206 lines
7.1 KiB
C++
206 lines
7.1 KiB
C++
/* SPDX-FileCopyrightText: 2024 Blender Authors
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*
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* SPDX-License-Identifier: GPL-2.0-or-later */
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#include "BKE_attribute_math.hh"
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#include "BLI_array.hh"
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#include "BLI_generic_span.hh"
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#include "BLI_index_mask.hh"
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#include "BLI_index_range.hh"
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#include "BLI_vector.hh"
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#include "BLI_virtual_array.hh"
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#include "GEO_smooth_curves.hh"
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namespace blender::geometry {
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template<typename T>
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static void gaussian_blur_1D(const Span<T> src,
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const int iterations,
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const float influence,
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const bool smooth_ends,
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const bool keep_shape,
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const bool is_cyclic,
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MutableSpan<T> dst)
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{
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/**
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* 1D Gaussian-like smoothing function.
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*
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* NOTE: This is the algorithm used by #BKE_gpencil_stroke_smooth_point (legacy),
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* but generalized and written in C++.
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*
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* This function uses a binomial kernel, which is the discrete version of gaussian blur.
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* The weight for a value at the relative index is:
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* `w = nCr(n, j + n/2) / 2^n = (n/1 * (n-1)/2 * ... * (n-j-n/2)/(j+n/2)) / 2^n`.
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* All weights together sum up to 1.
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* This is equivalent to doing multiple iterations of averaging neighbors,
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* where: `n = iterations * 2 and -n/2 <= j <= n/2`.
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*
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* Now the problem is that `nCr(n, j + n/2)` is very hard to compute for `n > 500`, since even
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* double precision isn't sufficient. A very good robust approximation for `n > 20` is:
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* `nCr(n, j + n/2) / 2^n = sqrt(2/(pi*n)) * exp(-2*j*j/n)`.
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*
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* `keep_shape` is a new option to stop the points from severely deforming.
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* It uses different partially negative weights.
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* `w = 2 * (nCr(n, j + n/2) / 2^n) - (nCr(3*n, j + n) / 2^(3*n))`
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* ` ~ 2 * sqrt(2/(pi*n)) * exp(-2*j*j/n) - sqrt(2/(pi*3*n)) * exp(-2*j*j/(3*n))`
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* All weights still sum up to 1.
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* Note that these weights only work because the averaging is done in relative coordinates.
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*/
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BLI_assert(!src.is_empty());
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BLI_assert(src.size() == dst.size());
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/* Avoid computation if the there is just one point. */
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if (src.size() == 1) {
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return;
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}
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/* Weight Initialization. */
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const int n_half = keep_shape ? (iterations * iterations) / 8 + iterations :
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(iterations * iterations) / 4 + 2 * iterations + 12;
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double w = keep_shape ? 2.0 : 1.0;
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double w2 = keep_shape ?
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(1.0 / M_SQRT3) * exp((2 * iterations * iterations) / double(n_half * 3)) :
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0.0;
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Array<double> total_weight(src.size(), 0.0);
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const int64_t total_points = src.size();
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const int64_t last_pt = total_points - 1;
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auto is_end_and_fixed = [smooth_ends, is_cyclic, last_pt](int index) {
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return !smooth_ends && !is_cyclic && ELEM(index, 0, last_pt);
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};
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/* Initialize at zero. */
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threading::parallel_for(dst.index_range(), 1024, [&](const IndexRange range) {
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for (const int64_t index : range) {
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if (!is_end_and_fixed(index)) {
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dst[index] = T(0);
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}
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}
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});
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/* Compute weights. */
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for (const int64_t step : IndexRange(iterations)) {
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const int64_t offset = iterations - step;
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threading::parallel_for(dst.index_range(), 1024, [&](const IndexRange range) {
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for (const int64_t index : range) {
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/* Filter out endpoints. */
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if (is_end_and_fixed(index)) {
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continue;
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}
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double w_before = w - w2;
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double w_after = w - w2;
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/* Compute the neighboring points. */
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int64_t before = index - offset;
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int64_t after = index + offset;
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if (is_cyclic) {
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before = (before % total_points + total_points) % total_points;
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after = after % total_points;
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}
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else {
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if (!smooth_ends && (before < 0)) {
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w_before *= -before / float(index);
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}
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before = math::max(before, int64_t(0));
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if (!smooth_ends && (after > last_pt)) {
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w_after *= (after - (total_points - 1)) / float(total_points - 1 - index);
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}
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after = math::min(after, last_pt);
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}
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/* Add the neighboring values. */
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const T bval = src[before];
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const T aval = src[after];
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const T cval = src[index];
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dst[index] += (bval - cval) * w_before;
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dst[index] += (aval - cval) * w_after;
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/* Update the weight values. */
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total_weight[index] += w_before;
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total_weight[index] += w_after;
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}
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});
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w *= (n_half + offset) / double(n_half + 1 - offset);
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w2 *= (n_half * 3 + offset) / double(n_half * 3 + 1 - offset);
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}
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/* Normalize the weights. */
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threading::parallel_for(dst.index_range(), 1024, [&](const IndexRange range) {
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for (const int64_t index : range) {
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if (!is_end_and_fixed(index)) {
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total_weight[index] += w - w2;
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dst[index] = src[index] + influence * dst[index] / total_weight[index];
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}
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}
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});
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}
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void gaussian_blur_1D(const GSpan src,
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const int iterations,
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const float influence,
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const bool smooth_ends,
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const bool keep_shape,
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const bool is_cyclic,
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GMutableSpan dst)
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{
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bke::attribute_math::convert_to_static_type(src.type(), [&](auto dummy) {
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using T = decltype(dummy);
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/* Only allow smoothing of float, float2, or float3. */
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/* Reduces unnecessary code generation. */
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if constexpr (std::is_same_v<T, float> || std::is_same_v<T, float2> ||
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std::is_same_v<T, float3>)
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{
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gaussian_blur_1D(src.typed<T>(),
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iterations,
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influence,
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smooth_ends,
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keep_shape,
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is_cyclic,
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dst.typed<T>());
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}
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});
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}
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void smooth_curve_attribute(const IndexMask &curves_to_smooth,
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const OffsetIndices<int> points_by_curve,
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const VArray<bool> &point_selection,
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const VArray<bool> &cyclic,
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const int iterations,
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const float influence,
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const bool smooth_ends,
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const bool keep_shape,
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GMutableSpan attribute_data)
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{
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curves_to_smooth.foreach_index(GrainSize(512), [&](const int curve_i) {
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Vector<std::byte> orig_data;
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const IndexRange points = points_by_curve[curve_i];
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IndexMaskMemory memory;
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const IndexMask selection_mask = IndexMask::from_bools(points, point_selection, memory);
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if (selection_mask.is_empty()) {
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return;
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}
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selection_mask.foreach_range([&](const IndexRange range) {
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GMutableSpan dst_data = attribute_data.slice(range);
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orig_data.resize(dst_data.size_in_bytes());
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dst_data.type().copy_assign_n(dst_data.data(), orig_data.data(), range.size());
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const GSpan src_data(dst_data.type(), orig_data.data(), range.size());
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gaussian_blur_1D(
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src_data, iterations, influence, smooth_ends, keep_shape, cyclic[curve_i], dst_data);
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});
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});
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}
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} // namespace blender::geometry
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