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When setting parameter validation_split to a value larger than 0.0, how does the Keras ImageDataGenerator select the validation images? Are they randomly selected from the input directory, or are the last n samples used, similar to the validation_split parameter for model.fit? More specifically, I'm primarily interested in the following situation: considering the flow_from_directory method, a shuffle parameter is available to randomize the data. However, is the shuffle applied after the input directory is splitted into a train and validation set by the ImageDataGenerator, or before?
I went through the official Keras and TF pages but they both show the same explanation of validation_split, namely:
validation_split: Float. Fraction of images reserved for validation (strictly between 0 and 1).
I also went through the source code (both Keras and TF) without any luck of finding additional information.
The text was updated successfully, but these errors were encountered:
Not sure why is that not visible in @Dref360s answer, but important part is last sentence:
split: tuple of floats (e.g. (0.2, 0.6)) to only take into
account a certain fraction of files in each directory.
E.g.: segment=(0.6, 1.0) would only account for last 40 percent
of images in each directory.
Actually, files are Python sorted() and if you format image names properly, you could use this feature pretty easy. Otherwise you might get something like this:
When setting parameter
validation_split
to a value larger than 0.0, how does the KerasImageDataGenerator
select the validation images? Are they randomly selected from the input directory, or are the lastn
samples used, similar to thevalidation_split
parameter formodel.fit
? More specifically, I'm primarily interested in the following situation: considering theflow_from_directory
method, ashuffle
parameter is available to randomize the data. However, is the shuffle applied after the input directory is splitted into a train and validation set by theImageDataGenerator
, or before?I went through the official Keras and TF pages but they both show the same explanation of
validation_split
, namely:I also went through the source code (both Keras and TF) without any luck of finding additional information.
The text was updated successfully, but these errors were encountered: