Attach visual images to spectral map objects — add_visual

add_visual_image() stores a visual image and map-to-image alignment metadata on an OpenSpecy or Specs object. visual_image() retrieves that attribute. detect_image_origin() detects red Thermo Fisher iN10 map boxes in visual images and returns the image coordinates needed for overlays and feature color extraction.

Usage

add_visual_image(
  x,
  image,
  bottom_left = NULL,
  top_right = NULL,
  source = NULL,
  detection_method = NULL,
  diagnostics = NULL,
  transform = NULL,
  ...
)

visual_image(x, require = FALSE, ...)

detect_image_origin(
  image,
  red_threshold = 50,
  red_ratio = 2,
  min_pixels = 1,
  diagnostics = TRUE,
  ...
)

Arguments

x: an OpenSpecy or Specs object.
image: image path, raster, matrix, array, raw BMP bytes, or an existing visual-image list.
bottom_left, top_right: numeric length-2 vectors giving the lower-left and upper-right corners of the spectral map in image pixel coordinates. Image x values are left-to-right and image y values are top-to-bottom.
source: optional image source label or file path.
detection_method: optional description of how the origin was detected.
diagnostics: optional diagnostic data to store with the image.
transform: optional list describing a custom transform.
require: logical; should visual_image() error when no image is attached?
red_threshold: minimum red-channel value on the 0-255 scale.
red_ratio: minimum red-to-green and red-to-blue ratio for red-box detection.
min_pixels: minimum number of red pixels required for origin detection.
...: reserved for future methods.

Value

add_visual_image() returns x with a visual_image attribute. visual_image() and detect_image_origin() return lists.

Examples

data("raman_hdpe")
img <- array(1, dim = c(10, 10, 3))
with_image <- add_visual_image(raman_hdpe, img,
                               bottom_left = c(1, 10),
                               top_right = c(10, 1))
visual_image(with_image)$bottom_left
#> [1]  1 10