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
| Arguments | Description |
|---|---|
| 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(). |
Details
Yields batches indefinitely, in an infinite loop.
Section
Yields
(x, y) where x is an array of image data and y is a array of corresponding labels. The generator loops indefinitely.
See Also
Other image preprocessing: fit_image_data_generator(), flow_images_from_dataframe(), flow_images_from_directory(), image_load(), image_to_array()