keras (version 2.13.0)

flow_images_from_data: Generates batches of augmented/normalized data from image data and labels

Description

Generates batches of augmented/normalized data from image data and labels

Usage

flow_images_from_data(
  x,
  y = NULL,
  generator = image_data_generator(),
  batch_size = 32,
  shuffle = TRUE,
  sample_weight = NULL,
  seed = NULL,
  save_to_dir = NULL,
  save_prefix = "",
  save_format = "png",
  subset = NULL
)

Arguments

x

data. Should have rank 4. In case of grayscale data, the channels axis should have value 1, and in case of RGB data, it should have value 3.

y

labels (can be NULL if no labels are required)

generator

Image data generator to use for augmenting/normalizing image data.

batch_size

int (default: 32).

shuffle

boolean (defaut: TRUE).

sample_weight

Sample weights.

seed

int (default: NULL).

save_to_dir

NULL or str (default: NULL). This allows you to optionally specify a directory to which to save the augmented pictures being generated (useful for visualizing what you are doing).

save_prefix

str (default: ''). Prefix to use for filenames of saved pictures (only relevant if save_to_dir is set).

save_format

one of "png", "jpeg" (only relevant if save_to_dir is set). Default: "png".

subset

Subset of data ("training" or "validation") if validation_split is set in image_data_generator().

Yields

(x, y) where x is an array of image data and y is a array of corresponding labels. The generator loops indefinitely.

Details

Yields batches indefinitely, in an infinite loop.

See Also

Other image preprocessing: fit_image_data_generator(), flow_images_from_dataframe(), flow_images_from_directory(), image_load(), image_to_array()