Hi in our project we use randint method to produce real samples for machine learning but it does not work. How can we fix it?
def generate_real_samples(dataset, n_samples, patch_shape):
# unpack dataset
trainA, trainB = dataset
# choose random instances
ix = random.randint(0, trainA.shape[0], n_samples)
# retrieve selected images
X1, X2 = trainA[ix], trainB[ix]
# generate 'real' class labels (1)
y = numpy.ones((n_samples, patch_shape, patch_shape, 1))
return [X1, X2], y
error is about parameter dimension. Explanation of this code is here
The generate_real_samples() function below will prepare a batch of random pairs of images from the training dataset, and the corresponding discriminator label of class=1 to indicate they are real.
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