Created
September 20, 2020 15:11
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# partition the data into training and testing splits using 75% of | |
# the data for training and the remaining 25% for testing | |
(trainX, testX, trainY, testY) = train_test_split(data, labels, | |
test_size=0.20, stratify=labels, random_state=42) | |
# construct the training image generator for data augmentation | |
aug = ImageDataGenerator( | |
rotation_range=20, | |
zoom_range=0.15, | |
width_shift_range=0.2, | |
height_shift_range=0.2, | |
shear_range=0.15, | |
horizontal_flip=True, | |
fill_mode="nearest") |
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