Visit seam candidates as the search finds them

Collecting every candidate within the radius into a vector cost more
than the search itself. Same order, so the seams are unchanged;
align_seam_points ~19.6 s at 0.1 mm / 2000k, was ~21.

src/libslic3r/GCode/SeamPlacer.cpp

@@ -1117,21 +1117,21 @@ std::optional<std::pair<size_t, size_t>> SeamPlacer::find_next_seam_in_layer(
     const size_t layer_idx, const float max_distance,
     const SeamPlacerImpl::SeamComparator &comparator) const {
   using namespace SeamPlacerImpl;
-  std::vector<size_t> nearby_points_indices = find_nearby_points(*layers[layer_idx].points_tree, projected_position,
-                                                                 max_distance);
-
-  if (nearby_points_indices.empty()) {
-    return {};
-  }
-
-  size_t best_nearby_point_index = nearby_points_indices[0];
-  size_t nearest_point_index = nearby_points_indices[0];
-
-  // Now find best nearby point, nearest point, and corresponding indices
-  for (const size_t &nearby_point_index : nearby_points_indices) {
+  // Find the best nearby point and the nearest one. A layer of a fine relief has tens of thousands of candidates within
+  // the radius, so they are looked at as the search finds them rather than collected into a vector first.
+  constexpr size_t none = std::numeric_limits<size_t>::max();
+  size_t best_nearby_point_index = none;
+  size_t nearest_point_index = none;
+  visit_nearby_points(*layers[layer_idx].points_tree, projected_position, max_distance,
+                      [&layers, &comparator, &projected_position, layer_idx, &best_nearby_point_index, &nearest_point_index]
+                      (size_t nearby_point_index) {
+    if (best_nearby_point_index == none) {
+      // The first point found starts both, as the first of the collected ones did.
+      best_nearby_point_index = nearest_point_index = nearby_point_index;
+    }
     const SeamCandidate &point = layers[layer_idx].points[nearby_point_index];
     if (point.perimeter.finalized) {
-      continue; // skip over finalized perimeters, try to find some that is not finalized
+      return; // skip over finalized perimeters, try to find some that is not finalized
     }
     if (comparator.is_first_better(point, layers[layer_idx].points[best_nearby_point_index],
                                    projected_position.head<2>())
@@ -1143,6 +1143,10 @@ std::optional<std::pair<size_t, size_t>> SeamPlacer::find_next_seam_in_layer(
         || layers[layer_idx].points[nearest_point_index].perimeter.finalized) {
       nearest_point_index = nearby_point_index;
     }
+  });
+
+  if (best_nearby_point_index == none) {
+    return {};
   }
 
   const SeamCandidate &best_nearby_point = layers[layer_idx].points[best_nearby_point_index];

src/libslic3r/KDTreeIndirect.hpp

@@ -313,6 +313,36 @@ std::vector<size_t> find_nearby_points(const KDTreeIndirectType &kdtree, const P
     return visitor.result;
 }
 
+// Visits the points within max_distance of center, in the order find_nearby_points() would collect them, and hands
+// each of them to `visitor_fn` instead of returning them all: a search over a dense set spends more on collecting the
+// points into a vector than on the search itself, and its caller usually keeps only a few of them.
+template<typename KDTreeIndirectType, typename PointType, typename VisitorFn>
+void visit_nearby_points(const KDTreeIndirectType &kdtree, const PointType &center,
+                         const typename KDTreeIndirectType::CoordType &max_distance, VisitorFn visitor_fn)
+{
+    using CoordType = typename KDTreeIndirectType::CoordType;
+
+    struct Visitor {
+        const KDTreeIndirectType &kdtree;
+        const PointType           center;
+        const CoordType           max_distance_squared;
+        VisitorFn                 visitor_fn;
+
+        unsigned int operator()(size_t idx, size_t dimension) {
+            auto dist = CoordType(0);
+            for (size_t i = 0; i < KDTreeIndirectType::NumDimensions; ++i) {
+                CoordType d = center[i] - kdtree.coordinate(idx, i);
+                dist += d * d;
+            }
+            if (dist < max_distance_squared)
+                visitor_fn(idx);
+            return kdtree.descent_mask(center[dimension], max_distance_squared, idx, dimension);
+        }
+    } visitor { kdtree, center, max_distance * max_distance, visitor_fn };
+
+    kdtree.visit(visitor);
+}
+
 template<typename KDTreeIndirectType, typename PointType>
 std::vector<size_t> find_nearby_points(const KDTreeIndirectType &kdtree, const PointType &center,
                                        const typename KDTreeIndirectType::CoordType& max_distance)