Package: pointcoral 0.1.0

Elvin Cordero

pointcoral: Local Point-Count Processing for Coral Photoquadrats

Imports Coral Point Count with Excel extensions (CPCe) point-count annotations and related exported tables, standardizes labels with a user-supplied crosswalk, creates ecological cover summaries, writes quality-control overlays, and exports machine-learning-ready point labels, image patches, sparse masks, and train/validation/test splits. The package is fully local and does not depend on third-party web platforms, user accounts, or other closed services. CPCe methods are described by Kohler and Gill (2006) "Coral Point Count with Excel extensions (CPCe): A Visual Basic program for the determination of coral and substrate coverage using random point count methodology" <doi:10.1016/j.cageo.2005.11.009>.

Authors:Elvin Cordero [aut, cre]

pointcoral_0.1.0.tar.gz
pointcoral_0.1.0.zip(r-4.7-any)pointcoral_0.1.0.zip(r-4.6-any)pointcoral_0.1.0.zip(r-4.5-any)
pointcoral_0.1.0.tgz(r-4.6-any)pointcoral_0.1.0.tgz(r-4.5-any)
pointcoral_0.1.0.tar.gz(r-4.7-any)pointcoral_0.1.0.tar.gz(r-4.6-any)
pointcoral_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
pointcoral/json (API)

# Install 'pointcoral' in R:

install.packages('pointcoral', repos = c('https://el-cordero.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/el-cordero/pointcoral/issues

Pkgdown/docs site:https://el-cordero.github.io

On CRAN:

4.18 score 1 stars 328 downloads 29 exports 42 dependencies

Last updated from:946314cb14. Checks:9 OK. Indexed: yes.
A new build is currently in progress.

Target	Result	Time
linux-devel	OK	177
source / vignettes	OK	200
linux-release	OK	181
macos-release	OK	122
macos-oldrel	OK	118
windows-devel	OK	140
windows-release	OK	130
windows-oldrel	OK	122
wasm-release	OK	143

Exports:check_crosswalk convert_cpce_coords export_coralnet_points export_segformer_sparse export_yolo_classification extract_point_patches make_class_lookup make_ml_points make_sparse_masks match_images plot_points_on_image qc_label_summary read_cpce_export read_cpce_file read_cpce_folder read_cpce_output_raw_tabs read_label_crosswalk run_pointcoral split_ml_points standardize_labels summarize_images summarize_points summarize_sites summarize_transects validate_points write_ml_points_csv write_pointcoral_dataset write_qc_overlays write_summary_tables

Dependencies:bit bit64 cellranger cli clipr cpp11 crayon curl dplyr fs generics glue hms janitor lifecycle lubridate magick magrittr pillar pkgconfig png prettyunits progress purrr R6 Rcpp readr readxl rematch rlang snakecase stringi stringr tibble tidyr tidyselect timechange tzdb utf8 vctrs vroom withr

Get started with pointcoral

Rendered frompointcoral-workflow.Rmdusingknitr::rmarkdown

Last update: 2026-07-18
Started: 2026-06-07

Help page	Topics
Check a label crosswalk against point data	check_crosswalk
Convert CPCe coordinates to image pixel coordinates	convert_cpce_coords
Export point labels in a simple CoralNet-style CSV	export_coralnet_points
Export SegFormer-style sparse masks	export_segformer_sparse
Export YOLO-style classification patches	export_yolo_classification
Extract point-centered image patches	extract_point_patches
Make a class lookup table	make_class_lookup
Make an ML-ready point-label table	make_ml_points
Create sparse semantic segmentation masks from point labels	make_sparse_masks
Match CPCe point rows to image files	match_images
Plot CPCe points on an image	plot_points_on_image
Summarize point-label QC issues	qc_label_summary
Read a CPCe CSV or Excel export	read_cpce_export
Read one CPCe '.cpc' file	read_cpce_file
Read CPCe files and exports from a folder	read_cpce_folder
Read _raw sheets from a CPCe output workbook	read_cpce_output_raw_tabs
Read a label crosswalk	read_label_crosswalk
Run the full pointcoral workflow from folders	run_pointcoral
Split ML points into train/validation/test sets	split_ml_points
Standardize CPCe labels with a crosswalk	standardize_labels
Summarize points at image level	summarize_images
Summarize point counts and percent cover	summarize_points
Summarize points at site level	summarize_sites
Summarize points at transect level	summarize_transects
Validate a point table	validate_points
Write ML point CSV files	write_ml_points_csv
Write a complete pointcoral dataset from imported points	write_pointcoral_dataset
Write QC overlays for point annotations	write_qc_overlays
Write ecological summary tables	write_summary_tables

Package: pointcoral 0.1.0

pointcoral: Local Point-Count Processing for Coral Photoquadrats

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