Generate batches of image data with real-time data augmentation. The data will be looped over (in batches).
Generate batches of image data with real-time data augmentation. The data will be looped over (in batches).
image_data_generator( featurewise_center = FALSE, samplewise_center = FALSE, featurewise_std_normalization = FALSE, samplewise_std_normalization = FALSE, zca_whitening = FALSE, zca_epsilon = 1e-06, 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, feature-wise. |
samplewise_center |
Boolean. Set each sample mean to 0. |
featurewise_std_normalization |
Divide inputs by std of the dataset, feature-wise. |
samplewise_std_normalization |
Divide each input by its std. |
zca_whitening |
apply ZCA whitening. |
zca_epsilon |
Epsilon for ZCA whitening. Default is 1e-6. |
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). |
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