griefith/test
1
0
Fork 0
Code Issues Pull Requests Actions 1 Packages Projects Releases Wiki Activity

Revert "Fix #78916: unpredictable results with merge by distance"

Browse Source 
This reverts commit 69e27b4855.

Own oversight in the approach since this modified vertices from a
bmesh operator intended to "find" duplicates.
This commit is contained in:
Campbell Barton
2025-09-19 16:22:35 +10:00
parent 69e27b4855
commit 20bea06f4a
3 changed files with 1 additions and 121 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
source/blender/blenlib/BLI_kdtree_impl.h
View File

@@ -68,18 +68,6 @@ int BLI_kdtree_nd_(calc_duplicates_fast)(const KDTree *tree,
bool use_index_order,
int *duplicates);
/**
* Stable clustering and centroid computation to ensure consistent survivor selection.
*
* \param tree: A tree, all indices *must* be unique.
*
* \note ~1.1x-1.5x slower than `calc_duplicates_fast` depending on the distribution of points.
*/
int BLI_kdtree_nd_(calc_duplicates_and_center)(const KDTree *tree,
const float range,
int *duplicates,
float (*r_cluster_center)[KD_DIMS]);
int BLI_kdtree_nd_(deduplicate)(KDTree *tree);
/** Versions of find/range search that take a squared distance callback to support bias. */

93
source/blender/blenlib/intern/kdtree_impl.h
View File

@@ -8,8 +8,6 @@
#include "MEM_guardedalloc.h"
#include "BLI_array.hh"
#include "BLI_bit_vector.hh"
#include "BLI_kdtree_impl.h"
#include "BLI_math_base.h"
#include "BLI_utildefines.h"
@@ -68,20 +66,6 @@ struct KDTree {
/** \name Local Math API
* \{ */
static void add_vn_vn(float v0[KD_DIMS], const float v1[KD_DIMS])
{
for (uint j = 0; j < KD_DIMS; j++) {
v0[j] += v1[j];
}
}
static void div_vn_fl(float v[KD_DIMS], const float f)
{
for (uint j = 0; j < KD_DIMS; j++) {
v[j] /= f;
}
}
static void copy_vn_vn(float v0[KD_DIMS], const float v1[KD_DIMS])
{
for (uint j = 0; j < KD_DIMS; j++) {
@@ -950,83 +934,6 @@ int BLI_kdtree_nd_(calc_duplicates_fast)(const KDTree *tree,
/** \} */
/* -------------------------------------------------------------------- */
/** \name BLI_kdtree_3d_calc_duplicates_and_center
* \{ */
int BLI_kdtree_nd_(calc_duplicates_and_center)(const KDTree *tree,
const float range,
int *duplicates,
float (*r_cluster_center)[KD_DIMS])
{
BLI_assert(tree->is_balanced);
if (UNLIKELY(tree->root == KD_NODE_UNSET)) {
return 0;
}
const uint nodes_len = tree->nodes_len;
blender::Array<int> index_to_node_index(tree->max_node_index + 1);
for (uint i = 0; i < nodes_len; i++) {
index_to_node_index[tree->nodes[i].index] = int(i);
}
blender::BitVector<> visited(tree->max_node_index + 1, false);
/* Could be inline, declare here to avoid re-allocation. */
blender::Vector<int> cluster;
int found = 0;
for (uint i = 0; i < nodes_len; i++) {
const int node_index = tree->nodes[i].index;
if ((duplicates[node_index] != -1) || visited[node_index]) {
continue;
}
const float *search_co = tree->nodes[index_to_node_index[node_index]].co;
BLI_assert(search_co != nullptr);
BLI_assert(cluster.is_empty());
visited[node_index].set();
auto accumulate_neighbors_fn = [&duplicates, &visited, &cluster](int neighbor_index,
const float * /*co*/,
float /*dist_sq*/) -> bool {
if ((duplicates[neighbor_index] == -1) && !visited[neighbor_index]) {
cluster.append(neighbor_index);
visited[neighbor_index].set();
}
return true;
};
BLI_kdtree_nd_(range_search_cb_cpp)(tree, search_co, range, accumulate_neighbors_fn);
if (cluster.is_empty()) {
continue;
}
cluster.append(node_index);
/* Compute centroid and choose survivor in one pass. */
float centroid[KD_DIMS] = {};
int survivor_index = node_index; /* Same as `cluster[0]`. */
for (int cluster_node_index : cluster) {
add_vn_vn(centroid, tree->nodes[index_to_node_index[cluster_node_index]].co);
survivor_index = std::min(cluster_node_index, survivor_index);
}
div_vn_fl(centroid, float(cluster.size()));
copy_vn_vn(r_cluster_center[survivor_index], centroid);
for (int cluster_node_index : cluster) {
duplicates[cluster_node_index] = survivor_index;
}
found += int(cluster.size()) - 1;
cluster.clear();
}
return found;
}
/** \} */
/* -------------------------------------------------------------------- */
/** \name BLI_kdtree_3d_deduplicate
* \{ */

17
source/blender/bmesh/operators/bmo_removedoubles.cc
View File

@@ -633,13 +633,8 @@ static int *bmesh_find_doubles_by_distance_impl(BMesh *bm,
const float dist,
const bool has_keep_vert)
{
if (verts_len == 0) {
return nullptr;
}
int *duplicates = MEM_malloc_arrayN<int>(verts_len, __func__);
bool found_duplicates = false;
blender::Vector<blender::float3> survivor_cos(verts_len);
KDTree_3d *tree = BLI_kdtree_3d_new(verts_len);
for (int i = 0; i < verts_len; i++) {
@@ -653,23 +648,13 @@ static int *bmesh_find_doubles_by_distance_impl(BMesh *bm,
}
BLI_kdtree_3d_balance(tree);
found_duplicates = BLI_kdtree_3d_calc_duplicates_and_center(
tree, dist, duplicates, (float(*)[3])survivor_cos.data()) != 0;
found_duplicates = BLI_kdtree_3d_calc_duplicates_fast(tree, dist, false, duplicates) != 0;
BLI_kdtree_3d_free(tree);
if (!found_duplicates) {
MEM_freeN(duplicates);
duplicates = nullptr;
}
else {
for (int i = 0; i < verts_len; i++) {
if (duplicates[i] == i) {
copy_v3_v3(verts[i]->co, survivor_cos[i]);
}
}
}
return duplicates;
}