Local Point-Count Processing for Coral Photoquadrats


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Documentation for package ‘pointcoral’ version 0.1.0

Help Pages

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