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@PhilipPurwoko
Created December 9, 2020 01:44
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# Create model structure
model = keras.Sequential([
# Input Layer
keras.layers.Conv2D(input_shape=(224,224,3),filters=32,kernel_size=(3,3),activation='relu'),
keras.layers.MaxPooling2D(),
# Hidden Layer
keras.layers.Conv2D(input_shape=(224,224,3),filters=64,kernel_size=(3,3),activation='relu'),
keras.layers.MaxPooling2D(),
keras.layers.Conv2D(input_shape=(224,224,3),filters=128,kernel_size=(3,3),activation='relu'),
keras.layers.MaxPooling2D(),
keras.layers.Flatten(),
keras.layers.Dense(128),
keras.layers.Activation('relu'),
# Output Layer
keras.layers.Dense(2),
keras.layers.Activation('softmax')
])
# Compile model
model.compile(loss='categorical_crossentropy',optimizer=keras.optimizers.Adam(),metrics=['acc'])
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