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+--- Thread: Kera how to load a dataset of images stored to my computer, not the Cifar-10? (/thread-27599.html)
Kera how to load a dataset of images stored to my computer, not the Cifar-10? - hobbyist - Jun-12-2020
Because I am searching but I cannot figure out how to make it work. Is there any way to load an image dataset stored in my PC ('png') so that it can be read by: trainX, trainY, testX, testY?? Because most of what I found is like this: (x_train, y_train), (x_test, y_test) = mnist.load_data() or (trainX, trainY), (testX, testY) = cifar10.load_data()
RE: trainX, trainY, testX, testY - Yoriz - Jun-12-2020
Do you mean like this?
def somefunc(): return ('trainX', 'trainY'), ('testX', 'testY') train, test = somefunc() print(train, test)Output:('trainX', 'trainY') ('testX', 'testY')Or maybe
def somefunc(): return 'trainX', 'trainY', 'testX', 'testY' trainX, trainY, testX, testY = somefunc() print(trainX, trainY, testX, testY )
Output:trainX trainY testX testYNote it depends how
mnist.load_data() returns its data, you could always make a function to return it how you wanted itsee this post for details of sequence unpacking
RE: trainX, trainY, testX, testY - hobbyist - Jun-12-2020
No, I mean this:
When I run
(x_train, y_train), (x_test, y_test) = mnist.load_data()it loads mnist dataset. I need instead of the mnist dataset to load the folder with the .png images that I have stored on my PC and contains 2 folders inside, the one folder has the training dataset and the other is the test dataset.
Thank you
RE: trainX, trainY, testX, testY - Yoriz - Jun-12-2020
Sorry, but from that one line and your description I don't understand
, maybe someone else will RE: trainX, trainY, testX, testY - hobbyist - Jun-12-2020
For example: this tutorial here:
CNN code
uses cifar10 dataset. I want to transform the code to load a dataset of images stored to my computer, not the Cifar-10. How do I achieve this?
(Better now?)
RE: trainX, trainY, testX, testY - Yoriz - Jun-12-2020
Kera > Code examples / Computer Vision / Image classification from scratch