Generates a tf.data.Dataset from image files in a directory. If your directory structure is:

image_dataset_from_directory(
  directory,
  labels = "inferred",
  label_mode = "int",
  class_names = NULL,
  color_mode = "rgb",
  batch_size = 32,
  image_size = c(256, 256),
  shuffle = TRUE,
  seed = NULL,
  validation_split = NULL,
  subset = NULL,
  interpolation = "bilinear",
  follow_links = FALSE
)

Arguments

directory

Directory where the data is located. If labels is "inferred", it should contain subdirectories, each containing images for a class. Otherwise, the directory structure is ignored.

labels

Either "inferred" (labels are generated from the directory structure), or a list/tuple of integer labels of the same size as the number of image files found in the directory. Labels should be sorted according to the alphanumeric order of the image file paths (obtained via os.walk(directory) in Python).

label_mode
  • 'int': means that the labels are encoded as integers (e.g. for sparse_categorical_crossentropy loss). - 'categorical' means that the labels are encoded as a categorical vector (e.g. for categorical_crossentropy loss). - 'binary' means that the labels (there can be only 2) are encoded as float32 scalars with values 0 or 1 (e.g. for binary_crossentropy). - None (no labels).

class_names

Only valid if "labels" is "inferred". This is the explict list of class names (must match names of subdirectories). Used to control the order of the classes (otherwise alphanumerical order is used).

color_mode

One of "grayscale", "rgb", "rgba". Default: "rgb". Whether the images will be converted to have 1, 3, or 4 channels.

batch_size

Size of the batches of data. Default: 32.

image_size

Size to resize images to after they are read from disk. Defaults to (256, 256). Since the pipeline processes batches of images that must all have the same size, this must be provided.

shuffle

Whether to shuffle the data. Default: TRUE. If set to FALSE, sorts the data in alphanumeric order.

seed

Optional random seed for shuffling and transformations.

validation_split

Optional float between 0 and 1, fraction of data to reserve for validation.

subset

One of "training" or "validation". Only used if validation_split is set.

interpolation

String, the interpolation method used when resizing images. Defaults to bilinear. Supports bilinear, nearest, bicubic, area, lanczos3, lanczos5, gaussian, mitchellcubic.

follow_links

Whether to visits subdirectories pointed to by symlinks. Defaults to FALSE.