ImageDataLoaders from folder — ImageDataLoaders_from

Create from imagenet style dataset in `path` with `train` and `valid` subfolders (or provide `valid_pct`)

ImageDataLoaders_from_folder(
  path,
  train = "train",
  valid = "valid",
  valid_pct = NULL,
  seed = NULL,
  vocab = NULL,
  item_tfms = NULL,
  batch_tfms = NULL,
  bs = 64,
  val_bs = NULL,
  shuffle_train = TRUE,
  device = NULL,
  size = NULL,
  ...
)

Arguments

path: The folder where to work
train: train data
valid: validation data
valid_pct: validion percentage
seed: random seed
vocab: vocabulary
item_tfms: One or several transforms applied to the items before batching them
batch_tfms: One or several transforms applied to the batches once they are formed
bs: batch size
val_bs: The batch size for the validation DataLoader (defaults to bs)
shuffle_train: If we shuffle the training DataLoader or not
device: device name
size: image size
...: additional parameters to pass