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Modello.py
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Modello.py
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# Classe Modello
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D, Dropout
class model:
def __init__(self, num_k, k_size, p_size, num_n, lossfun='categorical_crossentropy'):
self.model = Sequential()
self.nclasses = 24
num_conv_layer = len(num_k)
# Creazione Layers Convoluzionali
for i in range(num_conv_layer):
self.model.add(Conv2D(num_k[i], kernel_size=(k_size[i],k_size[i]), activation='relu', input_shape=(28,28,1)))
self.model.add(MaxPooling2D(pool_size=(p_size[i],p_size[i])))
# Flattening
self.model.add(Flatten())
# Layer Totalmente Connesso
self.model.add(Dense(num_n, activation='relu'))
# Layer di Output
self.model.add(Dense(self.nclasses, activation='softmax'))
# Compilazione del modello
self.model.compile(optimizer='adam',
loss=lossfun,
metrics=['accuracy'],
)#shuffle=1