Easy way to split data on your disk into train, test, and validation?

pip install split-folders

import splitfolders  # or import split_folders

input_folder = 'cell_images/'

# Split with a ratio.
# To only split into training and validation set, set a tuple to `ratio`, i.e, `(.8, .2)`.
#Train, val, test
splitfolders.ratio(input_folder, output="cell_images2", 
                   seed=42, ratio=(.7, .2, .1), 
                   group_prefix=None) # default values


# Split val/test with a fixed number of items e.g. 100 for each set.
# To only split into training and validation set, use a single number to `fixed`, i.e., `10`.
# enable oversampling of imbalanced datasets, works only with fixed
splitfolders.fixed(input_folder, output="cell_images2", 
                   seed=42, fixed=(35, 20), 
                   oversample=False, group_prefix=None)

Code generated in the video can be downloaded from here:

https://github.com/bnsreenu/python_fo…

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#deep-learning