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def get_model(dim = (224,224,3)):
keras.backend.clear_session()
model = keras.models.Sequential()
model.add(keras.layers.Conv2D(32,(3,3),activation='relu',input_shape=dim))
model.add(keras.layers.Conv2D(32,(3,3),activation='relu',padding="valid",))
model.add(keras.layers.MaxPooling2D((2,2)))
model.add(keras.layers.Dropout(.4))
model.add(keras.layers.Conv2D(32,(5,5),activation='relu',padding="valid"))
model.add(keras.layers.MaxPooling2D((2,2)))
model.add(keras.layers.Dropout(.4))
model.add(keras.layers.Conv2D(64,(5,5),activation='relu',padding="valid"))
model.add(keras.layers.MaxPooling2D((2,2)))
model.add(keras.layers.Dropout(.4))
model.add(keras.layers.Conv2D(64,(5,5),activation='relu',padding="valid"))
model.add(keras.layers.MaxPooling2D((2,2)))
model.add(keras.layers.Dropout(.4))
model.add(keras.layers.Flatten())
model.add(keras.layers.Dropout(.4))
model.add(keras.layers.Dense(2,activation='softmax'))
model.summary()
return model
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