Generate a vector point sf object of chip center locations for use with defineDynamicSegDataSet().
Usage
makeDynamicChipsSF(
pntPth,
pntName,
featPth,
featName,
extentPth,
extentName,
extentCrop = 50,
imgPth,
imgName,
doBackground = FALSE,
backgroundCnt,
backgroundDist,
useSeed = FALSE,
seed,
doShuffle = FALSE
)Arguments
- pntPth
Full folder path or relative path to vector point layer defining chip centers. Must include final forward slash.
- pntName
File name of point layer including file extension. Must contain "code" (numeric class code) and "class" (text class name) columns.
- featPth
Full folder path or relative path to vector polygon features used as the mask source. Must include final forward slash.
- featName
File name of polygon feature layer including file extension.
- extentPth
Full folder path or relative path to vector extent. Must include final forward slash.
- extentName
File name of extent including file extension.
- extentCrop
Amount to crop extent to avoid edge effects. We recommend cropping the extent more than the size of the chips you will use to avoid chips with NA cells. Default is 50 cells.
- imgPth
Path to image or predictor variable raster data. Must include the final forward slash.
- imgName
File name of image or predictor variable raster data including file extension.
- doBackground
Whether or not to randomly select background cells. Default is FALSE.
- backgroundCnt
Number of background cells to select.
- backgroundDist
Minimum allowed distance between randomly selected background locations and boundaries of reference features.
- useSeed
Whether or not to set a random seed for replicability. Default is FALSE.
- seed
Random seed value.
- doShuffle
Whether or not to shuffle the rows in the resulting table. Default is FALSE.
Value
sf dataframe object of center locations for chip creation with associated information as attributes.
Details
Requires an input vector point object defining chip center locations, an input vector polygon object of reference features used to generate segmentation masks, a boundary extent, and the path and name of the associated raster predictor variables. Note that the raster predictor variable must cover the full spatial extent defined by the extent object. If not, a smaller extent should be defined for which predictor variables are available.
The input point layer must contain a "code" column of numeric class codes and a "class" column of text class names. The input polygon feature layer is used only as the mask source during training and is not required to share attributes with the point layer, but must also contain "code" and "class" columns if class-specific masking is expected downstream.
The extent can be cropped to avoid generating chips without a full set of cells available. We recommend cropping by a factor larger than 50% the width/height of the desired chip size.
The tool returns a sf dataframe with class name ("class"), class numeric code ("code"), path to the image or predictor variables ("imgPth"), name of the image or predictor variables ("imgName"), the path to the input point layer ("pntPth"), the file name of the input point layer ("pntName"), the path to the input polygon features ("featPth"), the file name of the input polygon features ("featName"), the file path to the extent ("extentPth"), the file name for the extent ("extentName"), and the point geometry ("geometry").