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@@ -78,6 +78,7 @@ def generate_model():
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model.add(Activation('relu'))
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model.add(MaxPooling2D(pool_size=(2, 1)))
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+ model.add(Flatten())
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model.add(Dense(70, kernel_regularizer=l2(0.01)))
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model.add(BatchNormalization())
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model.add(Activation('relu'))
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@@ -115,10 +116,10 @@ def load_train_data():
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# this is the augmentation configuration we will use for training
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train_datagen = ImageDataGenerator(
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- rescale=1. / 255,
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- shear_range=0.2,
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- zoom_range=0.2,
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- horizontal_flip=True,
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+ #rescale=1. / 255,
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+ #shear_range=0.2,
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+ #zoom_range=0.2,
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+ #horizontal_flip=True,
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preprocessing_function=svd_metric.get_s_model_data)
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train_generator = train_datagen.flow_from_directory(
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@@ -138,7 +139,7 @@ def load_validation_data():
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# this is the augmentation configuration we will use for testing:
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# only rescaling
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test_datagen = ImageDataGenerator(
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- rescale=1. / 255,
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+ #rescale=1. / 255,
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preprocessing_function=svd_metric.get_s_model_data)
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validation_generator = test_datagen.flow_from_directory(
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