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Ultra-fast 3D alpha shape computation with label propagation from input points to hull vertices and faces. Optimized for tree segmentation workflows.
This package uses RcppCGAL for geometric computations. RcppCGAL is automatically installed from CRAN as a dependency. No external CGAL installation is required.
Rcpp, RcppCGAL,
rgl, RvcglidR, RANN,
tictoc (for examples)# Install from CRAN (once available)
install.packages("ahull3D")
# Development version from GitHub
remotes::install_github("DijoG/ahull3D")library(lidR)
library(dplyr)
library(ahull3D)
# Read tree point cloud
laz_file <- system.file("extdata", "12trees.laz", package = "ahull3D")
trees <- lidR::readLAS(laz_file)
# Prepare data
lasdff <- treesd@data[,c("X", "Y", "Z", "pid")] %>%
as.data.frame() %>%
distinct(across(1:3), .keep_all = TRUE) %>%
as.matrix()
# Compute alpha hull with tree labels ("pid" propagation)
tictoc::tic()
a <-
ahull3D::ahull3D(
points = lasdff[,1:3],
input_truth = lasdff[,4], # "pid" column
alpha = 0.1
)
tictoc::toc() # ~25 seconds
# Access and check results
input_pid <- attr(a, "input_truth") # a vector of n vertices
face_pid <- attr(a, "face_truth") # a matrix of 3*n faces
length(input_pid) == ncol(a$vb) # should be TRUE
dim(face_pid) == dim(a$it) # should be TRUE TRUEThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.