boxer {boundingbox}

Create a bounding box in an image based on selected points

Description

boxer allows the user to identify an area in an image around which to generate a bounding box and set a common classifier for all images.

Usage

boxer(
  names,
  file_path_input,
  color = "red",
  resize_x = NA,
  resize_y = NA,
  classifier = NA,
  batch = length(names),
  outbox = FALSE,
  file_path_output = NA,
  show_classifier = FALSE
)

Arguments

names

A vector that contains the names of JPG, PNG, or BMP image files.

file_path_input

The directory that contains the image files.

color

The name of the color for selected points and the bounding box. Default is "red".

resize_x

Number of pixels to resize the x-axis. Default is NA to keep original size.

resize_y

Number of pixels to resize the y-axis. Default is NA to keep original size.

classifier

Character string to add a classifier. Default is NA.

batch

Number of images before prompt to truncate stream. Default is length(names).

outbox

Logical to run outBox and output images. Default is F.

file_path_output

The directory where to save annotated images if outbox is T.

show_classifier

Logical to include the classifier above the bounding box if outbox is T. Default is F.

Details

Stream a series of images (JPEG, PNG, BMP) from a directory. As each image appears, indicate between 2 and 26 points around which boxer will calculate a bounding box. The name of the original file, the bounding box coordinates, and optional image resize values, classifier and box color are returned in a dataframe. Boxer also offers the option to call the outBox function that will output each image with its bounding box. If outputting the images, the show_classifier parameter controls whether or not to show the class as a label above the bounding box.

When an image appears, use the left mouse button to select the series of points, and the right mouse button to signal completion and to move to the next image. At least two points must be selected to record a bounding box. If more than 26 points are selected, only the first 26 will be used. To skip creating a bounding box for the current image, select the right mouse button without selecting any points. Messages noting the images skipped will appear at the end.

The dataframe of bounding box coordinates will only be returned when all of the images have been cycled through, unless you set the batch parameter. The batch parameter allows for the images to be processed in batches with the option to terminate and generate the output file at the end of each batch. The batch parameter can be set for the number of images to cycle through before the user is prompted to truncate the stream. Selecting "y" at the prompt will truncate the stream and return the bounding box coordinates for all of the images up to that point. Selecting any other key will continue to stream through the next batch of images.

If using the classifier and color parameters, boxer assumes all of the images are classified the same. To be able to set the classifier per bounding box, or to be able to generate multiple bounding boxes per image, use the boxer2 function.

Value

A dataframe with the bounding box coordinates and classifier for each image. Note the y-coordinate extends downward, not upward. Will also output new image file with the bounding box annotation for each of the images processed if outbox is set to T. The name of each output image file will be the same as the corresponding input file prefixed with "out_".

Examples

## Not run: 
boxer_results <- boxer(names = c("S2.jpg"),
file_path_input = system.file("extdata", package = "boundingbox"),
resize_x = 224, resize_y = 224, classifier = "dog", outbox = FALSE)

## End(Not run)