RoboFlow 100 Biology dataset Collection

Loads one of the RoboFlow 100 Biology datasets with COCO-style bounding box annotations for object detection tasks.

rf100_biology_collection(
  dataset,
  split = c("train", "test", "valid"),
  transform = NULL,
  target_transform = NULL,
  download = FALSE
)

Arguments

dataset

Dataset to select within c("stomata_cell", "blood_cell", "parasite", "cell", "bacteria", "cotton_desease","mitosis", "phage", "liver_desease").

split

the subset of the dataset to choose between c("train", "test", "valid").

transform

Optional transform function applied to the image.

target_transform

Optional transform function applied to the target.

download

Logical. If TRUE, downloads the dataset if not present at root.

Value

A torch dataset. Each element is a named list with:

• x: H x W x 3 array representing the image.

• y: a list containing the target with:

  • image_id: numeric identifier of the x image.

  • labels: numeric identifier of the N bounding-box object class.

  • boxes: a torch_tensor of shape (N, 4) with bounding boxes, each in \((x_{min}, y_{min}, x_{max}, y_{max})\) format.

The returned item inherits the class image_with_bounding_box so it can be visualised with helper functions such as draw_bounding_boxes().

See also

Other detection_dataset: coco_detection_dataset(), pascal_voc_datasets, rf100_damage_collection(), rf100_document_collection(), rf100_infrared_collection(), rf100_medical_collection(), rf100_underwater_collection()

Examples

if (FALSE) { # \dontrun{
ds <- rf100_biology_collection(
  dataset = "stomata_cell",
  split = "test",
  transform = transform_to_tensor,
  download = TRUE
)
item <- ds[1]
boxed <- draw_bounding_boxes(item)
tensor_image_browse(boxed)
} # }