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@@ -1,4 +1,23 @@
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from mnist import MNIST
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+import numpy as np
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-mndata = MNIST('../../resources/download')
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-images, labels = mndata.load_training()
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+def load_training_samples():
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+ """
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+ Return np_images, labels
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+ where
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+ np_impages is a np.array of 60 000 x 784
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+ labels is a python list of expected answers
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+ """
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+ mndata = MNIST('../../resources/download')
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+
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+ images = [[]] # Contains vectors of 784 pixels image
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+ labels = [] # Contains expected response for each image
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+
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+ images, labels = mndata.load_training()
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+
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+ np_images = np.array(images, dtype=np.float64)
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+
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+ # Normalize data between 0.0 and 1.0
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+ np_images /= 255
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+
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+ return np_images, labels
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