const Coord& ijk,
285 const size_t axis1,
286 const size_t axis2,
287 const auto& val)
288 {
289 Coord offset(0);
290 Int32& a = offset[axis1];
291 Int32& b = offset[axis2];
292 for (a = 0; a < CHILDDIM; a+=LEAFDIM) {
293 for (b = 0; b < CHILDDIM; b+=LEAFDIM) {
294 const Coord childijk = ijk + offset;
295 if (op.test(childijk, val)) {
296 mVoxelTopology.touchLeaf(childijk);
297 }
298 }
299 }
300
301 offset.reset(CHILDDIM-1);
302 for (a = 0; a < CHILDDIM; a+=LEAFDIM) {
303 for (b = 0; b < CHILDDIM; b+=LEAFDIM) {
304 const Coord childijk = ijk + offset;
305 if (op.test(childijk, val)) {
306 mVoxelTopology.touchLeaf(childijk);
307 }
308 }
309 }
310 };
311
312 for (auto iter = node.cbeginValueOn(); iter; ++iter) {
313 const Coord& ijk = iter.getCoord();
314 // @todo step only needs to search if a given direction
315 // depending on the face
316 step(ijk, 0, 1, *iter);
317 step(ijk, 0, 2, *iter);
318 step(ijk, 1, 2, *iter);
319 }
320 }
321
322 template<typename NodeT>
323 void operator()(const NodeT& node) const
324 {
325 using ChildT = typename NodeT::ChildNodeType;
326 static constexpr Int32 CHILDDIM = Int32(ChildT::DIM);
327 static constexpr Int32 LEAFDIM = Int32(LeafT::DIM);
328
329 static auto step =
330 [](const Tester& op,
331 const Coord& ijk,
332 const size_t axis1,
333 const size_t axis2,
334 const auto& val,
335 std::vector<Coord>& coords)
336 {
337 Coord offset(0);
338 Int32& a = offset[axis1];
339 Int32& b = offset[axis2];
340 for (a = 0; a < CHILDDIM; a+=LEAFDIM) {
341 for (b = 0; b < CHILDDIM; b+=LEAFDIM) {
342 const Coord childijk = ijk + offset;
343 if (op.test(childijk, val)) {
344 coords.emplace_back(childijk);
345 }
346 }
347 }
348
349 offset.reset(CHILDDIM-1);
350 for (a = 0; a < CHILDDIM; a+=LEAFDIM) {
351 for (b = 0; b < CHILDDIM; b+=LEAFDIM) {
352 const Coord childijk = ijk + offset;
353 if (op.test(childijk, val)) {
354 coords.emplace_back(childijk);
355 }
356 }
357 }
358 };
359
360 /// Two types of algorithms here
361 /// 1) For the case where this node is the direct parent of leaf nodes
362 /// 2) For all other node types
363 ///
364 /// In general, given a tile's ijk, search its faces/edges/corners for
365 /// values which differ from its own or leaf level topology. When a
366 /// difference is detected, mask topology is generated which can be used
367 /// with topologyUnion to ensure valid voxel values exist in the source
368 /// grid.
369 ///
370 /// This operator handles all internal node types. For example, for the
371 /// lowest level internal node (which contains leaf nodes as children)
372 /// each tile is at the leaf level (a single tile represents an 8x8x8
373 /// node). CHILDDIM is this case will match the valid of LEAFDIM, as we
374 /// only need to check each tiles immediate neighbors. For higher level
375 /// internal nodes (and the root node) each child tile will have a
376 /// significantly larger CHILDDIM than the grid's LEAFDIM. We
377 /// consistently probe values along the LEAFDIM stride to ensure no
378 /// changes are missed.
379
380 if (CHILDDIM == LEAFDIM) {
381 // If the current node is the parent of leaf nodes, search each
382 // neighbor directly and use a flag buffer to test offsets in
383 // this node which need converting to leaf level topology.
384 // This is faster than the more general method which steps across
385 // faces (unecessary due to CHILDDIM == LEAFDIM) and provides
386 // a simpler way of tracking new topology
387
388 std::vector<char> flags(NodeT::NUM_VALUES, char(0));
389 tbb::parallel_for(tbb::blocked_range<size_t>(0, NodeT::NUM_VALUES),
390 [&](const tbb::blocked_range<size_t>& range) {
391 const Tester op(mTree, mNeighbors);
392 for (size_t n = range.begin(), N = range.end(); n < N; ++n) {
393 if (node.isValueMaskOn(Index(n))) {
394 // if index is a tile, search its neighbors
395 const Coord ijk = node.offsetToGlobalCoord(Index(n));
396 flags[n] = op.test(ijk, node.getValue(ijk));
397 }
398 }
399 });
400
401 // create leaf level topology in this internal node
402 Index idx = 0;
403 for (auto iter = flags.begin(); iter != flags.end(); ++iter, ++idx) {
404 if (*iter) mVoxelTopology.touchLeaf(node.offsetToGlobalCoord(idx));
405 }
406 }
407 else {
408 // If this is a higher level internal node, we only need to search its
409 // face/edge/vertex neighbors for values which differ or leaf level
410 // topology. When a difference is detected, store the coordinate which
411 // needs to be voxelized.
412 // @todo investigate better threaded impl
413
414 tbb::concurrent_vector<Coord> nodes;
415 tbb::parallel_for(tbb::blocked_range<size_t>(0, NodeT::NUM_VALUES),
416 [&](const tbb::blocked_range<size_t>& range)
417 {
418 const Tester op(mTree, mNeighbors);
419 std::vector<Coord> coords;
420
421 for (size_t n = range.begin(), N = range.end(); n < N; ++n) {
422 if (!node.isValueMaskOn(Index(n))) continue;
423
424 const Coord ijk = node.offsetToGlobalCoord(Index(n));
425 const auto& val = node.getValue(ijk);
426 // @todo step only needs to search if a given direction
427 // depending on the face
428 step(op, ijk, 0, 1, val, coords);
429 step(op, ijk, 0, 2, val, coords);
430 step(op, ijk, 1, 2, val, coords);
431 }
432
433 if (!coords.empty()) {
434 std::copy(coords.begin(), coords.end(),
435 nodes.grow_by(coords.size()));
436 }
437 });
438
439 // create leaf level topology in this internal node
440 // @note nodes may contain duplicate coords
441 for (const auto& coord : nodes) {
442 mVoxelTopology.touchLeaf(coord);
443 }
444 }
445 }
446
447 private:
448 struct Tester
449 {
450 Tester(const TreeT& tree, const size_t NN)
451 : mAcc(tree), mNeighbors(NN) {}
452
453 inline bool test(const Coord& ijk,
454 const typename TreeT::ValueType& val) const
455 {
456 static constexpr Int32 LEAFDIM = Int32(LeafT::DIM);
457 const Coord* NN = util::COORD_OFFSETS;
458 for (size_t i = 0; i < mNeighbors; ++i, ++NN) {
459 Coord neighbor(*NN);
460 neighbor.x() *= LEAFDIM;
461 neighbor.y() *= LEAFDIM;
462 neighbor.z() *= LEAFDIM;
463 neighbor += ijk;
464 // if a leaf exists, assume its buffer is not constant
465 if (mAcc.getValue(neighbor) != val ||
466 mAcc.probeConstLeaf(neighbor)) {
467 return true;
468 }
469 }
470 return false;
471 }
472 private:
473 const tree::ValueAccessor<const TreeT> mAcc;
474 const size_t mNeighbors;
475 };
476
477 private:
478 TreeT& mTree;
479 MaskT& mVoxelTopology;
480 const size_t mNeighbors;
481 };// CreateVoxelMask
482
483 private:
484 MaskT mVoxelTopology;
485 std::unique_ptr<NodeManagerT> mManager;
486 const size_t mGrainSize;
487 CreateVoxelMask mOp;
488};
489
490// Helper function for Filter::Avg::operator()
491 template<typename T> static inline void accum(T& sum, T addend) { sum += addend; }
492// Overload for bool ValueType
493 inline void accum(bool& sum, bool addend) { sum = sum || addend; }
494
495} // namespace filter_internal
496
497/// @endcond
498
499////////////////////////////////////////
500
501
502 template<typename GridT, typename MaskT, typename InterruptT>
503 template<size_t Axis>
504 inline typename GridT::ValueType
505Filter<GridT, MaskT, InterruptT>::Avg<Axis>::operator()(Coord xyz)
506{
507 ValueType sum = zeroVal<ValueType>();
508 Int32 &i = xyz[Axis], j = i + width;
509 for (i -= width; i <= j; ++i) filter_internal::accum(sum, acc.getValue(xyz));
510 if constexpr(std::is_same<ValueType, bool>::value) {
511 return sum && frac > 0.0f;
512 } else {
513 OPENVDB_NO_TYPE_CONVERSION_WARNING_BEGIN
514 ValueType value = static_cast<ValueType>(sum * frac);
515 OPENVDB_NO_TYPE_CONVERSION_WARNING_END
516 return value;
517 }
518}
519
520
521////////////////////////////////////////
522
523
524 template<typename GridT, typename MaskT, typename InterruptT>
525 void
526 Filter<GridT, MaskT, InterruptT>::mean(int width, int iterations, const MaskType* mask)
527{
528 if (iterations <= 0) return;
529 mMask = mask;
530 const int w = std::max(1, width);
531 const bool serial = mGrainSize == 0;
532
533 if (mInterrupter) mInterrupter->start("Applying mean filter");
534
535 std::unique_ptr<filter_internal::Voxelizer<TreeType>> voxelizer;
536 if (this->getProcessTiles()) {
537 // if performing multiple iterations, also search edge/vertex
538 // neighbors for difference topology.
539 const bool allNeighbors = iterations > 1;
540 // If processing tiles, create a voxelizer and run a single
541 // width based search for tiles that need to be voxelized
542 voxelizer.reset(new filter_internal::Voxelizer<TreeType>
543 (mGrid->tree(), allNeighbors, mGrainSize));
544 if (!voxelizer->run(w)) voxelizer.reset();
545 }
546
547 LeafManagerType leafs(mGrid->tree(), 1, serial);
548
549 int iter = 1; // num of leaf level neighbor based searches performed
550 int dist = w; // kernel distance of the current iteration
551 for (int i=0; i<iterations && !this->wasInterrupted(); ++i, dist+=w) {
552 if (i > 0 && voxelizer) {
553 // the total influence distance in voxels of this iteration
554 // minus how far we've already accounted for
555 const int remain = dist - iter * int(TreeType::LeafNodeType::DIM);
556 if (remain > 0) {
557 const int searches = voxelizer->run(remain);
558 if (searches == 0) voxelizer.reset();
559 else leafs.rebuild(serial);
560 iter += searches;
561 }
562 }
563
564 mTask = std::bind(&Filter::doBoxX, std::placeholders::_1, std::placeholders::_2, w);
565 this->cook(leafs);
566 // note that the order of the YZ passes are flipped to maintain backwards-compatibility
567 // with an indexing typo in the original logic
568 mTask = std::bind(&Filter::doBoxZ, std::placeholders::_1, std::placeholders::_2, w);
569 this->cook(leafs);
570 mTask = std::bind(&Filter::doBoxY, std::placeholders::_1, std::placeholders::_2, w);
571 this->cook(leafs);
572 }
573
574 if (mInterrupter) mInterrupter->end();
575}
576
577
578 template<typename GridT, typename MaskT, typename InterruptT>
579 void
580 Filter<GridT, MaskT, InterruptT>::gaussian(int width, int iterations, const MaskType* mask)
581{
582 if (iterations <= 0) return;
583 mMask = mask;
584 const int w = std::max(1, width);
585 const bool serial = mGrainSize == 0;
586
587 if (mInterrupter) mInterrupter->start("Applying Gaussian filter");
588
589 std::unique_ptr<filter_internal::Voxelizer<TreeType>> voxelizer;
590 if (this->getProcessTiles()) {
591 // if performing multiple iterations, also search edge/vertex
592 // neighbors for difference topology.
593 const bool allNeighbors = iterations > 1;
594 // If processing tiles, create a voxelizer and run a single
595 // width based search for tiles that need to be voxelized
596 // @note account for sub iteration due to gaussian filter
597 voxelizer.reset(new filter_internal::Voxelizer<TreeType>
598 (mGrid->tree(), allNeighbors, mGrainSize));
599 if (!voxelizer->run(w*4)) voxelizer.reset();
600 }
601
602 LeafManagerType leafs(mGrid->tree(), 1, serial);
603
604 int iter = 1; // num of leaf level neighbor based searches performed
605 int dist = w*4; // kernel distance of the current iteration
606 for (int i=0; i<iterations; ++i, dist+=(w*4)) {
607 if (i > 0 && voxelizer) {
608 // the total influence distance in voxels of this iteration
609 // minus how far we've already accounted for
610 const int remain = dist - iter * int(TreeType::LeafNodeType::DIM);
611 if (remain > 0) {
612 const int searches = voxelizer->run(remain);
613 if (searches == 0) voxelizer.reset();
614 else leafs.rebuild(serial);
615 iter += searches;
616 }
617 }
618
619 for (int n=0; n<4 && !this->wasInterrupted(); ++n) {
620 mTask = std::bind(&Filter::doBoxX, std::placeholders::_1, std::placeholders::_2, w);
621 this->cook(leafs);
622 // note that the order of the YZ passes are flipped to maintain backwards-compatibility
623 // with an indexing typo in the original logic
624 mTask = std::bind(&Filter::doBoxZ, std::placeholders::_1, std::placeholders::_2, w);
625 this->cook(leafs);
626 mTask = std::bind(&Filter::doBoxY, std::placeholders::_1, std::placeholders::_2, w);
627 this->cook(leafs);
628 }
629 }
630
631 if (mInterrupter) mInterrupter->end();
632}
633
634
635 template<typename GridT, typename MaskT, typename InterruptT>
636 void
637 Filter<GridT, MaskT, InterruptT>::median(int width, int iterations, const MaskType* mask)
638{
639 if (iterations <= 0) return;
640 mMask = mask;
641 const int w = std::max(1, width);
642 const bool serial = mGrainSize == 0;
643
644 if (mInterrupter) mInterrupter->start("Applying median filter");
645
646 std::unique_ptr<filter_internal::Voxelizer<TreeType>> voxelizer;
647 if (this->getProcessTiles()) {
648 // If processing tiles, create a voxelizer and run a single
649 // width based search for tiles that need to be voxelized
650 voxelizer.reset(new filter_internal::Voxelizer<TreeType>
651 (mGrid->tree(), /*allNeighbors*/true, mGrainSize));
652 if (!voxelizer->run(w)) voxelizer.reset();
653 }
654
655 LeafManagerType leafs(mGrid->tree(), 1, serial);
656
657 mTask = std::bind(&Filter::doMedian, std::placeholders::_1, std::placeholders::_2, w);
658
659 int iter = 1; // num of leaf level neighbor based searches performed
660 int dist = w; // kernel distance of the current iteration
661 for (int i=0; i<iterations && !this->wasInterrupted(); ++i, dist+=w) {
662 if (i > 0 && voxelizer) {
663 // the total influence distance in voxels of this iteration
664 // minus how far we've already accounted for
665 const int remain = dist - iter * int(TreeType::LeafNodeType::DIM);
666 if (remain > 0) {
667 const int searches = voxelizer->run(remain);
668 if (searches == 0) voxelizer.reset();
669 else leafs.rebuild(serial);
670 iter += searches;
671 }
672 }
673
674 this->cook(leafs);
675 }
676
677 if (mInterrupter) mInterrupter->end();
678}
679
680
681 template<typename GridT, typename MaskT, typename InterruptT>
682 void
683 Filter<GridT, MaskT, InterruptT>::offset(ValueType value, const MaskType* mask)
684{
685 mMask = mask;
686
687 if (mInterrupter) mInterrupter->start("Applying offset");
688
689 if (this->getProcessTiles()) {
690 // Don't process leaf nodes with the node manager - we'll do them
691 // separately to allow for cleaner branching
692 using NodeManagerT = tree::NodeManager<TreeType, TreeType::RootNodeType::LEVEL-1>;
693 NodeManagerT manager(mGrid->tree());
694
695 if (mask) {
696 manager.foreachBottomUp([&](auto& node) {
697 this->wasInterrupted();
698 AlphaMaskT alpha(*mGrid, *mMask, mMinMask, mMaxMask, mInvertMask);
699 typename AlphaMaskT::FloatType a, b;
700 for (auto iter = node.beginValueOn(); iter; ++iter) {
701 if (!alpha(iter.getCoord(), a, b)) continue;
702 OPENVDB_NO_TYPE_CONVERSION_WARNING_BEGIN
703 iter.modifyValue([&](ValueType& v) { v += a*value; });
704 OPENVDB_NO_TYPE_CONVERSION_WARNING_END
705 }
706 });
707 }
708 else {
709 manager.foreachBottomUp([&](auto& node) {
710 this->wasInterrupted();
711 for (auto iter = node.beginValueOn(); iter; ++iter) {
712 iter.modifyValue([&](ValueType& v) { v += value; });
713 }
714 });
715 }
716 }
717
718 LeafManagerType leafs(mGrid->tree(), 0, mGrainSize==0);
719 mTask = std::bind(&Filter::doOffset, std::placeholders::_1, std::placeholders::_2, value);
720 this->cook(leafs);
721
722 if (mInterrupter) mInterrupter->end();
723}
724
725
726////////////////////////////////////////
727
728
729/// Private method to perform the task (serial or threaded) and
730/// subsequently swap the leaf buffers.
731 template<typename GridT, typename MaskT, typename InterruptT>
732 void
733Filter<GridT, MaskT, InterruptT>::cook(LeafManagerType& leafs)
734{
735 if (mGrainSize>0) {
736 tbb::parallel_for(leafs.leafRange(mGrainSize), *this);
737 } else {
738 (*this)(leafs.leafRange());
739 }
740 leafs.swapLeafBuffer(1, mGrainSize==0);
741}
742
743
744/// One dimensional convolution of a separable box filter
745 template<typename GridT, typename MaskT, typename InterruptT>
746 template <typename AvgT>
747 void
748Filter<GridT, MaskT, InterruptT>::doBox(const RangeType& range, Int32 w)
749{
750 this->wasInterrupted();
751 AvgT avg(mGrid, w);
752 if (mMask) {
753 typename AlphaMaskT::FloatType a, b;
754 AlphaMaskT alpha(*mGrid, *mMask, mMinMask, mMaxMask, mInvertMask);
755 for (LeafIterT leafIter=range.begin(); leafIter; ++leafIter) {
756 BufferT& buffer = leafIter.buffer(1);
757 for (VoxelCIterT iter = leafIter->cbeginValueOn(); iter; ++iter) {
758 const Coord xyz = iter.getCoord();
759 if (alpha(xyz, a, b)) {
760 OPENVDB_NO_TYPE_CONVERSION_WARNING_BEGIN
761 const ValueType value(b*(*iter) + a*avg(xyz));
762 OPENVDB_NO_TYPE_CONVERSION_WARNING_END
763 buffer.setValue(iter.pos(), value);
764 }
765 }
766 }
767 } else {
768 for (LeafIterT leafIter=range.begin(); leafIter; ++leafIter) {
769 BufferT& buffer = leafIter.buffer(1);
770 for (VoxelCIterT iter = leafIter->cbeginValueOn(); iter; ++iter) {
771 buffer.setValue(iter.pos(), avg(iter.getCoord()));
772 }
773 }
774 }
775}
776
777
778/// Performs simple but slow median-value diffusion
779 template<typename GridT, typename MaskT, typename InterruptT>
780 void
781Filter<GridT, MaskT, InterruptT>::doMedian(const RangeType& range, int width)
782{
783 this->wasInterrupted();
784 typename math::DenseStencil<GridType> stencil(*mGrid, width);//creates local cache!
785 if (mMask) {
786 typename AlphaMaskT::FloatType a, b;
787 AlphaMaskT alpha(*mGrid, *mMask, mMinMask, mMaxMask, mInvertMask);
788 for (LeafIterT leafIter=range.begin(); leafIter; ++leafIter) {
789 BufferT& buffer = leafIter.buffer(1);
790 for (VoxelCIterT iter = leafIter->cbeginValueOn(); iter; ++iter) {
791 if (alpha(iter.getCoord(), a, b)) {
792 stencil.moveTo(iter);
793 OPENVDB_NO_TYPE_CONVERSION_WARNING_BEGIN
794 ValueType value(b*(*iter) + a*stencil.median());
795 OPENVDB_NO_TYPE_CONVERSION_WARNING_END
796 buffer.setValue(iter.pos(), value);
797 }
798 }
799 }
800 } else {
801 for (LeafIterT leafIter=range.begin(); leafIter; ++leafIter) {
802 BufferT& buffer = leafIter.buffer(1);
803 for (VoxelCIterT iter = leafIter->cbeginValueOn(); iter; ++iter) {
804 stencil.moveTo(iter);
805 buffer.setValue(iter.pos(), stencil.median());
806 }
807 }
808 }
809}
810
811
812/// Offsets the values by a constant
813 template<typename GridT, typename MaskT, typename InterruptT>
814 void
815Filter<GridT, MaskT, InterruptT>::doOffset(const RangeType& range, ValueType offset)
816{
817 this->wasInterrupted();
818 if (mMask) {
819 typename AlphaMaskT::FloatType a, b;
820 AlphaMaskT alpha(*mGrid, *mMask, mMinMask, mMaxMask, mInvertMask);
821 for (LeafIterT leafIter=range.begin(); leafIter; ++leafIter) {
822 for (VoxelIterT iter = leafIter->beginValueOn(); iter; ++iter) {
823 if (alpha(iter.getCoord(), a, b)) {
824 OPENVDB_NO_TYPE_CONVERSION_WARNING_BEGIN
825 ValueType value(*iter + a*offset);
826 OPENVDB_NO_TYPE_CONVERSION_WARNING_END
827 iter.setValue(value);
828 }
829 }
830 }
831 } else {
832 for (LeafIterT leafIter=range.begin(); leafIter; ++leafIter) {
833 for (VoxelIterT iter = leafIter->beginValueOn(); iter; ++iter) {
834 iter.setValue(*iter + offset);
835 }
836 }
837 }
838}
839
840
841 template<typename GridT, typename MaskT, typename InterruptT>
842 inline bool
843Filter<GridT, MaskT, InterruptT>::wasInterrupted()
844{
845 if (util::wasInterrupted(mInterrupter)) {
846 thread::cancelGroupExecution();
847 return true;
848 }
849 return false;
850}
851
852
853////////////////////////////////////////
854
855
856// Explicit Template Instantiation
857
858#ifdef OPENVDB_USE_EXPLICIT_INSTANTIATION
859
860#ifdef OPENVDB_INSTANTIATE_FILTER
861#include <openvdb/util/ExplicitInstantiation.h>
862#endif
863
864 OPENVDB_INSTANTIATE_CLASS Filter<FloatGrid, FloatGrid, util::NullInterrupter>;
865 OPENVDB_INSTANTIATE_CLASS Filter<DoubleGrid, FloatGrid, util::NullInterrupter>;
866
867#endif // OPENVDB_USE_EXPLICIT_INSTANTIATION
868
869
870} // namespace tools
871} // namespace OPENVDB_VERSION_NAME
872} // namespace openvdb
873
874#endif // OPENVDB_TOOLS_FILTER_HAS_BEEN_INCLUDED
OPENVDB_THROW
#define OPENVDB_THROW(exception, message)
Definition Exceptions.h:74
ExplicitInstantiation.h
Grid.h
Interpolation.h
LeafManager.h
A LeafManager manages a linear array of pointers to a given tree's leaf nodes, as well as optional au...
Math.h
General-purpose arithmetic and comparison routines, most of which accept arbitrary value types (or at...
NullInterrupter.h
OPENVDB_NO_TYPE_CONVERSION_WARNING_BEGIN
#define OPENVDB_NO_TYPE_CONVERSION_WARNING_BEGIN
Bracket code with OPENVDB_NO_TYPE_CONVERSION_WARNING_BEGIN/_END, to inhibit warnings about type conve...
Definition Platform.h:227
OPENVDB_NO_TYPE_CONVERSION_WARNING_END
#define OPENVDB_NO_TYPE_CONVERSION_WARNING_END
Definition Platform.h:228
Transform.h
Types.h
Util.h
openvdb::v11_0::ValueError
Definition Exceptions.h:65
openvdb::v11_0::math::Coord
Signed (x, y, z) 32-bit integer coordinates.
Definition Coord.h:25
openvdb::v11_0::tools::AlphaMask
Definition Interpolation.h:544
openvdb::v11_0::tools::AlphaMask::FloatType
FloatT FloatType
Definition Interpolation.h:551
openvdb::v11_0::tools::Filter::getProcessTiles
bool getProcessTiles() const
Definition Filter.h:95
openvdb::v11_0::tools::Filter::AlphaType
typename MaskType::ValueType AlphaType
Definition Filter.h:53
openvdb::v11_0::tools::Filter::gaussian
void gaussian(int width=1, int iterations=1, const MaskType *mask=nullptr)
One iteration of a fast separable Gaussian filter.
Definition Filter.h:580
openvdb::v11_0::tools::Filter::LeafManagerType
typename tree::LeafManager< TreeType > LeafManagerType
Definition Filter.h:54
openvdb::v11_0::tools::Filter::minMask
AlphaType minMask() const
Return the minimum value of the mask to be used for the derivation of a smooth alpha value.
Definition Filter.h:106
openvdb::v11_0::tools::Filter::setProcessTiles
void setProcessTiles(bool flag)
Set whether active tiles should also be processed.
Definition Filter.h:102
openvdb::v11_0::tools::Filter::setGrainSize
void setGrainSize(int grainsize)
Set the grain-size used for multi-threading.
Definition Filter.h:92
openvdb::v11_0::tools::Filter::median
void median(int width=1, int iterations=1, const MaskType *mask=nullptr)
One iteration of a median-value filter.
Definition Filter.h:637
openvdb::v11_0::tools::Filter::invertMask
void invertMask(bool invert=true)
Invert the optional mask, i.e. min->max in the original mask maps to 1->0 in the inverted alpha mask.
Definition Filter.h:128
openvdb::v11_0::tools::Filter::mean
void mean(int width=1, int iterations=1, const MaskType *mask=nullptr)
One iteration of a fast separable mean-value (i.e. box) filter.
Definition Filter.h:526
openvdb::v11_0::tools::Filter::getGrainSize
int getGrainSize() const
Definition Filter.h:89
openvdb::v11_0::tools::Filter::ValueType
typename GridType::ValueType ValueType
Definition Filter.h:52
openvdb::v11_0::tools::Filter::TreeType
typename GridType::TreeType TreeType
Definition Filter.h:50
openvdb::v11_0::tools::Filter::setMaskRange
void setMaskRange(AlphaType min, AlphaType max)
Define the range for the (optional) scalar mask.
Definition Filter.h:116
openvdb::v11_0::tools::Filter::maxMask
AlphaType maxMask() const
Return the maximum value of the mask to be used for the derivation of a smooth alpha value.
Definition Filter.h:109
openvdb::v11_0::tools::Filter::Filter
Filter(const Filter &other)
Shallow copy constructor called by tbb::parallel_for() threads during filtering.
Definition Filter.h:77
openvdb::v11_0::tools::Filter::operator()
void operator()(const RangeType &range) const
Used internally by tbb::parallel_for()
Definition Filter.h:162
openvdb::v11_0::tools::Filter::RangeType
typename LeafManagerType::LeafRange RangeType
Definition Filter.h:55
openvdb::v11_0::tools::Filter::BufferType
typename LeafManagerType::BufferType BufferType
Definition Filter.h:56
openvdb::v11_0::tools::Filter::offset
void offset(ValueType offset, const MaskType *mask=nullptr)
Definition Filter.h:683
openvdb::v11_0::tools::Filter::MaskType
MaskT MaskType
Definition Filter.h:49
openvdb::v11_0::tools::Filter::LeafType
typename TreeType::LeafNodeType LeafType
Definition Filter.h:51
openvdb::v11_0::tools::Filter::isMaskInverted
bool isMaskInverted() const
Return true if the mask is inverted, i.e. min->max in the original mask maps to 1->0 in the inverted ...
Definition Filter.h:125
openvdb::v11_0::tools::Filter::GridType
GridT GridType
Definition Filter.h:48
openvdb::v11_0::tools::Filter::Filter
Filter(GridT &grid, InterruptT *interrupt=nullptr)
Definition Filter.h:63
openvdb::v11_0::tree::LeafManager
This class manages a linear array of pointers to a given tree's leaf nodes, as well as optional auxil...
Definition LeafManager.h:85
openvdb::v11_0::tree::LeafManager::BufferType
typename CopyConstness< TreeType, NonConstBufferType >::Type BufferType
Definition LeafManager.h:95
openvdb::v11_0::tree::NodeManager
To facilitate threading over the nodes of a tree, cache node pointers in linear arrays,...
Definition NodeManager.h:531
nanovdb::GridType
GridType
List of types that are currently supported by NanoVDB.
Definition NanoVDB.h:317
openvdb::v11_0::math::Axis
Axis
Definition Math.h:901
openvdb::v11_0::tree
Definition PointDataGrid.h:169
openvdb::v11_0::util::wasInterrupted
bool wasInterrupted(T *i, int percent=-1)
Definition NullInterrupter.h:49
openvdb::v11_0::Index
Index32 Index
Definition Types.h:54
openvdb::v11_0::Int32
int32_t Int32
Definition Types.h:56
openvdb
Definition Exceptions.h:13
Stencils.h
Defines various finite difference stencils by means of the "curiously recurring template pattern" on ...
NodeManager.h
NodeManager produces linear arrays of all tree nodes allowing for efficient threading and bottom-up p...
OPENVDB_VERSION_NAME
#define OPENVDB_VERSION_NAME
The version namespace name for this library version.
Definition version.h.in:121
OPENVDB_USE_VERSION_NAMESPACE
#define OPENVDB_USE_VERSION_NAMESPACE
Definition version.h.in:212
OPENVDB_INSTANTIATE_CLASS
#define OPENVDB_INSTANTIATE_CLASS
Definition version.h.in:153