RoboFlow 100 Damages dataset Collection — rf100_damage_collection • torchvision

Loads one of the RoboFlow 100 Damage & Risk assesment datasets with COCO-style bounding box annotations for object detection tasks.

rf100_damage_collection(
  dataset,
  split = c("train", "test", "valid"),
  transform = NULL,
  target_transform = NULL,
  download = FALSE
)

Arguments

dataset: Dataset to select within c("liquid_crystals", "solar_panel", "asbestos").
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_biology_collection(), rf100_document_collection(), rf100_infrared_collection(), rf100_medical_collection(), rf100_underwater_collection()

Examples

if (FALSE) { # \dontrun{
ds <- rf100_damage_collection(
  dataset = "solar_panel",
  split = "test",
  transform = transform_to_tensor,
  download = TRUE
)
item <- ds[1]
boxed <- draw_bounding_boxes(item)
tensor_image_browse(boxed)
} # }