Generate minibatches of image data with realtime data augmentation.
image_data_generator(featurewise_center = FALSE, samplewise_center = FALSE, featurewise_std_normalization = FALSE, samplewise_std_normalization = FALSE, zca_whitening = FALSE, zca_epsilon = 1e06, rotation_range = 0, width_shift_range = 0, height_shift_range = 0, brightness_range = NULL, shear_range = 0, zoom_range = 0, channel_shift_range = 0, fill_mode = "nearest", cval = 0, horizontal_flip = FALSE, vertical_flip = FALSE, rescale = NULL, preprocessing_function = NULL, data_format = NULL, validation_split = 0)
featurewise_center  set input mean to 0 over the dataset. 

samplewise_center  set each sample mean to 0. 
featurewise_std_normalization  divide inputs by std of the dataset. 
samplewise_std_normalization  divide each input by its std. 
zca_whitening  apply ZCA whitening. 
zca_epsilon  Epsilon for ZCA whitening. Default is 1e6. 
rotation_range  degrees (0 to 180). 
width_shift_range  fraction of total width. 
height_shift_range  fraction of total height. 
brightness_range  the range of brightness to apply 
shear_range  shear intensity (shear angle in radians). 
zoom_range  amount of zoom. if scalar z, zoom will be randomly picked
in the range 
channel_shift_range  shift range for each channels. 
fill_mode  One of "constant", "nearest", "reflect" or "wrap". Points outside the boundaries of the input are filled according to the given mode:

cval  value used for points outside the boundaries when fill_mode is 'constant'. Default is 0. 
horizontal_flip  whether to randomly flip images horizontally. 
vertical_flip  whether to randomly flip images vertically. 
rescale  rescaling factor. If NULL or 0, no rescaling is applied, otherwise we multiply the data by the value provided (before applying any other transformation). 
preprocessing_function  function that will be implied on each input. The function will run before any other modification on it. The function should take one argument: one image (tensor with rank 3), and should output a tensor with the same shape. 
data_format  'channels_first' or 'channels_last'. In 'channels_first'
mode, the channels dimension (the depth) is at index 1, in 'channels_last'
mode it is at index 3. It defaults to the 
validation_split  fraction of images reserved for validation (strictly between 0 and 1). 